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postgres/src/backend/executor/execPartition.c

2108 lines
66 KiB

/*-------------------------------------------------------------------------
*
* execPartition.c
* Support routines for partitioning.
*
* Portions Copyright (c) 1996-2021, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
* IDENTIFICATION
* src/backend/executor/execPartition.c
*
*-------------------------------------------------------------------------
*/
#include "postgres.h"
#include "access/table.h"
tableam: Add and use scan APIs. Too allow table accesses to be not directly dependent on heap, several new abstractions are needed. Specifically: 1) Heap scans need to be generalized into table scans. Do this by introducing TableScanDesc, which will be the "base class" for individual AMs. This contains the AM independent fields from HeapScanDesc. The previous heap_{beginscan,rescan,endscan} et al. have been replaced with a table_ version. There's no direct replacement for heap_getnext(), as that returned a HeapTuple, which is undesirable for a other AMs. Instead there's table_scan_getnextslot(). But note that heap_getnext() lives on, it's still used widely to access catalog tables. This is achieved by new scan_begin, scan_end, scan_rescan, scan_getnextslot callbacks. 2) The portion of parallel scans that's shared between backends need to be able to do so without the user doing per-AM work. To achieve that new parallelscan_{estimate, initialize, reinitialize} callbacks are introduced, which operate on a new ParallelTableScanDesc, which again can be subclassed by AMs. As it is likely that several AMs are going to be block oriented, block oriented callbacks that can be shared between such AMs are provided and used by heap. table_block_parallelscan_{estimate, intiialize, reinitialize} as callbacks, and table_block_parallelscan_{nextpage, init} for use in AMs. These operate on a ParallelBlockTableScanDesc. 3) Index scans need to be able to access tables to return a tuple, and there needs to be state across individual accesses to the heap to store state like buffers. That's now handled by introducing a sort-of-scan IndexFetchTable, which again is intended to be subclassed by individual AMs (for heap IndexFetchHeap). The relevant callbacks for an AM are index_fetch_{end, begin, reset} to create the necessary state, and index_fetch_tuple to retrieve an indexed tuple. Note that index_fetch_tuple implementations need to be smarter than just blindly fetching the tuples for AMs that have optimizations similar to heap's HOT - the currently alive tuple in the update chain needs to be fetched if appropriate. Similar to table_scan_getnextslot(), it's undesirable to continue to return HeapTuples. Thus index_fetch_heap (might want to rename that later) now accepts a slot as an argument. Core code doesn't have a lot of call sites performing index scans without going through the systable_* API (in contrast to loads of heap_getnext calls and working directly with HeapTuples). Index scans now store the result of a search in IndexScanDesc->xs_heaptid, rather than xs_ctup->t_self. As the target is not generally a HeapTuple anymore that seems cleaner. To be able to sensible adapt code to use the above, two further callbacks have been introduced: a) slot_callbacks returns a TupleTableSlotOps* suitable for creating slots capable of holding a tuple of the AMs type. table_slot_callbacks() and table_slot_create() are based upon that, but have additional logic to deal with views, foreign tables, etc. While this change could have been done separately, nearly all the call sites that needed to be adapted for the rest of this commit also would have been needed to be adapted for table_slot_callbacks(), making separation not worthwhile. b) tuple_satisfies_snapshot checks whether the tuple in a slot is currently visible according to a snapshot. That's required as a few places now don't have a buffer + HeapTuple around, but a slot (which in heap's case internally has that information). Additionally a few infrastructure changes were needed: I) SysScanDesc, as used by systable_{beginscan, getnext} et al. now internally uses a slot to keep track of tuples. While systable_getnext() still returns HeapTuples, and will so for the foreseeable future, the index API (see 1) above) now only deals with slots. The remainder, and largest part, of this commit is then adjusting all scans in postgres to use the new APIs. Author: Andres Freund, Haribabu Kommi, Alvaro Herrera Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de https://postgr.es/m/20160812231527.GA690404@alvherre.pgsql
7 years ago
#include "access/tableam.h"
#include "catalog/partition.h"
#include "catalog/pg_inherits.h"
#include "catalog/pg_type.h"
#include "executor/execPartition.h"
#include "executor/executor.h"
#include "foreign/fdwapi.h"
#include "mb/pg_wchar.h"
#include "miscadmin.h"
#include "nodes/makefuncs.h"
#include "partitioning/partbounds.h"
#include "partitioning/partdesc.h"
#include "partitioning/partprune.h"
#include "rewrite/rewriteManip.h"
#include "utils/acl.h"
#include "utils/lsyscache.h"
#include "utils/partcache.h"
#include "utils/rls.h"
#include "utils/ruleutils.h"
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/*-----------------------
* PartitionTupleRouting - Encapsulates all information required to
* route a tuple inserted into a partitioned table to one of its leaf
* partitions.
*
* partition_root
* The partitioned table that's the target of the command.
*
* partition_dispatch_info
* Array of 'max_dispatch' elements containing a pointer to a
* PartitionDispatch object for every partitioned table touched by tuple
* routing. The entry for the target partitioned table is *always*
* present in the 0th element of this array. See comment for
* PartitionDispatchData->indexes for details on how this array is
* indexed.
*
* nonleaf_partitions
* Array of 'max_dispatch' elements containing pointers to fake
* ResultRelInfo objects for nonleaf partitions, useful for checking
* the partition constraint.
*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* num_dispatch
* The current number of items stored in the 'partition_dispatch_info'
* array. Also serves as the index of the next free array element for
* new PartitionDispatch objects that need to be stored.
*
* max_dispatch
* The current allocated size of the 'partition_dispatch_info' array.
*
* partitions
* Array of 'max_partitions' elements containing a pointer to a
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
* ResultRelInfo for every leaf partition touched by tuple routing.
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* Some of these are pointers to ResultRelInfos which are borrowed out of
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
* the owning ModifyTableState node. The remainder have been built
* especially for tuple routing. See comment for
* PartitionDispatchData->indexes for details on how this array is
* indexed.
*
* is_borrowed_rel
* Array of 'max_partitions' booleans recording whether a given entry
* in 'partitions' is a ResultRelInfo pointer borrowed from the owning
* ModifyTableState node, rather than being built here.
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
*
* num_partitions
* The current number of items stored in the 'partitions' array. Also
* serves as the index of the next free array element for new
* ResultRelInfo objects that need to be stored.
*
* max_partitions
* The current allocated size of the 'partitions' array.
*
* memcxt
* Memory context used to allocate subsidiary structs.
*-----------------------
*/
struct PartitionTupleRouting
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
{
Relation partition_root;
PartitionDispatch *partition_dispatch_info;
ResultRelInfo **nonleaf_partitions;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
int num_dispatch;
int max_dispatch;
ResultRelInfo **partitions;
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
bool *is_borrowed_rel;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
int num_partitions;
int max_partitions;
MemoryContext memcxt;
};
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/*-----------------------
* PartitionDispatch - information about one partitioned table in a partition
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* hierarchy required to route a tuple to any of its partitions. A
* PartitionDispatch is always encapsulated inside a PartitionTupleRouting
* struct and stored inside its 'partition_dispatch_info' array.
*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* reldesc
* Relation descriptor of the table
*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* key
* Partition key information of the table
*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* keystate
* Execution state required for expressions in the partition key
*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* partdesc
* Partition descriptor of the table
*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* tupslot
* A standalone TupleTableSlot initialized with this table's tuple
* descriptor, or NULL if no tuple conversion between the parent is
* required.
*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* tupmap
* TupleConversionMap to convert from the parent's rowtype to this table's
* rowtype (when extracting the partition key of a tuple just before
* routing it through this table). A NULL value is stored if no tuple
* conversion is required.
*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* indexes
* Array of partdesc->nparts elements. For leaf partitions the index
* corresponds to the partition's ResultRelInfo in the encapsulating
* PartitionTupleRouting's partitions array. For partitioned partitions,
* the index corresponds to the PartitionDispatch for it in its
* partition_dispatch_info array. -1 indicates we've not yet allocated
* anything in PartitionTupleRouting for the partition.
*-----------------------
*/
typedef struct PartitionDispatchData
{
Relation reldesc;
PartitionKey key;
List *keystate; /* list of ExprState */
PartitionDesc partdesc;
TupleTableSlot *tupslot;
AttrMap *tupmap;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
int indexes[FLEXIBLE_ARRAY_MEMBER];
} PartitionDispatchData;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
static ResultRelInfo *ExecInitPartitionInfo(ModifyTableState *mtstate,
EState *estate, PartitionTupleRouting *proute,
PartitionDispatch dispatch,
ResultRelInfo *rootResultRelInfo,
int partidx);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
static void ExecInitRoutingInfo(ModifyTableState *mtstate,
EState *estate,
PartitionTupleRouting *proute,
PartitionDispatch dispatch,
ResultRelInfo *partRelInfo,
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
int partidx,
bool is_borrowed_rel);
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
static PartitionDispatch ExecInitPartitionDispatchInfo(EState *estate,
PartitionTupleRouting *proute,
Fix permission checks on constraint violation errors on partitions. If a cross-partition UPDATE violates a constraint on the target partition, and the columns in the new partition are in different physical order than in the parent, the error message can reveal columns that the user does not have SELECT permission on. A similar bug was fixed earlier in commit 804b6b6db4. The cause of the bug is that the callers of the ExecBuildSlotValueDescription() function got confused when constructing the list of modified columns. If the tuple was routed from a parent, we converted the tuple to the parent's format, but the list of modified columns was grabbed directly from the child's RTE entry. ExecUpdateLockMode() had a similar issue. That lead to confusion on which columns are key columns, leading to wrong tuple lock being taken on tables referenced by foreign keys, when a row is updated with INSERT ON CONFLICT UPDATE. A new isolation test is added for that corner case. With this patch, the ri_RangeTableIndex field is no longer set for partitions that don't have an entry in the range table. Previously, it was set to the RTE entry of the parent relation, but that was confusing. NOTE: This modifies the ResultRelInfo struct, replacing the ri_PartitionRoot field with ri_RootResultRelInfo. That's a bit risky to backpatch, because it breaks any extensions accessing the field. The change that ri_RangeTableIndex is not set for partitions could potentially break extensions, too. The ResultRelInfos are visible to FDWs at least, and this patch required small changes to postgres_fdw. Nevertheless, this seem like the least bad option. I don't think these fields widely used in extensions; I don't think there are FDWs out there that uses the FDW "direct update" API, other than postgres_fdw. If there is, you will get a compilation error, so hopefully it is caught quickly. Backpatch to 11, where support for both cross-partition UPDATEs, and unique indexes on partitioned tables, were added. Reviewed-by: Amit Langote Security: CVE-2021-3393
5 years ago
Oid partoid, PartitionDispatch parent_pd,
int partidx, ResultRelInfo *rootResultRelInfo);
static void FormPartitionKeyDatum(PartitionDispatch pd,
TupleTableSlot *slot,
EState *estate,
Datum *values,
bool *isnull);
static int get_partition_for_tuple(PartitionDispatch pd, Datum *values,
bool *isnull);
static char *ExecBuildSlotPartitionKeyDescription(Relation rel,
Datum *values,
bool *isnull,
int maxfieldlen);
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
static List *adjust_partition_colnos(List *colnos, ResultRelInfo *leaf_part_rri);
Restructure creation of run-time pruning steps. Previously, gen_partprune_steps() always built executor pruning steps using all suitable clauses, including those containing PARAM_EXEC Params. This meant that the pruning steps were only completely safe for executor run-time (scan start) pruning. To prune at executor startup, we had to ignore the steps involving exec Params. But this doesn't really work in general, since there may be logic changes needed as well --- for example, pruning according to the last operator's btree strategy is the wrong thing if we're not applying that operator. The rules embodied in gen_partprune_steps() and its minions are sufficiently complicated that tracking their incremental effects in other logic seems quite impractical. Short of a complete redesign, the only safe fix seems to be to run gen_partprune_steps() twice, once to create executor startup pruning steps and then again for run-time pruning steps. We can save a few cycles however by noting during the first scan whether we rejected any clauses because they involved exec Params --- if not, we don't need to do the second scan. In support of this, refactor the internal APIs in partprune.c to make more use of passing information in the GeneratePruningStepsContext struct, rather than as separate arguments. This is, I hope, the last piece of our response to a bug report from Alan Jackson. Back-patch to v11 where this code came in. Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
7 years ago
static void ExecInitPruningContext(PartitionPruneContext *context,
List *pruning_steps,
PartitionDesc partdesc,
PartitionKey partkey,
PlanState *planstate);
static void find_matching_subplans_recurse(PartitionPruningData *prunedata,
PartitionedRelPruningData *pprune,
bool initial_prune,
Bitmapset **validsubplans);
/*
* ExecSetupPartitionTupleRouting - sets up information needed during
* tuple routing for partitioned tables, encapsulates it in
* PartitionTupleRouting, and returns it.
*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* Callers must use the returned PartitionTupleRouting during calls to
* ExecFindPartition(). The actual ResultRelInfo for a partition is only
* allocated when the partition is found for the first time.
*
* The current memory context is used to allocate this struct and all
* subsidiary structs that will be allocated from it later on. Typically
* it should be estate->es_query_cxt.
*/
PartitionTupleRouting *
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
ExecSetupPartitionTupleRouting(EState *estate, Relation rel)
{
PartitionTupleRouting *proute;
/*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* Here we attempt to expend as little effort as possible in setting up
* the PartitionTupleRouting. Each partition's ResultRelInfo is built on
* demand, only when we actually need to route a tuple to that partition.
* The reason for this is that a common case is for INSERT to insert a
* single tuple into a partitioned table and this must be fast.
*/
proute = (PartitionTupleRouting *) palloc0(sizeof(PartitionTupleRouting));
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
proute->partition_root = rel;
proute->memcxt = CurrentMemoryContext;
/* Rest of members initialized by zeroing */
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/*
* Initialize this table's PartitionDispatch object. Here we pass in the
* parent as NULL as we don't need to care about any parent of the target
* partitioned table.
*/
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
ExecInitPartitionDispatchInfo(estate, proute, RelationGetRelid(rel),
Fix permission checks on constraint violation errors on partitions. If a cross-partition UPDATE violates a constraint on the target partition, and the columns in the new partition are in different physical order than in the parent, the error message can reveal columns that the user does not have SELECT permission on. A similar bug was fixed earlier in commit 804b6b6db4. The cause of the bug is that the callers of the ExecBuildSlotValueDescription() function got confused when constructing the list of modified columns. If the tuple was routed from a parent, we converted the tuple to the parent's format, but the list of modified columns was grabbed directly from the child's RTE entry. ExecUpdateLockMode() had a similar issue. That lead to confusion on which columns are key columns, leading to wrong tuple lock being taken on tables referenced by foreign keys, when a row is updated with INSERT ON CONFLICT UPDATE. A new isolation test is added for that corner case. With this patch, the ri_RangeTableIndex field is no longer set for partitions that don't have an entry in the range table. Previously, it was set to the RTE entry of the parent relation, but that was confusing. NOTE: This modifies the ResultRelInfo struct, replacing the ri_PartitionRoot field with ri_RootResultRelInfo. That's a bit risky to backpatch, because it breaks any extensions accessing the field. The change that ri_RangeTableIndex is not set for partitions could potentially break extensions, too. The ResultRelInfos are visible to FDWs at least, and this patch required small changes to postgres_fdw. Nevertheless, this seem like the least bad option. I don't think these fields widely used in extensions; I don't think there are FDWs out there that uses the FDW "direct update" API, other than postgres_fdw. If there is, you will get a compilation error, so hopefully it is caught quickly. Backpatch to 11, where support for both cross-partition UPDATEs, and unique indexes on partitioned tables, were added. Reviewed-by: Amit Langote Security: CVE-2021-3393
5 years ago
NULL, 0, NULL);
return proute;
}
/*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* ExecFindPartition -- Return the ResultRelInfo for the leaf partition that
* the tuple contained in *slot should belong to.
*
* If the partition's ResultRelInfo does not yet exist in 'proute' then we set
* one up or reuse one from mtstate's resultRelInfo array. When reusing a
* ResultRelInfo from the mtstate we verify that the relation is a valid
* target for INSERTs and initialize tuple routing information.
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
*
* rootResultRelInfo is the relation named in the query.
*
* estate must be non-NULL; we'll need it to compute any expressions in the
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* partition keys. Also, its per-tuple contexts are used as evaluation
* scratch space.
*
* If no leaf partition is found, this routine errors out with the appropriate
* error message. An error may also be raised if the found target partition
* is not a valid target for an INSERT.
*/
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
ResultRelInfo *
ExecFindPartition(ModifyTableState *mtstate,
ResultRelInfo *rootResultRelInfo,
PartitionTupleRouting *proute,
TupleTableSlot *slot, EState *estate)
{
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
PartitionDispatch *pd = proute->partition_dispatch_info;
Datum values[PARTITION_MAX_KEYS];
bool isnull[PARTITION_MAX_KEYS];
Relation rel;
PartitionDispatch dispatch;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
PartitionDesc partdesc;
ExprContext *ecxt = GetPerTupleExprContext(estate);
TupleTableSlot *ecxt_scantuple_saved = ecxt->ecxt_scantuple;
TupleTableSlot *rootslot = slot;
TupleTableSlot *myslot = NULL;
MemoryContext oldcxt;
ResultRelInfo *rri = NULL;
/* use per-tuple context here to avoid leaking memory */
oldcxt = MemoryContextSwitchTo(GetPerTupleMemoryContext(estate));
/*
* First check the root table's partition constraint, if any. No point in
* routing the tuple if it doesn't belong in the root table itself.
*/
Don't fetch partition check expression during InitResultRelInfo. Since there is only one place that actually needs the partition check expression, namely ExecPartitionCheck, it's better to fetch it from the relcache there. In this way we will never fetch it at all if the query never has use for it, and we still fetch it just once when we do need it. The reason for taking an interest in this is that if the relcache doesn't already have the check expression cached, fetching it requires obtaining AccessShareLock on the partition root. That means that operations that look like they should only touch the partition itself will also take a lock on the root. In particular we observed that TRUNCATE on a partition may take a lock on the partition's root, contributing to a deadlock situation in parallel pg_restore. As written, this patch does have a small cost, which is that we are microscopically reducing efficiency for the case where a partition has an empty check expression. ExecPartitionCheck will be called, and will go through the motions of setting up and checking an empty qual, where before it would not have been called at all. We could avoid that by adding a separate boolean flag to track whether there is a partition expression to test. However, this case only arises for a default partition with no siblings, which surely is not an interesting case in practice. Hence adding complexity for it does not seem like a good trade-off. Amit Langote, per a suggestion by me Discussion: https://postgr.es/m/VI1PR03MB31670CA1BD9625C3A8C5DD05EB230@VI1PR03MB3167.eurprd03.prod.outlook.com
5 years ago
if (rootResultRelInfo->ri_RelationDesc->rd_rel->relispartition)
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
ExecPartitionCheck(rootResultRelInfo, slot, estate, true);
/* start with the root partitioned table */
dispatch = pd[0];
while (dispatch != NULL)
{
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
int partidx = -1;
bool is_leaf;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
CHECK_FOR_INTERRUPTS();
rel = dispatch->reldesc;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
partdesc = dispatch->partdesc;
/*
* Extract partition key from tuple. Expression evaluation machinery
* that FormPartitionKeyDatum() invokes expects ecxt_scantuple to
* point to the correct tuple slot. The slot might have changed from
* what was used for the parent table if the table of the current
* partitioning level has different tuple descriptor from the parent.
* So update ecxt_scantuple accordingly.
*/
ecxt->ecxt_scantuple = slot;
FormPartitionKeyDatum(dispatch, slot, estate, values, isnull);
/*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* If this partitioned table has no partitions or no partition for
* these values, error out.
*/
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
if (partdesc->nparts == 0 ||
(partidx = get_partition_for_tuple(dispatch, values, isnull)) < 0)
{
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
char *val_desc;
val_desc = ExecBuildSlotPartitionKeyDescription(rel,
values, isnull, 64);
Assert(OidIsValid(RelationGetRelid(rel)));
ereport(ERROR,
(errcode(ERRCODE_CHECK_VIOLATION),
errmsg("no partition of relation \"%s\" found for row",
RelationGetRelationName(rel)),
val_desc ?
errdetail("Partition key of the failing row contains %s.",
val_desc) : 0,
errtable(rel)));
}
is_leaf = partdesc->is_leaf[partidx];
if (is_leaf)
{
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/*
* We've reached the leaf -- hurray, we're done. Look to see if
* we've already got a ResultRelInfo for this partition.
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
*/
if (likely(dispatch->indexes[partidx] >= 0))
{
/* ResultRelInfo already built */
Assert(dispatch->indexes[partidx] < proute->num_partitions);
rri = proute->partitions[dispatch->indexes[partidx]];
}
else
{
/*
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
* If the partition is known in the owning ModifyTableState
* node, we can re-use that ResultRelInfo instead of creating
* a new one with ExecInitPartitionInfo().
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
*/
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
rri = ExecLookupResultRelByOid(mtstate,
partdesc->oids[partidx],
true, false);
if (rri)
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
{
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
/* Verify this ResultRelInfo allows INSERTs */
CheckValidResultRel(rri, CMD_INSERT);
/*
* Initialize information needed to insert this and
* subsequent tuples routed to this partition.
*/
ExecInitRoutingInfo(mtstate, estate, proute, dispatch,
rri, partidx, true);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
}
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
else
{
/* We need to create a new one. */
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
rri = ExecInitPartitionInfo(mtstate, estate, proute,
dispatch,
rootResultRelInfo, partidx);
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
}
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
}
Assert(rri != NULL);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/* Signal to terminate the loop */
dispatch = NULL;
}
else
{
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/*
* Partition is a sub-partitioned table; get the PartitionDispatch
*/
if (likely(dispatch->indexes[partidx] >= 0))
{
/* Already built. */
Assert(dispatch->indexes[partidx] < proute->num_dispatch);
rri = proute->nonleaf_partitions[dispatch->indexes[partidx]];
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/*
* Move down to the next partition level and search again
* until we find a leaf partition that matches this tuple
*/
dispatch = pd[dispatch->indexes[partidx]];
}
else
{
/* Not yet built. Do that now. */
PartitionDispatch subdispatch;
/*
* Create the new PartitionDispatch. We pass the current one
* in as the parent PartitionDispatch
*/
Fix permission checks on constraint violation errors on partitions. If a cross-partition UPDATE violates a constraint on the target partition, and the columns in the new partition are in different physical order than in the parent, the error message can reveal columns that the user does not have SELECT permission on. A similar bug was fixed earlier in commit 804b6b6db4. The cause of the bug is that the callers of the ExecBuildSlotValueDescription() function got confused when constructing the list of modified columns. If the tuple was routed from a parent, we converted the tuple to the parent's format, but the list of modified columns was grabbed directly from the child's RTE entry. ExecUpdateLockMode() had a similar issue. That lead to confusion on which columns are key columns, leading to wrong tuple lock being taken on tables referenced by foreign keys, when a row is updated with INSERT ON CONFLICT UPDATE. A new isolation test is added for that corner case. With this patch, the ri_RangeTableIndex field is no longer set for partitions that don't have an entry in the range table. Previously, it was set to the RTE entry of the parent relation, but that was confusing. NOTE: This modifies the ResultRelInfo struct, replacing the ri_PartitionRoot field with ri_RootResultRelInfo. That's a bit risky to backpatch, because it breaks any extensions accessing the field. The change that ri_RangeTableIndex is not set for partitions could potentially break extensions, too. The ResultRelInfos are visible to FDWs at least, and this patch required small changes to postgres_fdw. Nevertheless, this seem like the least bad option. I don't think these fields widely used in extensions; I don't think there are FDWs out there that uses the FDW "direct update" API, other than postgres_fdw. If there is, you will get a compilation error, so hopefully it is caught quickly. Backpatch to 11, where support for both cross-partition UPDATEs, and unique indexes on partitioned tables, were added. Reviewed-by: Amit Langote Security: CVE-2021-3393
5 years ago
subdispatch = ExecInitPartitionDispatchInfo(estate,
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
proute,
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
partdesc->oids[partidx],
Fix permission checks on constraint violation errors on partitions. If a cross-partition UPDATE violates a constraint on the target partition, and the columns in the new partition are in different physical order than in the parent, the error message can reveal columns that the user does not have SELECT permission on. A similar bug was fixed earlier in commit 804b6b6db4. The cause of the bug is that the callers of the ExecBuildSlotValueDescription() function got confused when constructing the list of modified columns. If the tuple was routed from a parent, we converted the tuple to the parent's format, but the list of modified columns was grabbed directly from the child's RTE entry. ExecUpdateLockMode() had a similar issue. That lead to confusion on which columns are key columns, leading to wrong tuple lock being taken on tables referenced by foreign keys, when a row is updated with INSERT ON CONFLICT UPDATE. A new isolation test is added for that corner case. With this patch, the ri_RangeTableIndex field is no longer set for partitions that don't have an entry in the range table. Previously, it was set to the RTE entry of the parent relation, but that was confusing. NOTE: This modifies the ResultRelInfo struct, replacing the ri_PartitionRoot field with ri_RootResultRelInfo. That's a bit risky to backpatch, because it breaks any extensions accessing the field. The change that ri_RangeTableIndex is not set for partitions could potentially break extensions, too. The ResultRelInfos are visible to FDWs at least, and this patch required small changes to postgres_fdw. Nevertheless, this seem like the least bad option. I don't think these fields widely used in extensions; I don't think there are FDWs out there that uses the FDW "direct update" API, other than postgres_fdw. If there is, you will get a compilation error, so hopefully it is caught quickly. Backpatch to 11, where support for both cross-partition UPDATEs, and unique indexes on partitioned tables, were added. Reviewed-by: Amit Langote Security: CVE-2021-3393
5 years ago
dispatch, partidx,
mtstate->rootResultRelInfo);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
Assert(dispatch->indexes[partidx] >= 0 &&
dispatch->indexes[partidx] < proute->num_dispatch);
rri = proute->nonleaf_partitions[dispatch->indexes[partidx]];
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
dispatch = subdispatch;
}
/*
* Convert the tuple to the new parent's layout, if different from
* the previous parent.
*/
if (dispatch->tupslot)
{
AttrMap *map = dispatch->tupmap;
TupleTableSlot *tempslot = myslot;
myslot = dispatch->tupslot;
slot = execute_attr_map_slot(map, slot, myslot);
if (tempslot != NULL)
ExecClearTuple(tempslot);
}
}
/*
* If this partition is the default one, we must check its partition
* constraint now, which may have changed concurrently due to
* partitions being added to the parent.
*
* (We do this here, and do not rely on ExecInsert doing it, because
* we don't want to miss doing it for non-leaf partitions.)
*/
if (partidx == partdesc->boundinfo->default_index)
{
/*
* The tuple must match the partition's layout for the constraint
* expression to be evaluated successfully. If the partition is
* sub-partitioned, that would already be the case due to the code
* above, but for a leaf partition the tuple still matches the
* parent's layout.
*
* Note that we have a map to convert from root to current
* partition, but not from immediate parent to current partition.
* So if we have to convert, do it from the root slot; if not, use
* the root slot as-is.
*/
if (is_leaf)
{
TupleConversionMap *map = rri->ri_RootToPartitionMap;
if (map)
slot = execute_attr_map_slot(map->attrMap, rootslot,
rri->ri_PartitionTupleSlot);
else
slot = rootslot;
}
ExecPartitionCheck(rri, slot, estate, true);
}
}
/* Release the tuple in the lowest parent's dedicated slot. */
if (myslot != NULL)
ExecClearTuple(myslot);
/* and restore ecxt's scantuple */
ecxt->ecxt_scantuple = ecxt_scantuple_saved;
MemoryContextSwitchTo(oldcxt);
return rri;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
}
/*
* ExecInitPartitionInfo
* Lock the partition and initialize ResultRelInfo. Also setup other
* information for the partition and store it in the next empty slot in
* the proute->partitions array.
*
* Returns the ResultRelInfo
*/
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
static ResultRelInfo *
ExecInitPartitionInfo(ModifyTableState *mtstate, EState *estate,
PartitionTupleRouting *proute,
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
PartitionDispatch dispatch,
ResultRelInfo *rootResultRelInfo,
int partidx)
{
ModifyTable *node = (ModifyTable *) mtstate->ps.plan;
ALTER TABLE ... DETACH PARTITION ... CONCURRENTLY Allow a partition be detached from its partitioned table without blocking concurrent queries, by running in two transactions and only requiring ShareUpdateExclusive in the partitioned table. Because it runs in two transactions, it cannot be used in a transaction block. This is the main reason to use dedicated syntax: so that users can choose to use the original mode if they need it. But also, it doesn't work when a default partition exists (because an exclusive lock would still need to be obtained on it, in order to change its partition constraint.) In case the second transaction is cancelled or a crash occurs, there's ALTER TABLE .. DETACH PARTITION .. FINALIZE, which executes the final steps. The main trick to make this work is the addition of column pg_inherits.inhdetachpending, initially false; can only be set true in the first part of this command. Once that is committed, concurrent transactions that use a PartitionDirectory will include or ignore partitions so marked: in optimizer they are ignored if the row is marked committed for the snapshot; in executor they are always included. As a result, and because of the way PartitionDirectory caches partition descriptors, queries that were planned before the detach will see the rows in the detached partition and queries that are planned after the detach, won't. A CHECK constraint is created that duplicates the partition constraint. This is probably not strictly necessary, and some users will prefer to remove it afterwards, but if the partition is re-attached to a partitioned table, the constraint needn't be rechecked. Author: Álvaro Herrera <alvherre@alvh.no-ip.org> Reviewed-by: Amit Langote <amitlangote09@gmail.com> Reviewed-by: Justin Pryzby <pryzby@telsasoft.com> Discussion: https://postgr.es/m/20200803234854.GA24158@alvherre.pgsql
5 years ago
Oid partOid = dispatch->partdesc->oids[partidx];
Fix permission checks on constraint violation errors on partitions. If a cross-partition UPDATE violates a constraint on the target partition, and the columns in the new partition are in different physical order than in the parent, the error message can reveal columns that the user does not have SELECT permission on. A similar bug was fixed earlier in commit 804b6b6db4. The cause of the bug is that the callers of the ExecBuildSlotValueDescription() function got confused when constructing the list of modified columns. If the tuple was routed from a parent, we converted the tuple to the parent's format, but the list of modified columns was grabbed directly from the child's RTE entry. ExecUpdateLockMode() had a similar issue. That lead to confusion on which columns are key columns, leading to wrong tuple lock being taken on tables referenced by foreign keys, when a row is updated with INSERT ON CONFLICT UPDATE. A new isolation test is added for that corner case. With this patch, the ri_RangeTableIndex field is no longer set for partitions that don't have an entry in the range table. Previously, it was set to the RTE entry of the parent relation, but that was confusing. NOTE: This modifies the ResultRelInfo struct, replacing the ri_PartitionRoot field with ri_RootResultRelInfo. That's a bit risky to backpatch, because it breaks any extensions accessing the field. The change that ri_RangeTableIndex is not set for partitions could potentially break extensions, too. The ResultRelInfos are visible to FDWs at least, and this patch required small changes to postgres_fdw. Nevertheless, this seem like the least bad option. I don't think these fields widely used in extensions; I don't think there are FDWs out there that uses the FDW "direct update" API, other than postgres_fdw. If there is, you will get a compilation error, so hopefully it is caught quickly. Backpatch to 11, where support for both cross-partition UPDATEs, and unique indexes on partitioned tables, were added. Reviewed-by: Amit Langote Security: CVE-2021-3393
5 years ago
Relation partrel;
int firstVarno = mtstate->resultRelInfo[0].ri_RangeTableIndex;
Relation firstResultRel = mtstate->resultRelInfo[0].ri_RelationDesc;
ResultRelInfo *leaf_part_rri;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
MemoryContext oldcxt;
AttrMap *part_attmap = NULL;
bool found_whole_row;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
oldcxt = MemoryContextSwitchTo(proute->memcxt);
ALTER TABLE ... DETACH PARTITION ... CONCURRENTLY Allow a partition be detached from its partitioned table without blocking concurrent queries, by running in two transactions and only requiring ShareUpdateExclusive in the partitioned table. Because it runs in two transactions, it cannot be used in a transaction block. This is the main reason to use dedicated syntax: so that users can choose to use the original mode if they need it. But also, it doesn't work when a default partition exists (because an exclusive lock would still need to be obtained on it, in order to change its partition constraint.) In case the second transaction is cancelled or a crash occurs, there's ALTER TABLE .. DETACH PARTITION .. FINALIZE, which executes the final steps. The main trick to make this work is the addition of column pg_inherits.inhdetachpending, initially false; can only be set true in the first part of this command. Once that is committed, concurrent transactions that use a PartitionDirectory will include or ignore partitions so marked: in optimizer they are ignored if the row is marked committed for the snapshot; in executor they are always included. As a result, and because of the way PartitionDirectory caches partition descriptors, queries that were planned before the detach will see the rows in the detached partition and queries that are planned after the detach, won't. A CHECK constraint is created that duplicates the partition constraint. This is probably not strictly necessary, and some users will prefer to remove it afterwards, but if the partition is re-attached to a partitioned table, the constraint needn't be rechecked. Author: Álvaro Herrera <alvherre@alvh.no-ip.org> Reviewed-by: Amit Langote <amitlangote09@gmail.com> Reviewed-by: Justin Pryzby <pryzby@telsasoft.com> Discussion: https://postgr.es/m/20200803234854.GA24158@alvherre.pgsql
5 years ago
partrel = table_open(partOid, RowExclusiveLock);
leaf_part_rri = makeNode(ResultRelInfo);
InitResultRelInfo(leaf_part_rri,
partrel,
Fix permission checks on constraint violation errors on partitions. If a cross-partition UPDATE violates a constraint on the target partition, and the columns in the new partition are in different physical order than in the parent, the error message can reveal columns that the user does not have SELECT permission on. A similar bug was fixed earlier in commit 804b6b6db4. The cause of the bug is that the callers of the ExecBuildSlotValueDescription() function got confused when constructing the list of modified columns. If the tuple was routed from a parent, we converted the tuple to the parent's format, but the list of modified columns was grabbed directly from the child's RTE entry. ExecUpdateLockMode() had a similar issue. That lead to confusion on which columns are key columns, leading to wrong tuple lock being taken on tables referenced by foreign keys, when a row is updated with INSERT ON CONFLICT UPDATE. A new isolation test is added for that corner case. With this patch, the ri_RangeTableIndex field is no longer set for partitions that don't have an entry in the range table. Previously, it was set to the RTE entry of the parent relation, but that was confusing. NOTE: This modifies the ResultRelInfo struct, replacing the ri_PartitionRoot field with ri_RootResultRelInfo. That's a bit risky to backpatch, because it breaks any extensions accessing the field. The change that ri_RangeTableIndex is not set for partitions could potentially break extensions, too. The ResultRelInfos are visible to FDWs at least, and this patch required small changes to postgres_fdw. Nevertheless, this seem like the least bad option. I don't think these fields widely used in extensions; I don't think there are FDWs out there that uses the FDW "direct update" API, other than postgres_fdw. If there is, you will get a compilation error, so hopefully it is caught quickly. Backpatch to 11, where support for both cross-partition UPDATEs, and unique indexes on partitioned tables, were added. Reviewed-by: Amit Langote Security: CVE-2021-3393
5 years ago
0,
rootResultRelInfo,
estate->es_instrument);
/*
* Verify result relation is a valid target for an INSERT. An UPDATE of a
* partition-key becomes a DELETE+INSERT operation, so this check is still
* required when the operation is CMD_UPDATE.
*/
CheckValidResultRel(leaf_part_rri, CMD_INSERT);
/*
* Open partition indices. The user may have asked to check for conflicts
* within this leaf partition and do "nothing" instead of throwing an
* error. Be prepared in that case by initializing the index information
* needed by ExecInsert() to perform speculative insertions.
*/
if (partrel->rd_rel->relhasindex &&
leaf_part_rri->ri_IndexRelationDescs == NULL)
ExecOpenIndices(leaf_part_rri,
(node != NULL &&
node->onConflictAction != ONCONFLICT_NONE));
/*
* Build WITH CHECK OPTION constraints for the partition. Note that we
* didn't build the withCheckOptionList for partitions within the planner,
* but simple translation of varattnos will suffice. This only occurs for
* the INSERT case or in the case of UPDATE tuple routing where we didn't
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
* find a result rel to reuse.
*/
if (node && node->withCheckOptionLists != NIL)
{
List *wcoList;
List *wcoExprs = NIL;
ListCell *ll;
/*
* In the case of INSERT on a partitioned table, there is only one
* plan. Likewise, there is only one WCO list, not one per partition.
* For UPDATE, there are as many WCO lists as there are plans.
*/
Assert((node->operation == CMD_INSERT &&
list_length(node->withCheckOptionLists) == 1 &&
Rework planning and execution of UPDATE and DELETE. This patch makes two closely related sets of changes: 1. For UPDATE, the subplan of the ModifyTable node now only delivers the new values of the changed columns (i.e., the expressions computed in the query's SET clause) plus row identity information such as CTID. ModifyTable must re-fetch the original tuple to merge in the old values of any unchanged columns. The core advantage of this is that the changed columns are uniform across all tables of an inherited or partitioned target relation, whereas the other columns might not be. A secondary advantage, when the UPDATE involves joins, is that less data needs to pass through the plan tree. The disadvantage of course is an extra fetch of each tuple to be updated. However, that seems to be very nearly free in context; even worst-case tests don't show it to add more than a couple percent to the total query cost. At some point it might be interesting to combine the re-fetch with the tuple access that ModifyTable must do anyway to mark the old tuple dead; but that would require a good deal of refactoring and it seems it wouldn't buy all that much, so this patch doesn't attempt it. 2. For inherited UPDATE/DELETE, instead of generating a separate subplan for each target relation, we now generate a single subplan that is just exactly like a SELECT's plan, then stick ModifyTable on top of that. To let ModifyTable know which target relation a given incoming row refers to, a tableoid junk column is added to the row identity information. This gets rid of the horrid hack that was inheritance_planner(), eliminating O(N^2) planning cost and memory consumption in cases where there were many unprunable target relations. Point 2 of course requires point 1, so that there is a uniform definition of the non-junk columns to be returned by the subplan. We can't insist on uniform definition of the row identity junk columns however, if we want to keep the ability to have both plain and foreign tables in a partitioning hierarchy. Since it wouldn't scale very far to have every child table have its own row identity column, this patch includes provisions to merge similar row identity columns into one column of the subplan result. In particular, we can merge the whole-row Vars typically used as row identity by FDWs into one column by pretending they are type RECORD. (It's still okay for the actual composite Datums to be labeled with the table's rowtype OID, though.) There is more that can be done to file down residual inefficiencies in this patch, but it seems to be committable now. FDW authors should note several API changes: * The argument list for AddForeignUpdateTargets() has changed, and so has the method it must use for adding junk columns to the query. Call add_row_identity_var() instead of manipulating the parse tree directly. You might want to reconsider exactly what you're adding, too. * PlanDirectModify() must now work a little harder to find the ForeignScan plan node; if the foreign table is part of a partitioning hierarchy then the ForeignScan might not be the direct child of ModifyTable. See postgres_fdw for sample code. * To check whether a relation is a target relation, it's no longer sufficient to compare its relid to root->parse->resultRelation. Instead, check it against all_result_relids or leaf_result_relids, as appropriate. Amit Langote and Tom Lane Discussion: https://postgr.es/m/CA+HiwqHpHdqdDn48yCEhynnniahH78rwcrv1rEX65-fsZGBOLQ@mail.gmail.com
5 years ago
list_length(node->resultRelations) == 1) ||
(node->operation == CMD_UPDATE &&
list_length(node->withCheckOptionLists) ==
Rework planning and execution of UPDATE and DELETE. This patch makes two closely related sets of changes: 1. For UPDATE, the subplan of the ModifyTable node now only delivers the new values of the changed columns (i.e., the expressions computed in the query's SET clause) plus row identity information such as CTID. ModifyTable must re-fetch the original tuple to merge in the old values of any unchanged columns. The core advantage of this is that the changed columns are uniform across all tables of an inherited or partitioned target relation, whereas the other columns might not be. A secondary advantage, when the UPDATE involves joins, is that less data needs to pass through the plan tree. The disadvantage of course is an extra fetch of each tuple to be updated. However, that seems to be very nearly free in context; even worst-case tests don't show it to add more than a couple percent to the total query cost. At some point it might be interesting to combine the re-fetch with the tuple access that ModifyTable must do anyway to mark the old tuple dead; but that would require a good deal of refactoring and it seems it wouldn't buy all that much, so this patch doesn't attempt it. 2. For inherited UPDATE/DELETE, instead of generating a separate subplan for each target relation, we now generate a single subplan that is just exactly like a SELECT's plan, then stick ModifyTable on top of that. To let ModifyTable know which target relation a given incoming row refers to, a tableoid junk column is added to the row identity information. This gets rid of the horrid hack that was inheritance_planner(), eliminating O(N^2) planning cost and memory consumption in cases where there were many unprunable target relations. Point 2 of course requires point 1, so that there is a uniform definition of the non-junk columns to be returned by the subplan. We can't insist on uniform definition of the row identity junk columns however, if we want to keep the ability to have both plain and foreign tables in a partitioning hierarchy. Since it wouldn't scale very far to have every child table have its own row identity column, this patch includes provisions to merge similar row identity columns into one column of the subplan result. In particular, we can merge the whole-row Vars typically used as row identity by FDWs into one column by pretending they are type RECORD. (It's still okay for the actual composite Datums to be labeled with the table's rowtype OID, though.) There is more that can be done to file down residual inefficiencies in this patch, but it seems to be committable now. FDW authors should note several API changes: * The argument list for AddForeignUpdateTargets() has changed, and so has the method it must use for adding junk columns to the query. Call add_row_identity_var() instead of manipulating the parse tree directly. You might want to reconsider exactly what you're adding, too. * PlanDirectModify() must now work a little harder to find the ForeignScan plan node; if the foreign table is part of a partitioning hierarchy then the ForeignScan might not be the direct child of ModifyTable. See postgres_fdw for sample code. * To check whether a relation is a target relation, it's no longer sufficient to compare its relid to root->parse->resultRelation. Instead, check it against all_result_relids or leaf_result_relids, as appropriate. Amit Langote and Tom Lane Discussion: https://postgr.es/m/CA+HiwqHpHdqdDn48yCEhynnniahH78rwcrv1rEX65-fsZGBOLQ@mail.gmail.com
5 years ago
list_length(node->resultRelations)));
/*
* Use the WCO list of the first plan as a reference to calculate
* attno's for the WCO list of this partition. In the INSERT case,
* that refers to the root partitioned table, whereas in the UPDATE
* tuple routing case, that refers to the first partition in the
* mtstate->resultRelInfo array. In any case, both that relation and
* this partition should have the same columns, so we should be able
* to map attributes successfully.
*/
wcoList = linitial(node->withCheckOptionLists);
/*
* Convert Vars in it to contain this partition's attribute numbers.
*/
part_attmap =
build_attrmap_by_name(RelationGetDescr(partrel),
RelationGetDescr(firstResultRel));
wcoList = (List *)
map_variable_attnos((Node *) wcoList,
firstVarno, 0,
part_attmap,
RelationGetForm(partrel)->reltype,
&found_whole_row);
/* We ignore the value of found_whole_row. */
foreach(ll, wcoList)
{
WithCheckOption *wco = castNode(WithCheckOption, lfirst(ll));
ExprState *wcoExpr = ExecInitQual(castNode(List, wco->qual),
&mtstate->ps);
wcoExprs = lappend(wcoExprs, wcoExpr);
}
leaf_part_rri->ri_WithCheckOptions = wcoList;
leaf_part_rri->ri_WithCheckOptionExprs = wcoExprs;
}
/*
* Build the RETURNING projection for the partition. Note that we didn't
* build the returningList for partitions within the planner, but simple
* translation of varattnos will suffice. This only occurs for the INSERT
* case or in the case of UPDATE tuple routing where we didn't find a
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
* result rel to reuse.
*/
if (node && node->returningLists != NIL)
{
TupleTableSlot *slot;
ExprContext *econtext;
List *returningList;
/* See the comment above for WCO lists. */
Assert((node->operation == CMD_INSERT &&
list_length(node->returningLists) == 1 &&
Rework planning and execution of UPDATE and DELETE. This patch makes two closely related sets of changes: 1. For UPDATE, the subplan of the ModifyTable node now only delivers the new values of the changed columns (i.e., the expressions computed in the query's SET clause) plus row identity information such as CTID. ModifyTable must re-fetch the original tuple to merge in the old values of any unchanged columns. The core advantage of this is that the changed columns are uniform across all tables of an inherited or partitioned target relation, whereas the other columns might not be. A secondary advantage, when the UPDATE involves joins, is that less data needs to pass through the plan tree. The disadvantage of course is an extra fetch of each tuple to be updated. However, that seems to be very nearly free in context; even worst-case tests don't show it to add more than a couple percent to the total query cost. At some point it might be interesting to combine the re-fetch with the tuple access that ModifyTable must do anyway to mark the old tuple dead; but that would require a good deal of refactoring and it seems it wouldn't buy all that much, so this patch doesn't attempt it. 2. For inherited UPDATE/DELETE, instead of generating a separate subplan for each target relation, we now generate a single subplan that is just exactly like a SELECT's plan, then stick ModifyTable on top of that. To let ModifyTable know which target relation a given incoming row refers to, a tableoid junk column is added to the row identity information. This gets rid of the horrid hack that was inheritance_planner(), eliminating O(N^2) planning cost and memory consumption in cases where there were many unprunable target relations. Point 2 of course requires point 1, so that there is a uniform definition of the non-junk columns to be returned by the subplan. We can't insist on uniform definition of the row identity junk columns however, if we want to keep the ability to have both plain and foreign tables in a partitioning hierarchy. Since it wouldn't scale very far to have every child table have its own row identity column, this patch includes provisions to merge similar row identity columns into one column of the subplan result. In particular, we can merge the whole-row Vars typically used as row identity by FDWs into one column by pretending they are type RECORD. (It's still okay for the actual composite Datums to be labeled with the table's rowtype OID, though.) There is more that can be done to file down residual inefficiencies in this patch, but it seems to be committable now. FDW authors should note several API changes: * The argument list for AddForeignUpdateTargets() has changed, and so has the method it must use for adding junk columns to the query. Call add_row_identity_var() instead of manipulating the parse tree directly. You might want to reconsider exactly what you're adding, too. * PlanDirectModify() must now work a little harder to find the ForeignScan plan node; if the foreign table is part of a partitioning hierarchy then the ForeignScan might not be the direct child of ModifyTable. See postgres_fdw for sample code. * To check whether a relation is a target relation, it's no longer sufficient to compare its relid to root->parse->resultRelation. Instead, check it against all_result_relids or leaf_result_relids, as appropriate. Amit Langote and Tom Lane Discussion: https://postgr.es/m/CA+HiwqHpHdqdDn48yCEhynnniahH78rwcrv1rEX65-fsZGBOLQ@mail.gmail.com
5 years ago
list_length(node->resultRelations) == 1) ||
(node->operation == CMD_UPDATE &&
list_length(node->returningLists) ==
Rework planning and execution of UPDATE and DELETE. This patch makes two closely related sets of changes: 1. For UPDATE, the subplan of the ModifyTable node now only delivers the new values of the changed columns (i.e., the expressions computed in the query's SET clause) plus row identity information such as CTID. ModifyTable must re-fetch the original tuple to merge in the old values of any unchanged columns. The core advantage of this is that the changed columns are uniform across all tables of an inherited or partitioned target relation, whereas the other columns might not be. A secondary advantage, when the UPDATE involves joins, is that less data needs to pass through the plan tree. The disadvantage of course is an extra fetch of each tuple to be updated. However, that seems to be very nearly free in context; even worst-case tests don't show it to add more than a couple percent to the total query cost. At some point it might be interesting to combine the re-fetch with the tuple access that ModifyTable must do anyway to mark the old tuple dead; but that would require a good deal of refactoring and it seems it wouldn't buy all that much, so this patch doesn't attempt it. 2. For inherited UPDATE/DELETE, instead of generating a separate subplan for each target relation, we now generate a single subplan that is just exactly like a SELECT's plan, then stick ModifyTable on top of that. To let ModifyTable know which target relation a given incoming row refers to, a tableoid junk column is added to the row identity information. This gets rid of the horrid hack that was inheritance_planner(), eliminating O(N^2) planning cost and memory consumption in cases where there were many unprunable target relations. Point 2 of course requires point 1, so that there is a uniform definition of the non-junk columns to be returned by the subplan. We can't insist on uniform definition of the row identity junk columns however, if we want to keep the ability to have both plain and foreign tables in a partitioning hierarchy. Since it wouldn't scale very far to have every child table have its own row identity column, this patch includes provisions to merge similar row identity columns into one column of the subplan result. In particular, we can merge the whole-row Vars typically used as row identity by FDWs into one column by pretending they are type RECORD. (It's still okay for the actual composite Datums to be labeled with the table's rowtype OID, though.) There is more that can be done to file down residual inefficiencies in this patch, but it seems to be committable now. FDW authors should note several API changes: * The argument list for AddForeignUpdateTargets() has changed, and so has the method it must use for adding junk columns to the query. Call add_row_identity_var() instead of manipulating the parse tree directly. You might want to reconsider exactly what you're adding, too. * PlanDirectModify() must now work a little harder to find the ForeignScan plan node; if the foreign table is part of a partitioning hierarchy then the ForeignScan might not be the direct child of ModifyTable. See postgres_fdw for sample code. * To check whether a relation is a target relation, it's no longer sufficient to compare its relid to root->parse->resultRelation. Instead, check it against all_result_relids or leaf_result_relids, as appropriate. Amit Langote and Tom Lane Discussion: https://postgr.es/m/CA+HiwqHpHdqdDn48yCEhynnniahH78rwcrv1rEX65-fsZGBOLQ@mail.gmail.com
5 years ago
list_length(node->resultRelations)));
/*
* Use the RETURNING list of the first plan as a reference to
* calculate attno's for the RETURNING list of this partition. See
* the comment above for WCO lists for more details on why this is
* okay.
*/
returningList = linitial(node->returningLists);
/*
* Convert Vars in it to contain this partition's attribute numbers.
*/
if (part_attmap == NULL)
part_attmap =
build_attrmap_by_name(RelationGetDescr(partrel),
RelationGetDescr(firstResultRel));
returningList = (List *)
map_variable_attnos((Node *) returningList,
firstVarno, 0,
part_attmap,
RelationGetForm(partrel)->reltype,
&found_whole_row);
/* We ignore the value of found_whole_row. */
leaf_part_rri->ri_returningList = returningList;
/*
* Initialize the projection itself.
*
* Use the slot and the expression context that would have been set up
* in ExecInitModifyTable() for projection's output.
*/
Assert(mtstate->ps.ps_ResultTupleSlot != NULL);
slot = mtstate->ps.ps_ResultTupleSlot;
Assert(mtstate->ps.ps_ExprContext != NULL);
econtext = mtstate->ps.ps_ExprContext;
leaf_part_rri->ri_projectReturning =
ExecBuildProjectionInfo(returningList, econtext, slot,
&mtstate->ps, RelationGetDescr(partrel));
}
/* Set up information needed for routing tuples to the partition. */
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
ExecInitRoutingInfo(mtstate, estate, proute, dispatch,
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
leaf_part_rri, partidx, false);
/*
* If there is an ON CONFLICT clause, initialize state for it.
*/
if (node && node->onConflictAction != ONCONFLICT_NONE)
{
TupleDesc partrelDesc = RelationGetDescr(partrel);
ExprContext *econtext = mtstate->ps.ps_ExprContext;
ListCell *lc;
List *arbiterIndexes = NIL;
/*
* If there is a list of arbiter indexes, map it to a list of indexes
* in the partition. We do that by scanning the partition's index
* list and searching for ancestry relationships to each index in the
* ancestor table.
*/
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
if (list_length(rootResultRelInfo->ri_onConflictArbiterIndexes) > 0)
{
List *childIdxs;
childIdxs = RelationGetIndexList(leaf_part_rri->ri_RelationDesc);
foreach(lc, childIdxs)
{
Oid childIdx = lfirst_oid(lc);
List *ancestors;
ListCell *lc2;
ancestors = get_partition_ancestors(childIdx);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
foreach(lc2, rootResultRelInfo->ri_onConflictArbiterIndexes)
{
if (list_member_oid(ancestors, lfirst_oid(lc2)))
arbiterIndexes = lappend_oid(arbiterIndexes, childIdx);
}
list_free(ancestors);
}
}
/*
* If the resulting lists are of inequal length, something is wrong.
* (This shouldn't happen, since arbiter index selection should not
* pick up an invalid index.)
*/
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
if (list_length(rootResultRelInfo->ri_onConflictArbiterIndexes) !=
list_length(arbiterIndexes))
elog(ERROR, "invalid arbiter index list");
leaf_part_rri->ri_onConflictArbiterIndexes = arbiterIndexes;
/*
* In the DO UPDATE case, we have some more state to initialize.
*/
if (node->onConflictAction == ONCONFLICT_UPDATE)
{
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
OnConflictSetState *onconfl = makeNode(OnConflictSetState);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
TupleConversionMap *map;
map = leaf_part_rri->ri_RootToPartitionMap;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
Assert(node->onConflictSet != NIL);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
Assert(rootResultRelInfo->ri_onConflict != NULL);
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
leaf_part_rri->ri_onConflict = onconfl;
/*
* Need a separate existing slot for each partition, as the
* partition could be of a different AM, even if the tuple
* descriptors match.
*/
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
onconfl->oc_Existing =
tableam: Add and use scan APIs. Too allow table accesses to be not directly dependent on heap, several new abstractions are needed. Specifically: 1) Heap scans need to be generalized into table scans. Do this by introducing TableScanDesc, which will be the "base class" for individual AMs. This contains the AM independent fields from HeapScanDesc. The previous heap_{beginscan,rescan,endscan} et al. have been replaced with a table_ version. There's no direct replacement for heap_getnext(), as that returned a HeapTuple, which is undesirable for a other AMs. Instead there's table_scan_getnextslot(). But note that heap_getnext() lives on, it's still used widely to access catalog tables. This is achieved by new scan_begin, scan_end, scan_rescan, scan_getnextslot callbacks. 2) The portion of parallel scans that's shared between backends need to be able to do so without the user doing per-AM work. To achieve that new parallelscan_{estimate, initialize, reinitialize} callbacks are introduced, which operate on a new ParallelTableScanDesc, which again can be subclassed by AMs. As it is likely that several AMs are going to be block oriented, block oriented callbacks that can be shared between such AMs are provided and used by heap. table_block_parallelscan_{estimate, intiialize, reinitialize} as callbacks, and table_block_parallelscan_{nextpage, init} for use in AMs. These operate on a ParallelBlockTableScanDesc. 3) Index scans need to be able to access tables to return a tuple, and there needs to be state across individual accesses to the heap to store state like buffers. That's now handled by introducing a sort-of-scan IndexFetchTable, which again is intended to be subclassed by individual AMs (for heap IndexFetchHeap). The relevant callbacks for an AM are index_fetch_{end, begin, reset} to create the necessary state, and index_fetch_tuple to retrieve an indexed tuple. Note that index_fetch_tuple implementations need to be smarter than just blindly fetching the tuples for AMs that have optimizations similar to heap's HOT - the currently alive tuple in the update chain needs to be fetched if appropriate. Similar to table_scan_getnextslot(), it's undesirable to continue to return HeapTuples. Thus index_fetch_heap (might want to rename that later) now accepts a slot as an argument. Core code doesn't have a lot of call sites performing index scans without going through the systable_* API (in contrast to loads of heap_getnext calls and working directly with HeapTuples). Index scans now store the result of a search in IndexScanDesc->xs_heaptid, rather than xs_ctup->t_self. As the target is not generally a HeapTuple anymore that seems cleaner. To be able to sensible adapt code to use the above, two further callbacks have been introduced: a) slot_callbacks returns a TupleTableSlotOps* suitable for creating slots capable of holding a tuple of the AMs type. table_slot_callbacks() and table_slot_create() are based upon that, but have additional logic to deal with views, foreign tables, etc. While this change could have been done separately, nearly all the call sites that needed to be adapted for the rest of this commit also would have been needed to be adapted for table_slot_callbacks(), making separation not worthwhile. b) tuple_satisfies_snapshot checks whether the tuple in a slot is currently visible according to a snapshot. That's required as a few places now don't have a buffer + HeapTuple around, but a slot (which in heap's case internally has that information). Additionally a few infrastructure changes were needed: I) SysScanDesc, as used by systable_{beginscan, getnext} et al. now internally uses a slot to keep track of tuples. While systable_getnext() still returns HeapTuples, and will so for the foreseeable future, the index API (see 1) above) now only deals with slots. The remainder, and largest part, of this commit is then adjusting all scans in postgres to use the new APIs. Author: Andres Freund, Haribabu Kommi, Alvaro Herrera Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de https://postgr.es/m/20160812231527.GA690404@alvherre.pgsql
7 years ago
table_slot_create(leaf_part_rri->ri_RelationDesc,
&mtstate->ps.state->es_tupleTable);
/*
* If the partition's tuple descriptor matches exactly the root
* parent (the common case), we can re-use most of the parent's ON
* CONFLICT SET state, skipping a bunch of work. Otherwise, we
* need to create state specific to this partition.
*/
if (map == NULL)
{
/*
* It's safe to reuse these from the partition root, as we
* only process one tuple at a time (therefore we won't
* overwrite needed data in slots), and the results of
* projections are independent of the underlying storage.
* Projections and where clauses themselves don't store state
* / are independent of the underlying storage.
*/
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
onconfl->oc_ProjSlot =
rootResultRelInfo->ri_onConflict->oc_ProjSlot;
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
onconfl->oc_ProjInfo =
rootResultRelInfo->ri_onConflict->oc_ProjInfo;
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
onconfl->oc_WhereClause =
rootResultRelInfo->ri_onConflict->oc_WhereClause;
}
else
{
List *onconflset;
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
List *onconflcols;
bool found_whole_row;
/*
* Translate expressions in onConflictSet to account for
* different attribute numbers. For that, map partition
* varattnos twice: first to catch the EXCLUDED
* pseudo-relation (INNER_VAR), and second to handle the main
* target relation (firstVarno).
*/
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
onconflset = copyObject(node->onConflictSet);
if (part_attmap == NULL)
part_attmap =
build_attrmap_by_name(RelationGetDescr(partrel),
RelationGetDescr(firstResultRel));
onconflset = (List *)
map_variable_attnos((Node *) onconflset,
INNER_VAR, 0,
part_attmap,
RelationGetForm(partrel)->reltype,
&found_whole_row);
/* We ignore the value of found_whole_row. */
onconflset = (List *)
map_variable_attnos((Node *) onconflset,
firstVarno, 0,
part_attmap,
RelationGetForm(partrel)->reltype,
&found_whole_row);
/* We ignore the value of found_whole_row. */
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
/* Finally, adjust the target colnos to match the partition. */
onconflcols = adjust_partition_colnos(node->onConflictCols,
leaf_part_rri);
/* create the tuple slot for the UPDATE SET projection */
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
onconfl->oc_ProjSlot =
table_slot_create(partrel,
&mtstate->ps.state->es_tupleTable);
/* build UPDATE SET projection state */
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
onconfl->oc_ProjInfo =
ExecBuildUpdateProjection(onconflset,
true,
onconflcols,
partrelDesc,
econtext,
onconfl->oc_ProjSlot,
&mtstate->ps);
/*
* If there is a WHERE clause, initialize state where it will
* be evaluated, mapping the attribute numbers appropriately.
* As with onConflictSet, we need to map partition varattnos
* to the partition's tupdesc.
*/
if (node->onConflictWhere)
{
List *clause;
clause = copyObject((List *) node->onConflictWhere);
clause = (List *)
map_variable_attnos((Node *) clause,
INNER_VAR, 0,
part_attmap,
RelationGetForm(partrel)->reltype,
&found_whole_row);
/* We ignore the value of found_whole_row. */
clause = (List *)
map_variable_attnos((Node *) clause,
firstVarno, 0,
part_attmap,
RelationGetForm(partrel)->reltype,
&found_whole_row);
/* We ignore the value of found_whole_row. */
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
onconfl->oc_WhereClause =
ExecInitQual((List *) clause, &mtstate->ps);
}
}
}
}
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/*
* Since we've just initialized this ResultRelInfo, it's not in any list
* attached to the estate as yet. Add it, so that it can be found later.
*
* Note that the entries in this list appear in no predetermined order,
* because partition result rels are initialized as and when they're
* needed.
*/
MemoryContextSwitchTo(estate->es_query_cxt);
estate->es_tuple_routing_result_relations =
lappend(estate->es_tuple_routing_result_relations,
leaf_part_rri);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
MemoryContextSwitchTo(oldcxt);
return leaf_part_rri;
}
/*
* ExecInitRoutingInfo
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* Set up information needed for translating tuples between root
* partitioned table format and partition format, and keep track of it
* in PartitionTupleRouting.
*/
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
static void
ExecInitRoutingInfo(ModifyTableState *mtstate,
EState *estate,
PartitionTupleRouting *proute,
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
PartitionDispatch dispatch,
ResultRelInfo *partRelInfo,
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
int partidx,
bool is_borrowed_rel)
{
Fix permission checks on constraint violation errors on partitions. If a cross-partition UPDATE violates a constraint on the target partition, and the columns in the new partition are in different physical order than in the parent, the error message can reveal columns that the user does not have SELECT permission on. A similar bug was fixed earlier in commit 804b6b6db4. The cause of the bug is that the callers of the ExecBuildSlotValueDescription() function got confused when constructing the list of modified columns. If the tuple was routed from a parent, we converted the tuple to the parent's format, but the list of modified columns was grabbed directly from the child's RTE entry. ExecUpdateLockMode() had a similar issue. That lead to confusion on which columns are key columns, leading to wrong tuple lock being taken on tables referenced by foreign keys, when a row is updated with INSERT ON CONFLICT UPDATE. A new isolation test is added for that corner case. With this patch, the ri_RangeTableIndex field is no longer set for partitions that don't have an entry in the range table. Previously, it was set to the RTE entry of the parent relation, but that was confusing. NOTE: This modifies the ResultRelInfo struct, replacing the ri_PartitionRoot field with ri_RootResultRelInfo. That's a bit risky to backpatch, because it breaks any extensions accessing the field. The change that ri_RangeTableIndex is not set for partitions could potentially break extensions, too. The ResultRelInfos are visible to FDWs at least, and this patch required small changes to postgres_fdw. Nevertheless, this seem like the least bad option. I don't think these fields widely used in extensions; I don't think there are FDWs out there that uses the FDW "direct update" API, other than postgres_fdw. If there is, you will get a compilation error, so hopefully it is caught quickly. Backpatch to 11, where support for both cross-partition UPDATEs, and unique indexes on partitioned tables, were added. Reviewed-by: Amit Langote Security: CVE-2021-3393
5 years ago
ResultRelInfo *rootRelInfo = partRelInfo->ri_RootResultRelInfo;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
MemoryContext oldcxt;
int rri_index;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
oldcxt = MemoryContextSwitchTo(proute->memcxt);
/*
* Set up a tuple conversion map to convert a tuple routed to the
* partition from the parent's type to the partition's.
*/
partRelInfo->ri_RootToPartitionMap =
Fix permission checks on constraint violation errors on partitions. If a cross-partition UPDATE violates a constraint on the target partition, and the columns in the new partition are in different physical order than in the parent, the error message can reveal columns that the user does not have SELECT permission on. A similar bug was fixed earlier in commit 804b6b6db4. The cause of the bug is that the callers of the ExecBuildSlotValueDescription() function got confused when constructing the list of modified columns. If the tuple was routed from a parent, we converted the tuple to the parent's format, but the list of modified columns was grabbed directly from the child's RTE entry. ExecUpdateLockMode() had a similar issue. That lead to confusion on which columns are key columns, leading to wrong tuple lock being taken on tables referenced by foreign keys, when a row is updated with INSERT ON CONFLICT UPDATE. A new isolation test is added for that corner case. With this patch, the ri_RangeTableIndex field is no longer set for partitions that don't have an entry in the range table. Previously, it was set to the RTE entry of the parent relation, but that was confusing. NOTE: This modifies the ResultRelInfo struct, replacing the ri_PartitionRoot field with ri_RootResultRelInfo. That's a bit risky to backpatch, because it breaks any extensions accessing the field. The change that ri_RangeTableIndex is not set for partitions could potentially break extensions, too. The ResultRelInfos are visible to FDWs at least, and this patch required small changes to postgres_fdw. Nevertheless, this seem like the least bad option. I don't think these fields widely used in extensions; I don't think there are FDWs out there that uses the FDW "direct update" API, other than postgres_fdw. If there is, you will get a compilation error, so hopefully it is caught quickly. Backpatch to 11, where support for both cross-partition UPDATEs, and unique indexes on partitioned tables, were added. Reviewed-by: Amit Langote Security: CVE-2021-3393
5 years ago
convert_tuples_by_name(RelationGetDescr(rootRelInfo->ri_RelationDesc),
RelationGetDescr(partRelInfo->ri_RelationDesc));
/*
* If a partition has a different rowtype than the root parent, initialize
* a slot dedicated to storing this partition's tuples. The slot is used
* for various operations that are applied to tuples after routing, such
* as checking constraints.
*/
if (partRelInfo->ri_RootToPartitionMap != NULL)
{
Relation partrel = partRelInfo->ri_RelationDesc;
/*
* Initialize the slot itself setting its descriptor to this
* partition's TupleDesc; TupleDesc reference will be released at the
* end of the command.
*/
partRelInfo->ri_PartitionTupleSlot =
tableam: Add and use scan APIs. Too allow table accesses to be not directly dependent on heap, several new abstractions are needed. Specifically: 1) Heap scans need to be generalized into table scans. Do this by introducing TableScanDesc, which will be the "base class" for individual AMs. This contains the AM independent fields from HeapScanDesc. The previous heap_{beginscan,rescan,endscan} et al. have been replaced with a table_ version. There's no direct replacement for heap_getnext(), as that returned a HeapTuple, which is undesirable for a other AMs. Instead there's table_scan_getnextslot(). But note that heap_getnext() lives on, it's still used widely to access catalog tables. This is achieved by new scan_begin, scan_end, scan_rescan, scan_getnextslot callbacks. 2) The portion of parallel scans that's shared between backends need to be able to do so without the user doing per-AM work. To achieve that new parallelscan_{estimate, initialize, reinitialize} callbacks are introduced, which operate on a new ParallelTableScanDesc, which again can be subclassed by AMs. As it is likely that several AMs are going to be block oriented, block oriented callbacks that can be shared between such AMs are provided and used by heap. table_block_parallelscan_{estimate, intiialize, reinitialize} as callbacks, and table_block_parallelscan_{nextpage, init} for use in AMs. These operate on a ParallelBlockTableScanDesc. 3) Index scans need to be able to access tables to return a tuple, and there needs to be state across individual accesses to the heap to store state like buffers. That's now handled by introducing a sort-of-scan IndexFetchTable, which again is intended to be subclassed by individual AMs (for heap IndexFetchHeap). The relevant callbacks for an AM are index_fetch_{end, begin, reset} to create the necessary state, and index_fetch_tuple to retrieve an indexed tuple. Note that index_fetch_tuple implementations need to be smarter than just blindly fetching the tuples for AMs that have optimizations similar to heap's HOT - the currently alive tuple in the update chain needs to be fetched if appropriate. Similar to table_scan_getnextslot(), it's undesirable to continue to return HeapTuples. Thus index_fetch_heap (might want to rename that later) now accepts a slot as an argument. Core code doesn't have a lot of call sites performing index scans without going through the systable_* API (in contrast to loads of heap_getnext calls and working directly with HeapTuples). Index scans now store the result of a search in IndexScanDesc->xs_heaptid, rather than xs_ctup->t_self. As the target is not generally a HeapTuple anymore that seems cleaner. To be able to sensible adapt code to use the above, two further callbacks have been introduced: a) slot_callbacks returns a TupleTableSlotOps* suitable for creating slots capable of holding a tuple of the AMs type. table_slot_callbacks() and table_slot_create() are based upon that, but have additional logic to deal with views, foreign tables, etc. While this change could have been done separately, nearly all the call sites that needed to be adapted for the rest of this commit also would have been needed to be adapted for table_slot_callbacks(), making separation not worthwhile. b) tuple_satisfies_snapshot checks whether the tuple in a slot is currently visible according to a snapshot. That's required as a few places now don't have a buffer + HeapTuple around, but a slot (which in heap's case internally has that information). Additionally a few infrastructure changes were needed: I) SysScanDesc, as used by systable_{beginscan, getnext} et al. now internally uses a slot to keep track of tuples. While systable_getnext() still returns HeapTuples, and will so for the foreseeable future, the index API (see 1) above) now only deals with slots. The remainder, and largest part, of this commit is then adjusting all scans in postgres to use the new APIs. Author: Andres Freund, Haribabu Kommi, Alvaro Herrera Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de https://postgr.es/m/20160812231527.GA690404@alvherre.pgsql
7 years ago
table_slot_create(partrel, &estate->es_tupleTable);
}
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
else
partRelInfo->ri_PartitionTupleSlot = NULL;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/*
* If the partition is a foreign table, let the FDW init itself for
* routing tuples to the partition.
*/
if (partRelInfo->ri_FdwRoutine != NULL &&
partRelInfo->ri_FdwRoutine->BeginForeignInsert != NULL)
partRelInfo->ri_FdwRoutine->BeginForeignInsert(mtstate, partRelInfo);
/*
* Determine if the FDW supports batch insert and determine the batch size
* (a FDW may support batching, but it may be disabled for the
* server/table or for this particular query).
*
* If the FDW does not support batching, we set the batch size to 1.
*/
if (mtstate->operation == CMD_INSERT &&
partRelInfo->ri_FdwRoutine != NULL &&
partRelInfo->ri_FdwRoutine->GetForeignModifyBatchSize &&
partRelInfo->ri_FdwRoutine->ExecForeignBatchInsert)
partRelInfo->ri_BatchSize =
partRelInfo->ri_FdwRoutine->GetForeignModifyBatchSize(partRelInfo);
else
partRelInfo->ri_BatchSize = 1;
Assert(partRelInfo->ri_BatchSize >= 1);
partRelInfo->ri_CopyMultiInsertBuffer = NULL;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/*
* Keep track of it in the PartitionTupleRouting->partitions array.
*/
Assert(dispatch->indexes[partidx] == -1);
rri_index = proute->num_partitions++;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/* Allocate or enlarge the array, as needed */
if (proute->num_partitions >= proute->max_partitions)
{
if (proute->max_partitions == 0)
{
proute->max_partitions = 8;
proute->partitions = (ResultRelInfo **)
palloc(sizeof(ResultRelInfo *) * proute->max_partitions);
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
proute->is_borrowed_rel = (bool *)
palloc(sizeof(bool) * proute->max_partitions);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
}
else
{
proute->max_partitions *= 2;
proute->partitions = (ResultRelInfo **)
repalloc(proute->partitions, sizeof(ResultRelInfo *) *
proute->max_partitions);
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
proute->is_borrowed_rel = (bool *)
repalloc(proute->is_borrowed_rel, sizeof(bool) *
proute->max_partitions);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
}
}
proute->partitions[rri_index] = partRelInfo;
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
proute->is_borrowed_rel[rri_index] = is_borrowed_rel;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
dispatch->indexes[partidx] = rri_index;
MemoryContextSwitchTo(oldcxt);
}
/*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* ExecInitPartitionDispatchInfo
* Lock the partitioned table (if not locked already) and initialize
* PartitionDispatch for a partitioned table and store it in the next
* available slot in the proute->partition_dispatch_info array. Also,
* record the index into this array in the parent_pd->indexes[] array in
* the partidx element so that we can properly retrieve the newly created
* PartitionDispatch later.
*/
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
static PartitionDispatch
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
ExecInitPartitionDispatchInfo(EState *estate,
PartitionTupleRouting *proute, Oid partoid,
Fix permission checks on constraint violation errors on partitions. If a cross-partition UPDATE violates a constraint on the target partition, and the columns in the new partition are in different physical order than in the parent, the error message can reveal columns that the user does not have SELECT permission on. A similar bug was fixed earlier in commit 804b6b6db4. The cause of the bug is that the callers of the ExecBuildSlotValueDescription() function got confused when constructing the list of modified columns. If the tuple was routed from a parent, we converted the tuple to the parent's format, but the list of modified columns was grabbed directly from the child's RTE entry. ExecUpdateLockMode() had a similar issue. That lead to confusion on which columns are key columns, leading to wrong tuple lock being taken on tables referenced by foreign keys, when a row is updated with INSERT ON CONFLICT UPDATE. A new isolation test is added for that corner case. With this patch, the ri_RangeTableIndex field is no longer set for partitions that don't have an entry in the range table. Previously, it was set to the RTE entry of the parent relation, but that was confusing. NOTE: This modifies the ResultRelInfo struct, replacing the ri_PartitionRoot field with ri_RootResultRelInfo. That's a bit risky to backpatch, because it breaks any extensions accessing the field. The change that ri_RangeTableIndex is not set for partitions could potentially break extensions, too. The ResultRelInfos are visible to FDWs at least, and this patch required small changes to postgres_fdw. Nevertheless, this seem like the least bad option. I don't think these fields widely used in extensions; I don't think there are FDWs out there that uses the FDW "direct update" API, other than postgres_fdw. If there is, you will get a compilation error, so hopefully it is caught quickly. Backpatch to 11, where support for both cross-partition UPDATEs, and unique indexes on partitioned tables, were added. Reviewed-by: Amit Langote Security: CVE-2021-3393
5 years ago
PartitionDispatch parent_pd, int partidx,
ResultRelInfo *rootResultRelInfo)
{
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
Relation rel;
PartitionDesc partdesc;
PartitionDispatch pd;
int dispatchidx;
MemoryContext oldcxt;
ALTER TABLE ... DETACH PARTITION ... CONCURRENTLY Allow a partition be detached from its partitioned table without blocking concurrent queries, by running in two transactions and only requiring ShareUpdateExclusive in the partitioned table. Because it runs in two transactions, it cannot be used in a transaction block. This is the main reason to use dedicated syntax: so that users can choose to use the original mode if they need it. But also, it doesn't work when a default partition exists (because an exclusive lock would still need to be obtained on it, in order to change its partition constraint.) In case the second transaction is cancelled or a crash occurs, there's ALTER TABLE .. DETACH PARTITION .. FINALIZE, which executes the final steps. The main trick to make this work is the addition of column pg_inherits.inhdetachpending, initially false; can only be set true in the first part of this command. Once that is committed, concurrent transactions that use a PartitionDirectory will include or ignore partitions so marked: in optimizer they are ignored if the row is marked committed for the snapshot; in executor they are always included. As a result, and because of the way PartitionDirectory caches partition descriptors, queries that were planned before the detach will see the rows in the detached partition and queries that are planned after the detach, won't. A CHECK constraint is created that duplicates the partition constraint. This is probably not strictly necessary, and some users will prefer to remove it afterwards, but if the partition is re-attached to a partitioned table, the constraint needn't be rechecked. Author: Álvaro Herrera <alvherre@alvh.no-ip.org> Reviewed-by: Amit Langote <amitlangote09@gmail.com> Reviewed-by: Justin Pryzby <pryzby@telsasoft.com> Discussion: https://postgr.es/m/20200803234854.GA24158@alvherre.pgsql
5 years ago
/*
* For data modification, it is better that executor does not include
Fix relcache inconsistency hazard in partition detach During queries coming from ri_triggers.c, we need to omit partitions that are marked pending detach -- otherwise, the RI query is tricked into allowing a row into the referencing table whose corresponding row is in the detached partition. Which is bogus: once the detach operation completes, the row becomes an orphan. However, the code was not doing that in repeatable-read transactions, because relcache kept a copy of the partition descriptor that included the partition, and used it in the RI query. This commit changes the partdesc cache code to only keep descriptors that aren't dependent on a snapshot (namely: those where no detached partition exist, and those where detached partitions are included). When a partdesc-without- detached-partitions is requested, we create one afresh each time; also, those partdescs are stored in PortalContext instead of CacheMemoryContext. find_inheritance_children gets a new output *detached_exist boolean, which indicates whether any partition marked pending-detach is found. Its "include_detached" input flag is changed to "omit_detached", because that name captures desired the semantics more naturally. CreatePartitionDirectory() and RelationGetPartitionDesc() arguments are identically renamed. This was noticed because a buildfarm member that runs with relcache clobbering, which would not keep the improperly cached partdesc, broke one test, which led us to realize that the expected output of that test was bogus. This commit also corrects that expected output. Author: Amit Langote <amitlangote09@gmail.com> Author: Álvaro Herrera <alvherre@alvh.no-ip.org> Discussion: https://postgr.es/m/3269784.1617215412@sss.pgh.pa.us
5 years ago
* partitions being detached, except when running in snapshot-isolation
* mode. This means that a read-committed transaction immediately gets a
* "no partition for tuple" error when a tuple is inserted into a
* partition that's being detached concurrently, but a transaction in
* repeatable-read mode can still use such a partition.
ALTER TABLE ... DETACH PARTITION ... CONCURRENTLY Allow a partition be detached from its partitioned table without blocking concurrent queries, by running in two transactions and only requiring ShareUpdateExclusive in the partitioned table. Because it runs in two transactions, it cannot be used in a transaction block. This is the main reason to use dedicated syntax: so that users can choose to use the original mode if they need it. But also, it doesn't work when a default partition exists (because an exclusive lock would still need to be obtained on it, in order to change its partition constraint.) In case the second transaction is cancelled or a crash occurs, there's ALTER TABLE .. DETACH PARTITION .. FINALIZE, which executes the final steps. The main trick to make this work is the addition of column pg_inherits.inhdetachpending, initially false; can only be set true in the first part of this command. Once that is committed, concurrent transactions that use a PartitionDirectory will include or ignore partitions so marked: in optimizer they are ignored if the row is marked committed for the snapshot; in executor they are always included. As a result, and because of the way PartitionDirectory caches partition descriptors, queries that were planned before the detach will see the rows in the detached partition and queries that are planned after the detach, won't. A CHECK constraint is created that duplicates the partition constraint. This is probably not strictly necessary, and some users will prefer to remove it afterwards, but if the partition is re-attached to a partitioned table, the constraint needn't be rechecked. Author: Álvaro Herrera <alvherre@alvh.no-ip.org> Reviewed-by: Amit Langote <amitlangote09@gmail.com> Reviewed-by: Justin Pryzby <pryzby@telsasoft.com> Discussion: https://postgr.es/m/20200803234854.GA24158@alvherre.pgsql
5 years ago
*/
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
if (estate->es_partition_directory == NULL)
estate->es_partition_directory =
ALTER TABLE ... DETACH PARTITION ... CONCURRENTLY Allow a partition be detached from its partitioned table without blocking concurrent queries, by running in two transactions and only requiring ShareUpdateExclusive in the partitioned table. Because it runs in two transactions, it cannot be used in a transaction block. This is the main reason to use dedicated syntax: so that users can choose to use the original mode if they need it. But also, it doesn't work when a default partition exists (because an exclusive lock would still need to be obtained on it, in order to change its partition constraint.) In case the second transaction is cancelled or a crash occurs, there's ALTER TABLE .. DETACH PARTITION .. FINALIZE, which executes the final steps. The main trick to make this work is the addition of column pg_inherits.inhdetachpending, initially false; can only be set true in the first part of this command. Once that is committed, concurrent transactions that use a PartitionDirectory will include or ignore partitions so marked: in optimizer they are ignored if the row is marked committed for the snapshot; in executor they are always included. As a result, and because of the way PartitionDirectory caches partition descriptors, queries that were planned before the detach will see the rows in the detached partition and queries that are planned after the detach, won't. A CHECK constraint is created that duplicates the partition constraint. This is probably not strictly necessary, and some users will prefer to remove it afterwards, but if the partition is re-attached to a partitioned table, the constraint needn't be rechecked. Author: Álvaro Herrera <alvherre@alvh.no-ip.org> Reviewed-by: Amit Langote <amitlangote09@gmail.com> Reviewed-by: Justin Pryzby <pryzby@telsasoft.com> Discussion: https://postgr.es/m/20200803234854.GA24158@alvherre.pgsql
5 years ago
CreatePartitionDirectory(estate->es_query_cxt,
Fix relcache inconsistency hazard in partition detach During queries coming from ri_triggers.c, we need to omit partitions that are marked pending detach -- otherwise, the RI query is tricked into allowing a row into the referencing table whose corresponding row is in the detached partition. Which is bogus: once the detach operation completes, the row becomes an orphan. However, the code was not doing that in repeatable-read transactions, because relcache kept a copy of the partition descriptor that included the partition, and used it in the RI query. This commit changes the partdesc cache code to only keep descriptors that aren't dependent on a snapshot (namely: those where no detached partition exist, and those where detached partitions are included). When a partdesc-without- detached-partitions is requested, we create one afresh each time; also, those partdescs are stored in PortalContext instead of CacheMemoryContext. find_inheritance_children gets a new output *detached_exist boolean, which indicates whether any partition marked pending-detach is found. Its "include_detached" input flag is changed to "omit_detached", because that name captures desired the semantics more naturally. CreatePartitionDirectory() and RelationGetPartitionDesc() arguments are identically renamed. This was noticed because a buildfarm member that runs with relcache clobbering, which would not keep the improperly cached partdesc, broke one test, which led us to realize that the expected output of that test was bogus. This commit also corrects that expected output. Author: Amit Langote <amitlangote09@gmail.com> Author: Álvaro Herrera <alvherre@alvh.no-ip.org> Discussion: https://postgr.es/m/3269784.1617215412@sss.pgh.pa.us
5 years ago
!IsolationUsesXactSnapshot());
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
oldcxt = MemoryContextSwitchTo(proute->memcxt);
/*
* Only sub-partitioned tables need to be locked here. The root
* partitioned table will already have been locked as it's referenced in
* the query's rtable.
*/
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
if (partoid != RelationGetRelid(proute->partition_root))
rel = table_open(partoid, RowExclusiveLock);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
else
rel = proute->partition_root;
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
partdesc = PartitionDirectoryLookup(estate->es_partition_directory, rel);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
pd = (PartitionDispatch) palloc(offsetof(PartitionDispatchData, indexes) +
partdesc->nparts * sizeof(int));
pd->reldesc = rel;
pd->key = RelationGetPartitionKey(rel);
pd->keystate = NIL;
pd->partdesc = partdesc;
if (parent_pd != NULL)
{
TupleDesc tupdesc = RelationGetDescr(rel);
/*
* For sub-partitioned tables where the column order differs from its
* direct parent partitioned table, we must store a tuple table slot
* initialized with its tuple descriptor and a tuple conversion map to
* convert a tuple from its parent's rowtype to its own. This is to
* make sure that we are looking at the correct row using the correct
* tuple descriptor when computing its partition key for tuple
* routing.
*/
pd->tupmap = build_attrmap_by_name_if_req(RelationGetDescr(parent_pd->reldesc),
tupdesc);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
pd->tupslot = pd->tupmap ?
MakeSingleTupleTableSlot(tupdesc, &TTSOpsVirtual) : NULL;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
}
else
{
/* Not required for the root partitioned table */
pd->tupmap = NULL;
pd->tupslot = NULL;
}
/*
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
* Initialize with -1 to signify that the corresponding partition's
* ResultRelInfo or PartitionDispatch has not been created yet.
*/
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
memset(pd->indexes, -1, sizeof(int) * partdesc->nparts);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/* Track in PartitionTupleRouting for later use */
dispatchidx = proute->num_dispatch++;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/* Allocate or enlarge the array, as needed */
if (proute->num_dispatch >= proute->max_dispatch)
{
if (proute->max_dispatch == 0)
{
proute->max_dispatch = 4;
proute->partition_dispatch_info = (PartitionDispatch *)
palloc(sizeof(PartitionDispatch) * proute->max_dispatch);
proute->nonleaf_partitions = (ResultRelInfo **)
palloc(sizeof(ResultRelInfo *) * proute->max_dispatch);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
}
else
{
proute->max_dispatch *= 2;
proute->partition_dispatch_info = (PartitionDispatch *)
repalloc(proute->partition_dispatch_info,
sizeof(PartitionDispatch) * proute->max_dispatch);
proute->nonleaf_partitions = (ResultRelInfo **)
repalloc(proute->nonleaf_partitions,
sizeof(ResultRelInfo *) * proute->max_dispatch);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
}
}
proute->partition_dispatch_info[dispatchidx] = pd;
/*
* If setting up a PartitionDispatch for a sub-partitioned table, we may
* also need a minimally valid ResultRelInfo for checking the partition
* constraint later; set that up now.
*/
if (parent_pd)
{
ResultRelInfo *rri = makeNode(ResultRelInfo);
Fix permission checks on constraint violation errors on partitions. If a cross-partition UPDATE violates a constraint on the target partition, and the columns in the new partition are in different physical order than in the parent, the error message can reveal columns that the user does not have SELECT permission on. A similar bug was fixed earlier in commit 804b6b6db4. The cause of the bug is that the callers of the ExecBuildSlotValueDescription() function got confused when constructing the list of modified columns. If the tuple was routed from a parent, we converted the tuple to the parent's format, but the list of modified columns was grabbed directly from the child's RTE entry. ExecUpdateLockMode() had a similar issue. That lead to confusion on which columns are key columns, leading to wrong tuple lock being taken on tables referenced by foreign keys, when a row is updated with INSERT ON CONFLICT UPDATE. A new isolation test is added for that corner case. With this patch, the ri_RangeTableIndex field is no longer set for partitions that don't have an entry in the range table. Previously, it was set to the RTE entry of the parent relation, but that was confusing. NOTE: This modifies the ResultRelInfo struct, replacing the ri_PartitionRoot field with ri_RootResultRelInfo. That's a bit risky to backpatch, because it breaks any extensions accessing the field. The change that ri_RangeTableIndex is not set for partitions could potentially break extensions, too. The ResultRelInfos are visible to FDWs at least, and this patch required small changes to postgres_fdw. Nevertheless, this seem like the least bad option. I don't think these fields widely used in extensions; I don't think there are FDWs out there that uses the FDW "direct update" API, other than postgres_fdw. If there is, you will get a compilation error, so hopefully it is caught quickly. Backpatch to 11, where support for both cross-partition UPDATEs, and unique indexes on partitioned tables, were added. Reviewed-by: Amit Langote Security: CVE-2021-3393
5 years ago
InitResultRelInfo(rri, rel, 0, rootResultRelInfo, 0);
proute->nonleaf_partitions[dispatchidx] = rri;
}
else
proute->nonleaf_partitions[dispatchidx] = NULL;
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/*
* Finally, if setting up a PartitionDispatch for a sub-partitioned table,
* install a downlink in the parent to allow quick descent.
*/
if (parent_pd)
{
Assert(parent_pd->indexes[partidx] == -1);
parent_pd->indexes[partidx] = dispatchidx;
}
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
MemoryContextSwitchTo(oldcxt);
return pd;
}
/*
* ExecCleanupTupleRouting -- Clean up objects allocated for partition tuple
* routing.
*
* Close all the partitioned tables, leaf partitions, and their indices.
*/
void
ExecCleanupTupleRouting(ModifyTableState *mtstate,
PartitionTupleRouting *proute)
{
int i;
/*
* Remember, proute->partition_dispatch_info[0] corresponds to the root
* partitioned table, which we must not try to close, because it is the
* main target table of the query that will be closed by callers such as
* ExecEndPlan() or DoCopy(). Also, tupslot is NULL for the root
* partitioned table.
*/
for (i = 1; i < proute->num_dispatch; i++)
{
PartitionDispatch pd = proute->partition_dispatch_info[i];
table_close(pd->reldesc, NoLock);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
if (pd->tupslot)
ExecDropSingleTupleTableSlot(pd->tupslot);
}
for (i = 0; i < proute->num_partitions; i++)
{
ResultRelInfo *resultRelInfo = proute->partitions[i];
/* Allow any FDWs to shut down */
if (resultRelInfo->ri_FdwRoutine != NULL &&
resultRelInfo->ri_FdwRoutine->EndForeignInsert != NULL)
resultRelInfo->ri_FdwRoutine->EndForeignInsert(mtstate->ps.state,
resultRelInfo);
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
/*
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
* Close it if it's not one of the result relations borrowed from the
* owning ModifyTableState; those will be closed by ExecEndPlan().
Redesign initialization of partition routing structures This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well as the future MERGE) on partitioned tables. This changes the setup for tuple routing so that it does far less work during the initial setup and pushes more work out to when partitions receive tuples. PartitionDispatchData structs for sub-partitioned tables are only created when a tuple gets routed through it. The possibly large arrays in the PartitionTupleRouting struct have largely been removed. The partitions[] array remains but now never contains any NULL gaps. Previously the NULLs had to be skipped during ExecCleanupTupleRouting(), which could add a large overhead to the cleanup when the number of partitions was large. The partitions[] array is allocated small to start with and only enlarged when we route tuples to enough partitions that it runs out of space. This allows us to keep simple single-row partition INSERTs running quickly. Redesign The arrays in PartitionTupleRouting which stored the tuple translation maps have now been removed. These have been moved out into a PartitionRoutingInfo struct which is an additional field in ResultRelInfo. The find_all_inheritors() call still remains by far the slowest part of ExecSetupPartitionTupleRouting(). This commit just removes the other slow parts. In passing also rename the tuple translation maps from being ParentToChild and ChildToParent to being RootToPartition and PartitionToRoot. The old names mislead you into thinking that a partition of some sub-partitioned table would translate to the rowtype of the sub-partitioned table rather than the root partitioned table. Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera Testing help from Jesper Pedersen and Kato Sho. Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
7 years ago
*/
Postpone some stuff out of ExecInitModifyTable. Arrange to do some things on-demand, rather than immediately during executor startup, because there's a fair chance of never having to do them at all: * Don't open result relations' indexes until needed. * Don't initialize partition tuple routing, nor the child-to-root tuple conversion map, until needed. This wins in UPDATEs on partitioned tables when only some of the partitions will actually receive updates; with larger partition counts the savings is quite noticeable. Also, we can remove some sketchy heuristics in ExecInitModifyTable about whether to set up tuple routing. Also, remove execPartition.c's private hash table tracking which partitions were already opened by the ModifyTable node. Instead use the hash added to ModifyTable itself by commit 86dc90056. To allow lazy computation of the conversion maps, we now set ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it only in some, not terribly well-defined, cases. This has user-visible side effects in that now more error messages refer to the root relation instead of some partition (and provide error data in the root's column order, too). It looks to me like this is a strict improvement in consistency, so I don't have a problem with the output changes visible in this commit. Extracted from a larger patch, which seemed to me to be too messy to push in one commit. Amit Langote, reviewed at different times by Heikki Linnakangas and myself Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
5 years ago
if (proute->is_borrowed_rel[i])
continue;
ExecCloseIndices(resultRelInfo);
table_close(resultRelInfo->ri_RelationDesc, NoLock);
}
}
/* ----------------
* FormPartitionKeyDatum
* Construct values[] and isnull[] arrays for the partition key
* of a tuple.
*
* pd Partition dispatch object of the partitioned table
* slot Heap tuple from which to extract partition key
* estate executor state for evaluating any partition key
* expressions (must be non-NULL)
* values Array of partition key Datums (output area)
* isnull Array of is-null indicators (output area)
*
* the ecxt_scantuple slot of estate's per-tuple expr context must point to
* the heap tuple passed in.
* ----------------
*/
static void
FormPartitionKeyDatum(PartitionDispatch pd,
TupleTableSlot *slot,
EState *estate,
Datum *values,
bool *isnull)
{
ListCell *partexpr_item;
int i;
if (pd->key->partexprs != NIL && pd->keystate == NIL)
{
/* Check caller has set up context correctly */
Assert(estate != NULL &&
GetPerTupleExprContext(estate)->ecxt_scantuple == slot);
/* First time through, set up expression evaluation state */
pd->keystate = ExecPrepareExprList(pd->key->partexprs, estate);
}
partexpr_item = list_head(pd->keystate);
for (i = 0; i < pd->key->partnatts; i++)
{
AttrNumber keycol = pd->key->partattrs[i];
Datum datum;
bool isNull;
if (keycol != 0)
{
/* Plain column; get the value directly from the heap tuple */
datum = slot_getattr(slot, keycol, &isNull);
}
else
{
/* Expression; need to evaluate it */
if (partexpr_item == NULL)
elog(ERROR, "wrong number of partition key expressions");
datum = ExecEvalExprSwitchContext((ExprState *) lfirst(partexpr_item),
GetPerTupleExprContext(estate),
&isNull);
Represent Lists as expansible arrays, not chains of cons-cells. Originally, Postgres Lists were a more or less exact reimplementation of Lisp lists, which consist of chains of separately-allocated cons cells, each having a value and a next-cell link. We'd hacked that once before (commit d0b4399d8) to add a separate List header, but the data was still in cons cells. That makes some operations -- notably list_nth() -- O(N), and it's bulky because of the next-cell pointers and per-cell palloc overhead, and it's very cache-unfriendly if the cons cells end up scattered around rather than being adjacent. In this rewrite, we still have List headers, but the data is in a resizable array of values, with no next-cell links. Now we need at most two palloc's per List, and often only one, since we can allocate some values in the same palloc call as the List header. (Of course, extending an existing List may require repalloc's to enlarge the array. But this involves just O(log N) allocations not O(N).) Of course this is not without downsides. The key difficulty is that addition or deletion of a list entry may now cause other entries to move, which it did not before. For example, that breaks foreach() and sister macros, which historically used a pointer to the current cons-cell as loop state. We can repair those macros transparently by making their actual loop state be an integer list index; the exposed "ListCell *" pointer is no longer state carried across loop iterations, but is just a derived value. (In practice, modern compilers can optimize things back to having just one loop state value, at least for simple cases with inline loop bodies.) In principle, this is a semantics change for cases where the loop body inserts or deletes list entries ahead of the current loop index; but I found no such cases in the Postgres code. The change is not at all transparent for code that doesn't use foreach() but chases lists "by hand" using lnext(). The largest share of such code in the backend is in loops that were maintaining "prev" and "next" variables in addition to the current-cell pointer, in order to delete list cells efficiently using list_delete_cell(). However, we no longer need a previous-cell pointer to delete a list cell efficiently. Keeping a next-cell pointer doesn't work, as explained above, but we can improve matters by changing such code to use a regular foreach() loop and then using the new macro foreach_delete_current() to delete the current cell. (This macro knows how to update the associated foreach loop's state so that no cells will be missed in the traversal.) There remains a nontrivial risk of code assuming that a ListCell * pointer will remain good over an operation that could now move the list contents. To help catch such errors, list.c can be compiled with a new define symbol DEBUG_LIST_MEMORY_USAGE that forcibly moves list contents whenever that could possibly happen. This makes list operations significantly more expensive so it's not normally turned on (though it is on by default if USE_VALGRIND is on). There are two notable API differences from the previous code: * lnext() now requires the List's header pointer in addition to the current cell's address. * list_delete_cell() no longer requires a previous-cell argument. These changes are somewhat unfortunate, but on the other hand code using either function needs inspection to see if it is assuming anything it shouldn't, so it's not all bad. Programmers should be aware of these significant performance changes: * list_nth() and related functions are now O(1); so there's no major access-speed difference between a list and an array. * Inserting or deleting a list element now takes time proportional to the distance to the end of the list, due to moving the array elements. (However, it typically *doesn't* require palloc or pfree, so except in long lists it's probably still faster than before.) Notably, lcons() used to be about the same cost as lappend(), but that's no longer true if the list is long. Code that uses lcons() and list_delete_first() to maintain a stack might usefully be rewritten to push and pop at the end of the list rather than the beginning. * There are now list_insert_nth...() and list_delete_nth...() functions that add or remove a list cell identified by index. These have the data-movement penalty explained above, but there's no search penalty. * list_concat() and variants now copy the second list's data into storage belonging to the first list, so there is no longer any sharing of cells between the input lists. The second argument is now declared "const List *" to reflect that it isn't changed. This patch just does the minimum needed to get the new implementation in place and fix bugs exposed by the regression tests. As suggested by the foregoing, there's a fair amount of followup work remaining to do. Also, the ENABLE_LIST_COMPAT macros are finally removed in this commit. Code using those should have been gone a dozen years ago. Patch by me; thanks to David Rowley, Jesper Pedersen, and others for review. Discussion: https://postgr.es/m/11587.1550975080@sss.pgh.pa.us
7 years ago
partexpr_item = lnext(pd->keystate, partexpr_item);
}
values[i] = datum;
isnull[i] = isNull;
}
if (partexpr_item != NULL)
elog(ERROR, "wrong number of partition key expressions");
}
/*
* get_partition_for_tuple
* Finds partition of relation which accepts the partition key specified
* in values and isnull
*
* Return value is index of the partition (>= 0 and < partdesc->nparts) if one
* found or -1 if none found.
*/
static int
get_partition_for_tuple(PartitionDispatch pd, Datum *values, bool *isnull)
{
int bound_offset;
int part_index = -1;
PartitionKey key = pd->key;
PartitionDesc partdesc = pd->partdesc;
PartitionBoundInfo boundinfo = partdesc->boundinfo;
/* Route as appropriate based on partitioning strategy. */
switch (key->strategy)
{
case PARTITION_STRATEGY_HASH:
{
uint64 rowHash;
rowHash = compute_partition_hash_value(key->partnatts,
key->partsupfunc,
Collations with nondeterministic comparison This adds a flag "deterministic" to collations. If that is false, such a collation disables various optimizations that assume that strings are equal only if they are byte-wise equal. That then allows use cases such as case-insensitive or accent-insensitive comparisons or handling of strings with different Unicode normal forms. This functionality is only supported with the ICU provider. At least glibc doesn't appear to have any locales that work in a nondeterministic way, so it's not worth supporting this for the libc provider. The term "deterministic comparison" in this context is from Unicode Technical Standard #10 (https://unicode.org/reports/tr10/#Deterministic_Comparison). This patch makes changes in three areas: - CREATE COLLATION DDL changes and system catalog changes to support this new flag. - Many executor nodes and auxiliary code are extended to track collations. Previously, this code would just throw away collation information, because the eventually-called user-defined functions didn't use it since they only cared about equality, which didn't need collation information. - String data type functions that do equality comparisons and hashing are changed to take the (non-)deterministic flag into account. For comparison, this just means skipping various shortcuts and tie breakers that use byte-wise comparison. For hashing, we first need to convert the input string to a canonical "sort key" using the ICU analogue of strxfrm(). Reviewed-by: Daniel Verite <daniel@manitou-mail.org> Reviewed-by: Peter Geoghegan <pg@bowt.ie> Discussion: https://www.postgresql.org/message-id/flat/1ccc668f-4cbc-0bef-af67-450b47cdfee7@2ndquadrant.com
7 years ago
key->partcollation,
values, isnull);
Fix hash partition pruning with asymmetric partition sets. perform_pruning_combine_step() was not taught about the number of partition indexes used in hash partitioning; more embarrassingly, get_matching_hash_bounds() also had it wrong. These errors are masked in the common case where all the partitions have the same modulus and no partition is missing. However, with missing or unequal-size partitions, we could erroneously prune some partitions that need to be scanned, leading to silently wrong query answers. While a minimal-footprint fix for this could be to export get_partition_bound_num_indexes and make the incorrect functions use it, I'm of the opinion that that function should never have existed in the first place. It's not reasonable data structure design that PartitionBoundInfoData lacks any explicit record of the length of its indexes[] array. Perhaps that was all right when it could always be assumed equal to ndatums, but something should have been done about it as soon as that stopped being true. Putting in an explicit "nindexes" field makes both partition_bounds_equal() and partition_bounds_copy() simpler, safer, and faster than before, and removes explicit knowledge of the number-of-partition-indexes rules from some other places too. This change also makes get_hash_partition_greatest_modulus obsolete. I left that in place in case any external code uses it, but no core code does anymore. Per bug #16840 from Michał Albrycht. Back-patch to v11 where the hash partitioning code came in. (In the back branches, add the new field at the end of PartitionBoundInfoData to minimize ABI risks.) Discussion: https://postgr.es/m/16840-571a22976f829ad4@postgresql.org
5 years ago
part_index = boundinfo->indexes[rowHash % boundinfo->nindexes];
}
break;
case PARTITION_STRATEGY_LIST:
if (isnull[0])
{
if (partition_bound_accepts_nulls(boundinfo))
part_index = boundinfo->null_index;
}
else
{
bool equal = false;
bound_offset = partition_list_bsearch(key->partsupfunc,
key->partcollation,
boundinfo,
values[0], &equal);
if (bound_offset >= 0 && equal)
part_index = boundinfo->indexes[bound_offset];
}
break;
case PARTITION_STRATEGY_RANGE:
{
bool equal = false,
range_partkey_has_null = false;
int i;
/*
* No range includes NULL, so this will be accepted by the
* default partition if there is one, and otherwise rejected.
*/
for (i = 0; i < key->partnatts; i++)
{
if (isnull[i])
{
range_partkey_has_null = true;
break;
}
}
if (!range_partkey_has_null)
{
bound_offset = partition_range_datum_bsearch(key->partsupfunc,
key->partcollation,
boundinfo,
key->partnatts,
values,
&equal);
/*
* The bound at bound_offset is less than or equal to the
* tuple value, so the bound at offset+1 is the upper
* bound of the partition we're looking for, if there
* actually exists one.
*/
part_index = boundinfo->indexes[bound_offset + 1];
}
}
break;
default:
elog(ERROR, "unexpected partition strategy: %d",
(int) key->strategy);
}
/*
* part_index < 0 means we failed to find a partition of this parent. Use
* the default partition, if there is one.
*/
if (part_index < 0)
part_index = boundinfo->default_index;
return part_index;
}
/*
* ExecBuildSlotPartitionKeyDescription
*
* This works very much like BuildIndexValueDescription() and is currently
* used for building error messages when ExecFindPartition() fails to find
* partition for a row.
*/
static char *
ExecBuildSlotPartitionKeyDescription(Relation rel,
Datum *values,
bool *isnull,
int maxfieldlen)
{
StringInfoData buf;
PartitionKey key = RelationGetPartitionKey(rel);
int partnatts = get_partition_natts(key);
int i;
Oid relid = RelationGetRelid(rel);
AclResult aclresult;
if (check_enable_rls(relid, InvalidOid, true) == RLS_ENABLED)
return NULL;
/* If the user has table-level access, just go build the description. */
aclresult = pg_class_aclcheck(relid, GetUserId(), ACL_SELECT);
if (aclresult != ACLCHECK_OK)
{
/*
* Step through the columns of the partition key and make sure the
* user has SELECT rights on all of them.
*/
for (i = 0; i < partnatts; i++)
{
AttrNumber attnum = get_partition_col_attnum(key, i);
/*
* If this partition key column is an expression, we return no
* detail rather than try to figure out what column(s) the
* expression includes and if the user has SELECT rights on them.
*/
if (attnum == InvalidAttrNumber ||
pg_attribute_aclcheck(relid, attnum, GetUserId(),
ACL_SELECT) != ACLCHECK_OK)
return NULL;
}
}
initStringInfo(&buf);
appendStringInfo(&buf, "(%s) = (",
pg_get_partkeydef_columns(relid, true));
for (i = 0; i < partnatts; i++)
{
char *val;
int vallen;
if (isnull[i])
val = "null";
else
{
Oid foutoid;
bool typisvarlena;
getTypeOutputInfo(get_partition_col_typid(key, i),
&foutoid, &typisvarlena);
val = OidOutputFunctionCall(foutoid, values[i]);
}
if (i > 0)
appendStringInfoString(&buf, ", ");
/* truncate if needed */
vallen = strlen(val);
if (vallen <= maxfieldlen)
appendBinaryStringInfo(&buf, val, vallen);
else
{
vallen = pg_mbcliplen(val, vallen, maxfieldlen);
appendBinaryStringInfo(&buf, val, vallen);
appendStringInfoString(&buf, "...");
}
}
appendStringInfoChar(&buf, ')');
return buf.data;
}
/*
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
* adjust_partition_colnos
* Adjust the list of UPDATE target column numbers to account for
* attribute differences between the parent and the partition.
*/
static List *
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
adjust_partition_colnos(List *colnos, ResultRelInfo *leaf_part_rri)
{
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
List *new_colnos = NIL;
TupleConversionMap *map = ExecGetChildToRootMap(leaf_part_rri);
AttrMap *attrMap;
ListCell *lc;
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
Assert(map != NULL); /* else we shouldn't be here */
attrMap = map->attrMap;
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
foreach(lc, colnos)
{
AttrNumber parentattrno = lfirst_int(lc);
if (parentattrno <= 0 ||
parentattrno > attrMap->maplen ||
attrMap->attnums[parentattrno - 1] == 0)
elog(ERROR, "unexpected attno %d in target column list",
parentattrno);
new_colnos = lappend_int(new_colnos,
attrMap->attnums[parentattrno - 1]);
}
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028
5 years ago
return new_colnos;
}
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/*-------------------------------------------------------------------------
* Run-Time Partition Pruning Support.
*
* The following series of functions exist to support the removal of unneeded
* subplans for queries against partitioned tables. The supporting functions
* here are designed to work with any plan type which supports an arbitrary
* number of subplans, e.g. Append, MergeAppend.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*
* When pruning involves comparison of a partition key to a constant, it's
* done by the planner. However, if we have a comparison to a non-constant
* but not volatile expression, that presents an opportunity for run-time
* pruning by the executor, allowing irrelevant partitions to be skipped
* dynamically.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*
* We must distinguish expressions containing PARAM_EXEC Params from
* expressions that don't contain those. Even though a PARAM_EXEC Param is
* considered to be a stable expression, it can change value from one plan
* node scan to the next during query execution. Stable comparison
* expressions that don't involve such Params allow partition pruning to be
* done once during executor startup. Expressions that do involve such Params
* require us to prune separately for each scan of the parent plan node.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*
* Note that pruning away unneeded subplans during executor startup has the
* added benefit of not having to initialize the unneeded subplans at all.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*
*
* Functions:
*
* ExecCreatePartitionPruneState:
* Creates the PartitionPruneState required by each of the two pruning
* functions. Details stored include how to map the partition index
* returned by the partition pruning code into subplan indexes.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*
* ExecFindInitialMatchingSubPlans:
* Returns indexes of matching subplans. Partition pruning is attempted
* without any evaluation of expressions containing PARAM_EXEC Params.
* This function must be called during executor startup for the parent
* plan before the subplans themselves are initialized. Subplans which
* are found not to match by this function must be removed from the
* plan's list of subplans during execution, as this function performs a
* remap of the partition index to subplan index map and the newly
* created map provides indexes only for subplans which remain after
* calling this function.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*
* ExecFindMatchingSubPlans:
* Returns indexes of matching subplans after evaluating all available
* expressions. This function can only be called during execution and
* must be called again each time the value of a Param listed in
* PartitionPruneState's 'execparamids' changes.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*-------------------------------------------------------------------------
*/
/*
* ExecCreatePartitionPruneState
* Build the data structure required for calling
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
* ExecFindInitialMatchingSubPlans and ExecFindMatchingSubPlans.
*
* 'planstate' is the parent plan node's execution state.
*
* 'partitionpruneinfo' is a PartitionPruneInfo as generated by
* make_partition_pruneinfo. Here we build a PartitionPruneState containing a
* PartitionPruningData for each partitioning hierarchy (i.e., each sublist of
* partitionpruneinfo->prune_infos), each of which contains a
* PartitionedRelPruningData for each PartitionedRelPruneInfo appearing in
* that sublist. This two-level system is needed to keep from confusing the
* different hierarchies when a UNION ALL contains multiple partitioned tables
* as children. The data stored in each PartitionedRelPruningData can be
* re-used each time we re-evaluate which partitions match the pruning steps
* provided in each PartitionedRelPruneInfo.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*/
PartitionPruneState *
ExecCreatePartitionPruneState(PlanState *planstate,
PartitionPruneInfo *partitionpruneinfo)
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
{
EState *estate = planstate->state;
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
PartitionPruneState *prunestate;
int n_part_hierarchies;
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
ListCell *lc;
int i;
Fix relcache inconsistency hazard in partition detach During queries coming from ri_triggers.c, we need to omit partitions that are marked pending detach -- otherwise, the RI query is tricked into allowing a row into the referencing table whose corresponding row is in the detached partition. Which is bogus: once the detach operation completes, the row becomes an orphan. However, the code was not doing that in repeatable-read transactions, because relcache kept a copy of the partition descriptor that included the partition, and used it in the RI query. This commit changes the partdesc cache code to only keep descriptors that aren't dependent on a snapshot (namely: those where no detached partition exist, and those where detached partitions are included). When a partdesc-without- detached-partitions is requested, we create one afresh each time; also, those partdescs are stored in PortalContext instead of CacheMemoryContext. find_inheritance_children gets a new output *detached_exist boolean, which indicates whether any partition marked pending-detach is found. Its "include_detached" input flag is changed to "omit_detached", because that name captures desired the semantics more naturally. CreatePartitionDirectory() and RelationGetPartitionDesc() arguments are identically renamed. This was noticed because a buildfarm member that runs with relcache clobbering, which would not keep the improperly cached partdesc, broke one test, which led us to realize that the expected output of that test was bogus. This commit also corrects that expected output. Author: Amit Langote <amitlangote09@gmail.com> Author: Álvaro Herrera <alvherre@alvh.no-ip.org> Discussion: https://postgr.es/m/3269784.1617215412@sss.pgh.pa.us
5 years ago
/* For data reading, executor always omits detached partitions */
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
if (estate->es_partition_directory == NULL)
estate->es_partition_directory =
Fix relcache inconsistency hazard in partition detach During queries coming from ri_triggers.c, we need to omit partitions that are marked pending detach -- otherwise, the RI query is tricked into allowing a row into the referencing table whose corresponding row is in the detached partition. Which is bogus: once the detach operation completes, the row becomes an orphan. However, the code was not doing that in repeatable-read transactions, because relcache kept a copy of the partition descriptor that included the partition, and used it in the RI query. This commit changes the partdesc cache code to only keep descriptors that aren't dependent on a snapshot (namely: those where no detached partition exist, and those where detached partitions are included). When a partdesc-without- detached-partitions is requested, we create one afresh each time; also, those partdescs are stored in PortalContext instead of CacheMemoryContext. find_inheritance_children gets a new output *detached_exist boolean, which indicates whether any partition marked pending-detach is found. Its "include_detached" input flag is changed to "omit_detached", because that name captures desired the semantics more naturally. CreatePartitionDirectory() and RelationGetPartitionDesc() arguments are identically renamed. This was noticed because a buildfarm member that runs with relcache clobbering, which would not keep the improperly cached partdesc, broke one test, which led us to realize that the expected output of that test was bogus. This commit also corrects that expected output. Author: Amit Langote <amitlangote09@gmail.com> Author: Álvaro Herrera <alvherre@alvh.no-ip.org> Discussion: https://postgr.es/m/3269784.1617215412@sss.pgh.pa.us
5 years ago
CreatePartitionDirectory(estate->es_query_cxt, false);
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
n_part_hierarchies = list_length(partitionpruneinfo->prune_infos);
Assert(n_part_hierarchies > 0);
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/*
* Allocate the data structure
*/
prunestate = (PartitionPruneState *)
palloc(offsetof(PartitionPruneState, partprunedata) +
sizeof(PartitionPruningData *) * n_part_hierarchies);
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
prunestate->execparamids = NULL;
/* other_subplans can change at runtime, so we need our own copy */
prunestate->other_subplans = bms_copy(partitionpruneinfo->other_subplans);
prunestate->do_initial_prune = false; /* may be set below */
prunestate->do_exec_prune = false; /* may be set below */
prunestate->num_partprunedata = n_part_hierarchies;
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/*
* Create a short-term memory context which we'll use when making calls to
* the partition pruning functions. This avoids possible memory leaks,
* since the pruning functions call comparison functions that aren't under
* our control.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*/
prunestate->prune_context =
AllocSetContextCreate(CurrentMemoryContext,
"Partition Prune",
ALLOCSET_DEFAULT_SIZES);
i = 0;
foreach(lc, partitionpruneinfo->prune_infos)
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
{
List *partrelpruneinfos = lfirst_node(List, lc);
int npartrelpruneinfos = list_length(partrelpruneinfos);
PartitionPruningData *prunedata;
ListCell *lc2;
int j;
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
prunedata = (PartitionPruningData *)
palloc(offsetof(PartitionPruningData, partrelprunedata) +
npartrelpruneinfos * sizeof(PartitionedRelPruningData));
prunestate->partprunedata[i] = prunedata;
prunedata->num_partrelprunedata = npartrelpruneinfos;
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
j = 0;
foreach(lc2, partrelpruneinfos)
{
PartitionedRelPruneInfo *pinfo = lfirst_node(PartitionedRelPruneInfo, lc2);
PartitionedRelPruningData *pprune = &prunedata->partrelprunedata[j];
Relation partrel;
PartitionDesc partdesc;
PartitionKey partkey;
/*
* We can rely on the copies of the partitioned table's partition
* key and partition descriptor appearing in its relcache entry,
* because that entry will be held open and locked for the
* duration of this executor run.
*/
partrel = ExecGetRangeTableRelation(estate, pinfo->rtindex);
partkey = RelationGetPartitionKey(partrel);
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
partdesc = PartitionDirectoryLookup(estate->es_partition_directory,
partrel);
/*
ALTER TABLE ... DETACH PARTITION ... CONCURRENTLY Allow a partition be detached from its partitioned table without blocking concurrent queries, by running in two transactions and only requiring ShareUpdateExclusive in the partitioned table. Because it runs in two transactions, it cannot be used in a transaction block. This is the main reason to use dedicated syntax: so that users can choose to use the original mode if they need it. But also, it doesn't work when a default partition exists (because an exclusive lock would still need to be obtained on it, in order to change its partition constraint.) In case the second transaction is cancelled or a crash occurs, there's ALTER TABLE .. DETACH PARTITION .. FINALIZE, which executes the final steps. The main trick to make this work is the addition of column pg_inherits.inhdetachpending, initially false; can only be set true in the first part of this command. Once that is committed, concurrent transactions that use a PartitionDirectory will include or ignore partitions so marked: in optimizer they are ignored if the row is marked committed for the snapshot; in executor they are always included. As a result, and because of the way PartitionDirectory caches partition descriptors, queries that were planned before the detach will see the rows in the detached partition and queries that are planned after the detach, won't. A CHECK constraint is created that duplicates the partition constraint. This is probably not strictly necessary, and some users will prefer to remove it afterwards, but if the partition is re-attached to a partitioned table, the constraint needn't be rechecked. Author: Álvaro Herrera <alvherre@alvh.no-ip.org> Reviewed-by: Amit Langote <amitlangote09@gmail.com> Reviewed-by: Justin Pryzby <pryzby@telsasoft.com> Discussion: https://postgr.es/m/20200803234854.GA24158@alvherre.pgsql
5 years ago
* Initialize the subplan_map and subpart_map.
*
* Because we request detached partitions to be included, and
* detaching waits for old transactions, it is safe to assume that
* no partitions have disappeared since this query was planned.
*
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
* However, new partitions may have been added.
*/
Assert(partdesc->nparts >= pinfo->nparts);
Restructure creation of run-time pruning steps. Previously, gen_partprune_steps() always built executor pruning steps using all suitable clauses, including those containing PARAM_EXEC Params. This meant that the pruning steps were only completely safe for executor run-time (scan start) pruning. To prune at executor startup, we had to ignore the steps involving exec Params. But this doesn't really work in general, since there may be logic changes needed as well --- for example, pruning according to the last operator's btree strategy is the wrong thing if we're not applying that operator. The rules embodied in gen_partprune_steps() and its minions are sufficiently complicated that tracking their incremental effects in other logic seems quite impractical. Short of a complete redesign, the only safe fix seems to be to run gen_partprune_steps() twice, once to create executor startup pruning steps and then again for run-time pruning steps. We can save a few cycles however by noting during the first scan whether we rejected any clauses because they involved exec Params --- if not, we don't need to do the second scan. In support of this, refactor the internal APIs in partprune.c to make more use of passing information in the GeneratePruningStepsContext struct, rather than as separate arguments. This is, I hope, the last piece of our response to a bug report from Alan Jackson. Back-patch to v11 where this code came in. Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
7 years ago
pprune->nparts = partdesc->nparts;
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
pprune->subplan_map = palloc(sizeof(int) * partdesc->nparts);
if (partdesc->nparts == pinfo->nparts)
{
/*
* There are no new partitions, so this is simple. We can
* simply point to the subpart_map from the plan, but we must
* copy the subplan_map since we may change it later.
*/
pprune->subpart_map = pinfo->subpart_map;
memcpy(pprune->subplan_map, pinfo->subplan_map,
sizeof(int) * pinfo->nparts);
/*
* Double-check that the list of unpruned relations has not
* changed. (Pruned partitions are not in relid_map[].)
*/
#ifdef USE_ASSERT_CHECKING
for (int k = 0; k < pinfo->nparts; k++)
{
Assert(partdesc->oids[k] == pinfo->relid_map[k] ||
pinfo->subplan_map[k] == -1);
}
#endif
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
}
else
{
int pd_idx = 0;
int pp_idx;
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
/*
* Some new partitions have appeared since plan time, and
* those are reflected in our PartitionDesc but were not
* present in the one used to construct subplan_map and
* subpart_map. So we must construct new and longer arrays
* where the partitions that were originally present map to
* the same sub-structures, and any added partitions map to
* -1, as if the new partitions had been pruned.
*
* Note: pinfo->relid_map[] may contain InvalidOid entries for
* partitions pruned by the planner. We cannot tell exactly
* which of the partdesc entries these correspond to, but we
* don't have to; just skip over them. The non-pruned
* relid_map entries, however, had better be a subset of the
* partdesc entries and in the same order.
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
*/
pprune->subpart_map = palloc(sizeof(int) * partdesc->nparts);
for (pp_idx = 0; pp_idx < partdesc->nparts; pp_idx++)
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
{
/* Skip any InvalidOid relid_map entries */
while (pd_idx < pinfo->nparts &&
!OidIsValid(pinfo->relid_map[pd_idx]))
pd_idx++;
if (pd_idx < pinfo->nparts &&
pinfo->relid_map[pd_idx] == partdesc->oids[pp_idx])
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
{
/* match... */
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
pprune->subplan_map[pp_idx] =
pinfo->subplan_map[pd_idx];
pprune->subpart_map[pp_idx] =
pinfo->subpart_map[pd_idx];
pd_idx++;
}
else
{
/* this partdesc entry is not in the plan */
pprune->subplan_map[pp_idx] = -1;
pprune->subpart_map[pp_idx] = -1;
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
}
}
/*
* It might seem that we need to skip any trailing InvalidOid
* entries in pinfo->relid_map before checking that we scanned
* all of the relid_map. But we will have skipped them above,
* because they must correspond to some partdesc->oids
* entries; we just couldn't tell which.
*/
if (pd_idx != pinfo->nparts)
elog(ERROR, "could not match partition child tables to plan elements");
Allow ATTACH PARTITION with only ShareUpdateExclusiveLock. We still require AccessExclusiveLock on the partition itself, because otherwise an insert that violates the newly-imposed partition constraint could be in progress at the same time that we're changing that constraint; only the lock level on the parent relation is weakened. To make this safe, we have to cope with (at least) three separate problems. First, relevant DDL might commit while we're in the process of building a PartitionDesc. If so, find_inheritance_children() might see a new partition while the RELOID system cache still has the old partition bound cached, and even before invalidation messages have been queued. To fix that, if we see that the pg_class tuple seems to be missing or to have a null relpartbound, refetch the value directly from the table. We can't get the wrong value, because DETACH PARTITION still requires AccessExclusiveLock throughout; if we ever want to change that, this will need more thought. In testing, I found it quite difficult to hit even the null-relpartbound case; the race condition is extremely tight, but the theoretical risk is there. Second, successive calls to RelationGetPartitionDesc might not return the same answer. The query planner will get confused if lookup up the PartitionDesc for a particular relation does not return a consistent answer for the entire duration of query planning. Likewise, query execution will get confused if the same relation seems to have a different PartitionDesc at different times. Invent a new PartitionDirectory concept and use it to ensure consistency. This ensures that a single invocation of either the planner or the executor sees the same view of the PartitionDesc from beginning to end, but it does not guarantee that the planner and the executor see the same view. Since this allows pointers to old PartitionDesc entries to survive even after a relcache rebuild, also postpone removing the old PartitionDesc entry until we're certain no one is using it. For the most part, it seems to be OK for the planner and executor to have different views of the PartitionDesc, because the executor will just ignore any concurrently added partitions which were unknown at plan time; those partitions won't be part of the inheritance expansion, but invalidation messages will trigger replanning at some point. Normally, this happens by the time the very next command is executed, but if the next command acquires no locks and executes a prepared query, it can manage not to notice until a new transaction is started. We might want to tighten that up, but it's material for a separate patch. There would still be a small window where a query that started just after an ATTACH PARTITION command committed might fail to notice its results -- but only if the command starts before the commit has been acknowledged to the user. All in all, the warts here around serializability seem small enough to be worth accepting for the considerable advantage of being able to add partitions without a full table lock. Although in general the consequences of new partitions showing up between planning and execution are limited to the query not noticing the new partitions, run-time partition pruning will get confused in that case, so that's the third problem that this patch fixes. Run-time partition pruning assumes that indexes into the PartitionDesc are stable between planning and execution. So, add code so that if new partitions are added between plan time and execution time, the indexes stored in the subplan_map[] and subpart_map[] arrays within the plan's PartitionedRelPruneInfo get adjusted accordingly. There does not seem to be a simple way to generalize this scheme to cope with partitions that are removed, mostly because they could then get added back again with different bounds, but it works OK for added partitions. This code does not try to ensure that every backend participating in a parallel query sees the same view of the PartitionDesc. That currently doesn't matter, because we never pass PartitionDesc indexes between backends. Each backend will ignore the concurrently added partitions which it notices, and it doesn't matter if different backends are ignoring different sets of concurrently added partitions. If in the future that matters, for example because we allow writes in parallel query and want all participants to do tuple routing to the same set of partitions, the PartitionDirectory concept could be improved to share PartitionDescs across backends. There is a draft patch to serialize and restore PartitionDescs on the thread where this patch was discussed, which may be a useful place to start. Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs, Amit Langote, and Michael Paquier for discussion, and to Alvaro Herrera for some review. Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
7 years ago
}
Restructure creation of run-time pruning steps. Previously, gen_partprune_steps() always built executor pruning steps using all suitable clauses, including those containing PARAM_EXEC Params. This meant that the pruning steps were only completely safe for executor run-time (scan start) pruning. To prune at executor startup, we had to ignore the steps involving exec Params. But this doesn't really work in general, since there may be logic changes needed as well --- for example, pruning according to the last operator's btree strategy is the wrong thing if we're not applying that operator. The rules embodied in gen_partprune_steps() and its minions are sufficiently complicated that tracking their incremental effects in other logic seems quite impractical. Short of a complete redesign, the only safe fix seems to be to run gen_partprune_steps() twice, once to create executor startup pruning steps and then again for run-time pruning steps. We can save a few cycles however by noting during the first scan whether we rejected any clauses because they involved exec Params --- if not, we don't need to do the second scan. In support of this, refactor the internal APIs in partprune.c to make more use of passing information in the GeneratePruningStepsContext struct, rather than as separate arguments. This is, I hope, the last piece of our response to a bug report from Alan Jackson. Back-patch to v11 where this code came in. Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
7 years ago
/* present_parts is also subject to later modification */
pprune->present_parts = bms_copy(pinfo->present_parts);
Restructure creation of run-time pruning steps. Previously, gen_partprune_steps() always built executor pruning steps using all suitable clauses, including those containing PARAM_EXEC Params. This meant that the pruning steps were only completely safe for executor run-time (scan start) pruning. To prune at executor startup, we had to ignore the steps involving exec Params. But this doesn't really work in general, since there may be logic changes needed as well --- for example, pruning according to the last operator's btree strategy is the wrong thing if we're not applying that operator. The rules embodied in gen_partprune_steps() and its minions are sufficiently complicated that tracking their incremental effects in other logic seems quite impractical. Short of a complete redesign, the only safe fix seems to be to run gen_partprune_steps() twice, once to create executor startup pruning steps and then again for run-time pruning steps. We can save a few cycles however by noting during the first scan whether we rejected any clauses because they involved exec Params --- if not, we don't need to do the second scan. In support of this, refactor the internal APIs in partprune.c to make more use of passing information in the GeneratePruningStepsContext struct, rather than as separate arguments. This is, I hope, the last piece of our response to a bug report from Alan Jackson. Back-patch to v11 where this code came in. Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
7 years ago
/*
* Initialize pruning contexts as needed.
*/
pprune->initial_pruning_steps = pinfo->initial_pruning_steps;
if (pinfo->initial_pruning_steps)
{
Restructure creation of run-time pruning steps. Previously, gen_partprune_steps() always built executor pruning steps using all suitable clauses, including those containing PARAM_EXEC Params. This meant that the pruning steps were only completely safe for executor run-time (scan start) pruning. To prune at executor startup, we had to ignore the steps involving exec Params. But this doesn't really work in general, since there may be logic changes needed as well --- for example, pruning according to the last operator's btree strategy is the wrong thing if we're not applying that operator. The rules embodied in gen_partprune_steps() and its minions are sufficiently complicated that tracking their incremental effects in other logic seems quite impractical. Short of a complete redesign, the only safe fix seems to be to run gen_partprune_steps() twice, once to create executor startup pruning steps and then again for run-time pruning steps. We can save a few cycles however by noting during the first scan whether we rejected any clauses because they involved exec Params --- if not, we don't need to do the second scan. In support of this, refactor the internal APIs in partprune.c to make more use of passing information in the GeneratePruningStepsContext struct, rather than as separate arguments. This is, I hope, the last piece of our response to a bug report from Alan Jackson. Back-patch to v11 where this code came in. Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
7 years ago
ExecInitPruningContext(&pprune->initial_context,
pinfo->initial_pruning_steps,
partdesc, partkey, planstate);
/* Record whether initial pruning is needed at any level */
prunestate->do_initial_prune = true;
}
pprune->exec_pruning_steps = pinfo->exec_pruning_steps;
if (pinfo->exec_pruning_steps)
{
ExecInitPruningContext(&pprune->exec_context,
pinfo->exec_pruning_steps,
partdesc, partkey, planstate);
/* Record whether exec pruning is needed at any level */
prunestate->do_exec_prune = true;
}
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/*
* Accumulate the IDs of all PARAM_EXEC Params affecting the
* partitioning decisions at this plan node.
*/
prunestate->execparamids = bms_add_members(prunestate->execparamids,
pinfo->execparamids);
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
j++;
}
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
i++;
}
return prunestate;
}
Restructure creation of run-time pruning steps. Previously, gen_partprune_steps() always built executor pruning steps using all suitable clauses, including those containing PARAM_EXEC Params. This meant that the pruning steps were only completely safe for executor run-time (scan start) pruning. To prune at executor startup, we had to ignore the steps involving exec Params. But this doesn't really work in general, since there may be logic changes needed as well --- for example, pruning according to the last operator's btree strategy is the wrong thing if we're not applying that operator. The rules embodied in gen_partprune_steps() and its minions are sufficiently complicated that tracking their incremental effects in other logic seems quite impractical. Short of a complete redesign, the only safe fix seems to be to run gen_partprune_steps() twice, once to create executor startup pruning steps and then again for run-time pruning steps. We can save a few cycles however by noting during the first scan whether we rejected any clauses because they involved exec Params --- if not, we don't need to do the second scan. In support of this, refactor the internal APIs in partprune.c to make more use of passing information in the GeneratePruningStepsContext struct, rather than as separate arguments. This is, I hope, the last piece of our response to a bug report from Alan Jackson. Back-patch to v11 where this code came in. Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
7 years ago
/*
* Initialize a PartitionPruneContext for the given list of pruning steps.
*/
static void
ExecInitPruningContext(PartitionPruneContext *context,
List *pruning_steps,
PartitionDesc partdesc,
PartitionKey partkey,
PlanState *planstate)
{
int n_steps;
int partnatts;
ListCell *lc;
n_steps = list_length(pruning_steps);
context->strategy = partkey->strategy;
context->partnatts = partnatts = partkey->partnatts;
context->nparts = partdesc->nparts;
context->boundinfo = partdesc->boundinfo;
context->partcollation = partkey->partcollation;
context->partsupfunc = partkey->partsupfunc;
/* We'll look up type-specific support functions as needed */
context->stepcmpfuncs = (FmgrInfo *)
palloc0(sizeof(FmgrInfo) * n_steps * partnatts);
context->ppccontext = CurrentMemoryContext;
context->planstate = planstate;
/* Initialize expression state for each expression we need */
context->exprstates = (ExprState **)
palloc0(sizeof(ExprState *) * n_steps * partnatts);
foreach(lc, pruning_steps)
{
PartitionPruneStepOp *step = (PartitionPruneStepOp *) lfirst(lc);
ListCell *lc2;
int keyno;
/* not needed for other step kinds */
if (!IsA(step, PartitionPruneStepOp))
continue;
Assert(list_length(step->exprs) <= partnatts);
keyno = 0;
foreach(lc2, step->exprs)
{
Expr *expr = (Expr *) lfirst(lc2);
/* not needed for Consts */
if (!IsA(expr, Const))
{
int stateidx = PruneCxtStateIdx(partnatts,
step->step.step_id,
keyno);
context->exprstates[stateidx] =
ExecInitExpr(expr, context->planstate);
}
keyno++;
}
}
}
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/*
* ExecFindInitialMatchingSubPlans
* Identify the set of subplans that cannot be eliminated by initial
* pruning, disregarding any pruning constraints involving PARAM_EXEC
* Params.
*
* If additional pruning passes will be required (because of PARAM_EXEC
* Params), we must also update the translation data that allows conversion
* of partition indexes into subplan indexes to account for the unneeded
* subplans having been removed.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*
* Must only be called once per 'prunestate', and only if initial pruning
* is required.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*
* 'nsubplans' must be passed as the total number of unpruned subplans.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*/
Bitmapset *
ExecFindInitialMatchingSubPlans(PartitionPruneState *prunestate, int nsubplans)
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
{
Bitmapset *result = NULL;
MemoryContext oldcontext;
int i;
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/* Caller error if we get here without do_initial_prune */
Assert(prunestate->do_initial_prune);
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/*
* Switch to a temp context to avoid leaking memory in the executor's
* query-lifespan memory context.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*/
oldcontext = MemoryContextSwitchTo(prunestate->prune_context);
/*
* For each hierarchy, do the pruning tests, and add nondeletable
* subplans' indexes to "result".
*/
for (i = 0; i < prunestate->num_partprunedata; i++)
{
PartitionPruningData *prunedata;
PartitionedRelPruningData *pprune;
prunedata = prunestate->partprunedata[i];
pprune = &prunedata->partrelprunedata[0];
/* Perform pruning without using PARAM_EXEC Params */
find_matching_subplans_recurse(prunedata, pprune, true, &result);
/* Expression eval may have used space in node's ps_ExprContext too */
Restructure creation of run-time pruning steps. Previously, gen_partprune_steps() always built executor pruning steps using all suitable clauses, including those containing PARAM_EXEC Params. This meant that the pruning steps were only completely safe for executor run-time (scan start) pruning. To prune at executor startup, we had to ignore the steps involving exec Params. But this doesn't really work in general, since there may be logic changes needed as well --- for example, pruning according to the last operator's btree strategy is the wrong thing if we're not applying that operator. The rules embodied in gen_partprune_steps() and its minions are sufficiently complicated that tracking their incremental effects in other logic seems quite impractical. Short of a complete redesign, the only safe fix seems to be to run gen_partprune_steps() twice, once to create executor startup pruning steps and then again for run-time pruning steps. We can save a few cycles however by noting during the first scan whether we rejected any clauses because they involved exec Params --- if not, we don't need to do the second scan. In support of this, refactor the internal APIs in partprune.c to make more use of passing information in the GeneratePruningStepsContext struct, rather than as separate arguments. This is, I hope, the last piece of our response to a bug report from Alan Jackson. Back-patch to v11 where this code came in. Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
7 years ago
if (pprune->initial_pruning_steps)
ResetExprContext(pprune->initial_context.planstate->ps_ExprContext);
}
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/* Add in any subplans that partition pruning didn't account for */
result = bms_add_members(result, prunestate->other_subplans);
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
MemoryContextSwitchTo(oldcontext);
/* Copy result out of the temp context before we reset it */
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
result = bms_copy(result);
MemoryContextReset(prunestate->prune_context);
/*
* If exec-time pruning is required and we pruned subplans above, then we
* must re-sequence the subplan indexes so that ExecFindMatchingSubPlans
* properly returns the indexes from the subplans which will remain after
* execution of this function.
*
* We can safely skip this when !do_exec_prune, even though that leaves
* invalid data in prunestate, because that data won't be consulted again
* (cf initial Assert in ExecFindMatchingSubPlans).
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*/
if (prunestate->do_exec_prune && bms_num_members(result) < nsubplans)
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
{
int *new_subplan_indexes;
Bitmapset *new_other_subplans;
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
int i;
int newidx;
/*
* First we must build a temporary array which maps old subplan
* indexes to new ones. For convenience of initialization, we use
* 1-based indexes in this array and leave pruned items as 0.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*/
new_subplan_indexes = (int *) palloc0(sizeof(int) * nsubplans);
newidx = 1;
i = -1;
while ((i = bms_next_member(result, i)) >= 0)
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
{
Assert(i < nsubplans);
new_subplan_indexes[i] = newidx++;
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
}
/*
* Now we can update each PartitionedRelPruneInfo's subplan_map with
* new subplan indexes. We must also recompute its present_parts
* bitmap.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*/
for (i = 0; i < prunestate->num_partprunedata; i++)
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
{
PartitionPruningData *prunedata = prunestate->partprunedata[i];
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
int j;
/*
* Within each hierarchy, we perform this loop in back-to-front
* order so that we determine present_parts for the lowest-level
* partitioned tables first. This way we can tell whether a
* sub-partitioned table's partitions were entirely pruned so we
* can exclude it from the current level's present_parts.
*/
for (j = prunedata->num_partrelprunedata - 1; j >= 0; j--)
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
{
PartitionedRelPruningData *pprune = &prunedata->partrelprunedata[j];
Restructure creation of run-time pruning steps. Previously, gen_partprune_steps() always built executor pruning steps using all suitable clauses, including those containing PARAM_EXEC Params. This meant that the pruning steps were only completely safe for executor run-time (scan start) pruning. To prune at executor startup, we had to ignore the steps involving exec Params. But this doesn't really work in general, since there may be logic changes needed as well --- for example, pruning according to the last operator's btree strategy is the wrong thing if we're not applying that operator. The rules embodied in gen_partprune_steps() and its minions are sufficiently complicated that tracking their incremental effects in other logic seems quite impractical. Short of a complete redesign, the only safe fix seems to be to run gen_partprune_steps() twice, once to create executor startup pruning steps and then again for run-time pruning steps. We can save a few cycles however by noting during the first scan whether we rejected any clauses because they involved exec Params --- if not, we don't need to do the second scan. In support of this, refactor the internal APIs in partprune.c to make more use of passing information in the GeneratePruningStepsContext struct, rather than as separate arguments. This is, I hope, the last piece of our response to a bug report from Alan Jackson. Back-patch to v11 where this code came in. Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
7 years ago
int nparts = pprune->nparts;
int k;
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/* We just rebuild present_parts from scratch */
bms_free(pprune->present_parts);
pprune->present_parts = NULL;
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
for (k = 0; k < nparts; k++)
{
int oldidx = pprune->subplan_map[k];
int subidx;
/*
* If this partition existed as a subplan then change the
* old subplan index to the new subplan index. The new
* index may become -1 if the partition was pruned above,
* or it may just come earlier in the subplan list due to
* some subplans being removed earlier in the list. If
* it's a subpartition, add it to present_parts unless
* it's entirely pruned.
*/
if (oldidx >= 0)
{
Assert(oldidx < nsubplans);
pprune->subplan_map[k] = new_subplan_indexes[oldidx] - 1;
if (new_subplan_indexes[oldidx] > 0)
pprune->present_parts =
bms_add_member(pprune->present_parts, k);
}
else if ((subidx = pprune->subpart_map[k]) >= 0)
{
PartitionedRelPruningData *subprune;
subprune = &prunedata->partrelprunedata[subidx];
if (!bms_is_empty(subprune->present_parts))
pprune->present_parts =
bms_add_member(pprune->present_parts, k);
}
}
}
}
/*
* We must also recompute the other_subplans set, since indexes in it
* may change.
*/
new_other_subplans = NULL;
i = -1;
while ((i = bms_next_member(prunestate->other_subplans, i)) >= 0)
new_other_subplans = bms_add_member(new_other_subplans,
new_subplan_indexes[i] - 1);
bms_free(prunestate->other_subplans);
prunestate->other_subplans = new_other_subplans;
pfree(new_subplan_indexes);
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
}
return result;
}
/*
* ExecFindMatchingSubPlans
* Determine which subplans match the pruning steps detailed in
* 'prunestate' for the current comparison expression values.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*
* Here we assume we may evaluate PARAM_EXEC Params.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*/
Bitmapset *
ExecFindMatchingSubPlans(PartitionPruneState *prunestate)
{
Bitmapset *result = NULL;
MemoryContext oldcontext;
int i;
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/*
* If !do_exec_prune, we've got problems because
* ExecFindInitialMatchingSubPlans will not have bothered to update
* prunestate for whatever pruning it did.
*/
Assert(prunestate->do_exec_prune);
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/*
* Switch to a temp context to avoid leaking memory in the executor's
* query-lifespan memory context.
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*/
oldcontext = MemoryContextSwitchTo(prunestate->prune_context);
/*
* For each hierarchy, do the pruning tests, and add nondeletable
* subplans' indexes to "result".
*/
for (i = 0; i < prunestate->num_partprunedata; i++)
{
PartitionPruningData *prunedata;
PartitionedRelPruningData *pprune;
prunedata = prunestate->partprunedata[i];
pprune = &prunedata->partrelprunedata[0];
find_matching_subplans_recurse(prunedata, pprune, false, &result);
/* Expression eval may have used space in node's ps_ExprContext too */
Restructure creation of run-time pruning steps. Previously, gen_partprune_steps() always built executor pruning steps using all suitable clauses, including those containing PARAM_EXEC Params. This meant that the pruning steps were only completely safe for executor run-time (scan start) pruning. To prune at executor startup, we had to ignore the steps involving exec Params. But this doesn't really work in general, since there may be logic changes needed as well --- for example, pruning according to the last operator's btree strategy is the wrong thing if we're not applying that operator. The rules embodied in gen_partprune_steps() and its minions are sufficiently complicated that tracking their incremental effects in other logic seems quite impractical. Short of a complete redesign, the only safe fix seems to be to run gen_partprune_steps() twice, once to create executor startup pruning steps and then again for run-time pruning steps. We can save a few cycles however by noting during the first scan whether we rejected any clauses because they involved exec Params --- if not, we don't need to do the second scan. In support of this, refactor the internal APIs in partprune.c to make more use of passing information in the GeneratePruningStepsContext struct, rather than as separate arguments. This is, I hope, the last piece of our response to a bug report from Alan Jackson. Back-patch to v11 where this code came in. Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
7 years ago
if (pprune->exec_pruning_steps)
ResetExprContext(pprune->exec_context.planstate->ps_ExprContext);
}
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/* Add in any subplans that partition pruning didn't account for */
result = bms_add_members(result, prunestate->other_subplans);
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
MemoryContextSwitchTo(oldcontext);
/* Copy result out of the temp context before we reset it */
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
result = bms_copy(result);
MemoryContextReset(prunestate->prune_context);
return result;
}
/*
* find_matching_subplans_recurse
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
* Recursive worker function for ExecFindMatchingSubPlans and
* ExecFindInitialMatchingSubPlans
*
* Adds valid (non-prunable) subplan IDs to *validsubplans
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*/
static void
find_matching_subplans_recurse(PartitionPruningData *prunedata,
PartitionedRelPruningData *pprune,
bool initial_prune,
Bitmapset **validsubplans)
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
{
Bitmapset *partset;
int i;
/* Guard against stack overflow due to overly deep partition hierarchy. */
check_stack_depth();
/* Only prune if pruning would be useful at this level. */
Restructure creation of run-time pruning steps. Previously, gen_partprune_steps() always built executor pruning steps using all suitable clauses, including those containing PARAM_EXEC Params. This meant that the pruning steps were only completely safe for executor run-time (scan start) pruning. To prune at executor startup, we had to ignore the steps involving exec Params. But this doesn't really work in general, since there may be logic changes needed as well --- for example, pruning according to the last operator's btree strategy is the wrong thing if we're not applying that operator. The rules embodied in gen_partprune_steps() and its minions are sufficiently complicated that tracking their incremental effects in other logic seems quite impractical. Short of a complete redesign, the only safe fix seems to be to run gen_partprune_steps() twice, once to create executor startup pruning steps and then again for run-time pruning steps. We can save a few cycles however by noting during the first scan whether we rejected any clauses because they involved exec Params --- if not, we don't need to do the second scan. In support of this, refactor the internal APIs in partprune.c to make more use of passing information in the GeneratePruningStepsContext struct, rather than as separate arguments. This is, I hope, the last piece of our response to a bug report from Alan Jackson. Back-patch to v11 where this code came in. Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
7 years ago
if (initial_prune && pprune->initial_pruning_steps)
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
{
Restructure creation of run-time pruning steps. Previously, gen_partprune_steps() always built executor pruning steps using all suitable clauses, including those containing PARAM_EXEC Params. This meant that the pruning steps were only completely safe for executor run-time (scan start) pruning. To prune at executor startup, we had to ignore the steps involving exec Params. But this doesn't really work in general, since there may be logic changes needed as well --- for example, pruning according to the last operator's btree strategy is the wrong thing if we're not applying that operator. The rules embodied in gen_partprune_steps() and its minions are sufficiently complicated that tracking their incremental effects in other logic seems quite impractical. Short of a complete redesign, the only safe fix seems to be to run gen_partprune_steps() twice, once to create executor startup pruning steps and then again for run-time pruning steps. We can save a few cycles however by noting during the first scan whether we rejected any clauses because they involved exec Params --- if not, we don't need to do the second scan. In support of this, refactor the internal APIs in partprune.c to make more use of passing information in the GeneratePruningStepsContext struct, rather than as separate arguments. This is, I hope, the last piece of our response to a bug report from Alan Jackson. Back-patch to v11 where this code came in. Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
7 years ago
partset = get_matching_partitions(&pprune->initial_context,
pprune->initial_pruning_steps);
}
else if (!initial_prune && pprune->exec_pruning_steps)
{
partset = get_matching_partitions(&pprune->exec_context,
pprune->exec_pruning_steps);
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
}
else
{
/*
* If no pruning is to be done, just include all partitions at this
* level.
*/
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
partset = pprune->present_parts;
}
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
/* Translate partset into subplan indexes */
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
i = -1;
while ((i = bms_next_member(partset, i)) >= 0)
{
if (pprune->subplan_map[i] >= 0)
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
*validsubplans = bms_add_member(*validsubplans,
pprune->subplan_map[i]);
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
else
{
int partidx = pprune->subpart_map[i];
if (partidx >= 0)
find_matching_subplans_recurse(prunedata,
&prunedata->partrelprunedata[partidx],
initial_prune, validsubplans);
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
else
{
/*
* We get here if the planner already pruned all the sub-
* partitions for this partition. Silently ignore this
* partition in this case. The end result is the same: we
* would have pruned all partitions just the same, but we
* don't have any pruning steps to execute to verify this.
*/
Support partition pruning at execution time Existing partition pruning is only able to work at plan time, for query quals that appear in the parsed query. This is good but limiting, as there can be parameters that appear later that can be usefully used to further prune partitions. This commit adds support for pruning subnodes of Append which cannot possibly contain any matching tuples, during execution, by evaluating Params to determine the minimum set of subnodes that can possibly match. We support more than just simple Params in WHERE clauses. Support additionally includes: 1. Parameterized Nested Loop Joins: The parameter from the outer side of the join can be used to determine the minimum set of inner side partitions to scan. 2. Initplans: Once an initplan has been executed we can then determine which partitions match the value from the initplan. Partition pruning is performed in two ways. When Params external to the plan are found to match the partition key we attempt to prune away unneeded Append subplans during the initialization of the executor. This allows us to bypass the initialization of non-matching subplans meaning they won't appear in the EXPLAIN or EXPLAIN ANALYZE output. For parameters whose value is only known during the actual execution then the pruning of these subplans must wait. Subplans which are eliminated during this stage of pruning are still visible in the EXPLAIN output. In order to determine if pruning has actually taken place, the EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never executed due to the elimination of the partition then the execution timing area will state "(never executed)". Whereas, if, for example in the case of parameterized nested loops, the number of loops stated in the EXPLAIN ANALYZE output for certain subplans may appear lower than others due to the subplan having been scanned fewer times. This is due to the list of matching subnodes having to be evaluated whenever a parameter which was found to match the partition key changes. This commit required some additional infrastructure that permits the building of a data structure which is able to perform the translation of the matching partition IDs, as returned by get_matching_partitions, into the list index of a subpaths list, as exist in node types such as Append, MergeAppend and ModifyTable. This allows us to translate a list of clauses into a Bitmapset of all the subpath indexes which must be included to satisfy the clause list. Author: David Rowley, based on an earlier effort by Beena Emerson Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi, Jesper Pedersen Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
8 years ago
}
}
}
}