473 Commits (e6ccd1ce1644d1b40b7981f8bc172394de524f99)

Author	SHA1	Message	Date
Etsuro Fujita	a363bc6da9	Fix EXPLAIN ANALYZE for async-capable nodes. ... EXPLAIN ANALYZE for an async-capable ForeignScan node associated with postgres_fdw is done just by using instrumentation for ExecProcNode() called from the node's callbacks, causing the following problems: 1) If the remote table to scan is empty, the node is incorrectly considered as "never executed" by the command even if the node is executed, as ExecProcNode() isn't called from the node's callbacks at all in that case. 2) The command fails to collect timings for things other than ExecProcNode() done in the node, such as creating a cursor for the node's remote query. To fix these problems, add instrumentation for async-capable nodes, and modify postgres_fdw accordingly. My oversight in commit 27e1f1456. While at it, update a comment for the AsyncRequest struct in execnodes.h and the documentation for the ForeignAsyncRequest API in fdwhandler.sgml to match the code in ExecAsyncAppendResponse() in nodeAppend.c, and fix typos in comments in nodeAppend.c. Per report from Andrey Lepikhov, though I didn't use his patch. Reviewed-by: Andrey Lepikhov Discussion: https://postgr.es/m/2eb662bb-105d-fc20-7412-2f027cc3ca72%40postgrespro.ru	5 years ago
Tom Lane	a1115fa078	Postpone some more stuff out of ExecInitModifyTable. ... Delay creation of the projections for INSERT and UPDATE tuples until they're needed. This saves a pretty fair amount of work when only some of the partitions are actually touched. The logic associated with identifying junk columns in UPDATE/DELETE is moved to another loop, allowing removal of one loop over the target relations; but it didn't actually change at all. 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
Tom Lane	c5b7ba4e67	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
David Rowley	9eacee2e62	Add Result Cache executor node (take 2) ... Here we add a new executor node type named "Result Cache". The planner can include this node type in the plan to have the executor cache the results from the inner side of parameterized nested loop joins. This allows caching of tuples for sets of parameters so that in the event that the node sees the same parameter values again, it can just return the cached tuples instead of rescanning the inner side of the join all over again. Internally, result cache uses a hash table in order to quickly find tuples that have been previously cached. For certain data sets, this can significantly improve the performance of joins. The best cases for using this new node type are for join problems where a large portion of the tuples from the inner side of the join have no join partner on the outer side of the join. In such cases, hash join would have to hash values that are never looked up, thus bloating the hash table and possibly causing it to multi-batch. Merge joins would have to skip over all of the unmatched rows. If we use a nested loop join with a result cache, then we only cache tuples that have at least one join partner on the outer side of the join. The benefits of using a parameterized nested loop with a result cache increase when there are fewer distinct values being looked up and the number of lookups of each value is large. Also, hash probes to lookup the cache can be much faster than the hash probe in a hash join as it's common that the result cache's hash table is much smaller than the hash join's due to result cache only caching useful tuples rather than all tuples from the inner side of the join. This variation in hash probe performance is more significant when the hash join's hash table no longer fits into the CPU's L3 cache, but the result cache's hash table does. The apparent "random" access of hash buckets with each hash probe can cause a poor L3 cache hit ratio for large hash tables. Smaller hash tables generally perform better. The hash table used for the cache limits itself to not exceeding work_mem * hash_mem_multiplier in size. We maintain a dlist of keys for this cache and when we're adding new tuples and realize we've exceeded the memory budget, we evict cache entries starting with the least recently used ones until we have enough memory to add the new tuples to the cache. For parameterized nested loop joins, we now consider using one of these result cache nodes in between the nested loop node and its inner node. We determine when this might be useful based on cost, which is primarily driven off of what the expected cache hit ratio will be. Estimating the cache hit ratio relies on having good distinct estimates on the nested loop's parameters. For now, the planner will only consider using a result cache for parameterized nested loop joins. This works for both normal joins and also for LATERAL type joins to subqueries. It is possible to use this new node for other uses in the future. For example, to cache results from correlated subqueries. However, that's not done here due to some difficulties obtaining a distinct estimation on the outer plan to calculate the estimated cache hit ratio. Currently we plan the inner plan before planning the outer plan so there is no good way to know if a result cache would be useful or not since we can't estimate the number of times the subplan will be called until the outer plan is generated. The functionality being added here is newly introducing a dependency on the return value of estimate_num_groups() during the join search. Previously, during the join search, we only ever needed to perform selectivity estimations. With this commit, we need to use estimate_num_groups() in order to estimate what the hit ratio on the result cache will be. In simple terms, if we expect 10 distinct values and we expect 1000 outer rows, then we'll estimate the hit ratio to be 99%. Since cache hits are very cheap compared to scanning the underlying nodes on the inner side of the nested loop join, then this will significantly reduce the planner's cost for the join. However, it's fairly easy to see here that things will go bad when estimate_num_groups() incorrectly returns a value that's significantly lower than the actual number of distinct values. If this happens then that may cause us to make use of a nested loop join with a result cache instead of some other join type, such as a merge or hash join. Our distinct estimations have been known to be a source of trouble in the past, so the extra reliance on them here could cause the planner to choose slower plans than it did previous to having this feature. Distinct estimations are also fairly hard to estimate accurately when several tables have been joined already or when a WHERE clause filters out a set of values that are correlated to the expressions we're estimating the number of distinct value for. For now, the costing we perform during query planning for result caches does put quite a bit of faith in the distinct estimations being accurate. When these are accurate then we should generally see faster execution times for plans containing a result cache. However, in the real world, we may find that we need to either change the costings to put less trust in the distinct estimations being accurate or perhaps even disable this feature by default. There's always an element of risk when we teach the query planner to do new tricks that it decides to use that new trick at the wrong time and causes a regression. Users may opt to get the old behavior by turning the feature off using the enable_resultcache GUC. Currently, this is enabled by default. It remains to be seen if we'll maintain that setting for the release. Additionally, the name "Result Cache" is the best name I could think of for this new node at the time I started writing the patch. Nobody seems to strongly dislike the name. A few people did suggest other names but no other name seemed to dominate in the brief discussion that there was about names. Let's allow the beta period to see if the current name pleases enough people. If there's some consensus on a better name, then we can change it before the release. Please see the 2nd discussion link below for the discussion on the "Result Cache" name. Author: David Rowley Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu, Hou Zhijie Tested-By: Konstantin Knizhnik Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com	5 years ago
David Rowley	28b3e3905c	Revert b6002a796 ... This removes "Add Result Cache executor node". It seems that something weird is going on with the tracking of cache hits and misses as highlighted by many buildfarm animals. It's not yet clear what the problem is as other parts of the plan indicate that the cache did work correctly, it's just the hits and misses that were being reported as 0. This is especially a bad time to have the buildfarm so broken, so reverting before too many more animals go red. Discussion: https://postgr.es/m/CAApHDvq_hydhfovm4=izgWs+C5HqEeRScjMbOgbpC-jRAeK3Yw@mail.gmail.com	5 years ago
David Rowley	b6002a796d	Add Result Cache executor node ... Here we add a new executor node type named "Result Cache". The planner can include this node type in the plan to have the executor cache the results from the inner side of parameterized nested loop joins. This allows caching of tuples for sets of parameters so that in the event that the node sees the same parameter values again, it can just return the cached tuples instead of rescanning the inner side of the join all over again. Internally, result cache uses a hash table in order to quickly find tuples that have been previously cached. For certain data sets, this can significantly improve the performance of joins. The best cases for using this new node type are for join problems where a large portion of the tuples from the inner side of the join have no join partner on the outer side of the join. In such cases, hash join would have to hash values that are never looked up, thus bloating the hash table and possibly causing it to multi-batch. Merge joins would have to skip over all of the unmatched rows. If we use a nested loop join with a result cache, then we only cache tuples that have at least one join partner on the outer side of the join. The benefits of using a parameterized nested loop with a result cache increase when there are fewer distinct values being looked up and the number of lookups of each value is large. Also, hash probes to lookup the cache can be much faster than the hash probe in a hash join as it's common that the result cache's hash table is much smaller than the hash join's due to result cache only caching useful tuples rather than all tuples from the inner side of the join. This variation in hash probe performance is more significant when the hash join's hash table no longer fits into the CPU's L3 cache, but the result cache's hash table does. The apparent "random" access of hash buckets with each hash probe can cause a poor L3 cache hit ratio for large hash tables. Smaller hash tables generally perform better. The hash table used for the cache limits itself to not exceeding work_mem * hash_mem_multiplier in size. We maintain a dlist of keys for this cache and when we're adding new tuples and realize we've exceeded the memory budget, we evict cache entries starting with the least recently used ones until we have enough memory to add the new tuples to the cache. For parameterized nested loop joins, we now consider using one of these result cache nodes in between the nested loop node and its inner node. We determine when this might be useful based on cost, which is primarily driven off of what the expected cache hit ratio will be. Estimating the cache hit ratio relies on having good distinct estimates on the nested loop's parameters. For now, the planner will only consider using a result cache for parameterized nested loop joins. This works for both normal joins and also for LATERAL type joins to subqueries. It is possible to use this new node for other uses in the future. For example, to cache results from correlated subqueries. However, that's not done here due to some difficulties obtaining a distinct estimation on the outer plan to calculate the estimated cache hit ratio. Currently we plan the inner plan before planning the outer plan so there is no good way to know if a result cache would be useful or not since we can't estimate the number of times the subplan will be called until the outer plan is generated. The functionality being added here is newly introducing a dependency on the return value of estimate_num_groups() during the join search. Previously, during the join search, we only ever needed to perform selectivity estimations. With this commit, we need to use estimate_num_groups() in order to estimate what the hit ratio on the result cache will be. In simple terms, if we expect 10 distinct values and we expect 1000 outer rows, then we'll estimate the hit ratio to be 99%. Since cache hits are very cheap compared to scanning the underlying nodes on the inner side of the nested loop join, then this will significantly reduce the planner's cost for the join. However, it's fairly easy to see here that things will go bad when estimate_num_groups() incorrectly returns a value that's significantly lower than the actual number of distinct values. If this happens then that may cause us to make use of a nested loop join with a result cache instead of some other join type, such as a merge or hash join. Our distinct estimations have been known to be a source of trouble in the past, so the extra reliance on them here could cause the planner to choose slower plans than it did previous to having this feature. Distinct estimations are also fairly hard to estimate accurately when several tables have been joined already or when a WHERE clause filters out a set of values that are correlated to the expressions we're estimating the number of distinct value for. For now, the costing we perform during query planning for result caches does put quite a bit of faith in the distinct estimations being accurate. When these are accurate then we should generally see faster execution times for plans containing a result cache. However, in the real world, we may find that we need to either change the costings to put less trust in the distinct estimations being accurate or perhaps even disable this feature by default. There's always an element of risk when we teach the query planner to do new tricks that it decides to use that new trick at the wrong time and causes a regression. Users may opt to get the old behavior by turning the feature off using the enable_resultcache GUC. Currently, this is enabled by default. It remains to be seen if we'll maintain that setting for the release. Additionally, the name "Result Cache" is the best name I could think of for this new node at the time I started writing the patch. Nobody seems to strongly dislike the name. A few people did suggest other names but no other name seemed to dominate in the brief discussion that there was about names. Let's allow the beta period to see if the current name pleases enough people. If there's some consensus on a better name, then we can change it before the release. Please see the 2nd discussion link below for the discussion on the "Result Cache" name. Author: David Rowley Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu Tested-By: Konstantin Knizhnik Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com	5 years ago
Tom Lane	86dc90056d	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
Etsuro Fujita	27e1f14563	Add support for asynchronous execution. ... This implements asynchronous execution, which runs multiple parts of a non-parallel-aware Append concurrently rather than serially to improve performance when possible. Currently, the only node type that can be run concurrently is a ForeignScan that is an immediate child of such an Append. In the case where such ForeignScans access data on different remote servers, this would run those ForeignScans concurrently, and overlap the remote operations to be performed simultaneously, so it'll improve the performance especially when the operations involve time-consuming ones such as remote join and remote aggregation. We may extend this to other node types such as joins or aggregates over ForeignScans in the future. This also adds the support for postgres_fdw, which is enabled by the table-level/server-level option "async_capable". The default is false. Robert Haas, Kyotaro Horiguchi, Thomas Munro, and myself. This commit is mostly based on the patch proposed by Robert Haas, but also uses stuff from the patch proposed by Kyotaro Horiguchi and from the patch proposed by Thomas Munro. Reviewed by Kyotaro Horiguchi, Konstantin Knizhnik, Andrey Lepikhov, Movead Li, Thomas Munro, Justin Pryzby, and others. Discussion: https://postgr.es/m/CA%2BTgmoaXQEt4tZ03FtQhnzeDEMzBck%2BLrni0UWHVVgOTnA6C1w%40mail.gmail.com Discussion: https://postgr.es/m/CA%2BhUKGLBRyu0rHrDCMC4%3DRn3252gogyp1SjOgG8SEKKZv%3DFwfQ%40mail.gmail.com Discussion: https://postgr.es/m/20200228.170650.667613673625155850.horikyota.ntt%40gmail.com	5 years ago
David Rowley	bb437f995d	Add TID Range Scans to support efficient scanning ranges of TIDs ... This adds a new executor node named TID Range Scan. The query planner will generate paths for TID Range scans when quals are discovered on base relations which search for ranges on the table's ctid column. These ranges may be open at either end. For example, WHERE ctid >= '(10,0)'; will return all tuples on page 10 and over. To support this, two new optional callback functions have been added to table AM. scan_set_tidrange is used to set the scan range to just the given range of TIDs. scan_getnextslot_tidrange fetches the next tuple in the given range. For AMs were scanning ranges of TIDs would not make sense, these functions can be set to NULL in the TableAmRoutine. The query planner won't generate TID Range Scan Paths in that case. Author: Edmund Horner, David Rowley Reviewed-by: David Rowley, Tomas Vondra, Tom Lane, Andres Freund, Zhihong Yu Discussion: https://postgr.es/m/CAMyN-kB-nFTkF=VA_JPwFNo08S0d-Yk0F741S2B7LDmYAi8eyA@mail.gmail.com	5 years ago
Heikki Linnakangas	54e51dcde0	Make ExecGetInsertedCols() and friends more robust and improve comments. ... If ExecGetInsertedCols(), ExecGetUpdatedCols() or ExecGetExtraUpdatedCols() were called with a ResultRelInfo that's not in the range table and isn't a partition routing target, the functions would dereference a NULL pointer, relinfo->ri_RootResultRelInfo. Such ResultRelInfos are created when firing RI triggers in tables that are not modified directly. None of the current callers of these functions pass such relations, so this isn't a live bug, but let's make them more robust. Also update comment in ResultRelInfo; after commit 6214e2b228, ri_RangeTableIndex is zero for ResultRelInfos created for partition tuple routing. Noted by Coverity. Backpatch down to v11, like commit 6214e2b228. Reviewed-by: Tom Lane, Amit Langote	5 years ago
Heikki Linnakangas	6214e2b228	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
Tomas Vondra	b663a41363	Implement support for bulk inserts in postgres_fdw ... Extends the FDW API to allow batching inserts into foreign tables. That is usually much more efficient than inserting individual rows, due to high latency for each round-trip to the foreign server. It was possible to implement something similar in the regular FDW API, but it was inconvenient and there were issues with reporting the number of actually inserted rows etc. This extends the FDW API with two new functions: * GetForeignModifyBatchSize - allows the FDW picking optimal batch size * ExecForeignBatchInsert - inserts a batch of rows at once Currently, only INSERT queries support batching. Support for DELETE and UPDATE may be added in the future. This also implements batching for postgres_fdw. The batch size may be specified using "batch_size" option both at the server and table level. The initial patch version was written by me, but it was rewritten and improved in many ways by Takayuki Tsunakawa. Author: Takayuki Tsunakawa Reviewed-by: Tomas Vondra, Amit Langote Discussion: https://postgr.es/m/20200628151002.7x5laxwpgvkyiu3q@development	5 years ago
Bruce Momjian	ca3b37487b	Update copyright for 2021 ... Backpatch-through: 9.5	5 years ago
Heikki Linnakangas	0a2bc5d61e	Move per-agg and per-trans duplicate finding to the planner. ... This has the advantage that the cost estimates for aggregates can count the number of calls to transition and final functions correctly. Bump catalog version, because views can contain Aggrefs. Reviewed-by: Andres Freund Discussion: https://www.postgresql.org/message-id/b2e3536b-1dbc-8303-c97e-89cb0b4a9a48%40iki.fi	5 years ago
Heikki Linnakangas	68b1a4877e	Fix a few comments that referred to copy.c. ... Missed these in the previous commit.	5 years ago
Heikki Linnakangas	fb5883da86	Remove PartitionRoutingInfo struct. ... The extra indirection neeeded to access its members via its enclosing ResultRelInfo seems pointless. Move all the fields from PartitionRoutingInfo to ResultRelInfo. Author: Amit Langote Reviewed-by: Alvaro Herrera Discussion: https://www.postgresql.org/message-id/CA%2BHiwqFViT47Zbr_ASBejiK7iDG8%3DQ1swQ-tjM6caRPQ67pT%3Dw%40mail.gmail.com	5 years ago
Heikki Linnakangas	6973533650	Revise child-to-root tuple conversion map management. ... Store the tuple conversion map to convert a tuple from a child table's format to the root format in a new ri_ChildToRootMap field in ResultRelInfo. It is initialized if transition tuple capture for FOR STATEMENT triggers or INSERT tuple routing on a partitioned table is needed. Previously, ModifyTable kept the maps in the per-subplan ModifyTableState->mt_per_subplan_tupconv_maps array, or when tuple routing was used, in ResultRelInfo->ri_Partitioninfo->pi_PartitionToRootMap. The new field replaces both of those. Now that the child-to-root tuple conversion map is always available in ResultRelInfo (when needed), remove the TransitionCaptureState.tcs_map field. The callers of Exec*Trigger() functions no longer need to set or save it, which is much less confusing and bug-prone. Also, as a future optimization, this will allow us to delay creating the map for a given result relation until the relation is actually processed during execution. Author: Amit Langote Discussion: https://www.postgresql.org/message-id/CA%2BHiwqHtCWLdK-LO%3DNEsvOdHx%2B7yv4mE_zYK0i3BH7dXb-wxog%40mail.gmail.com	5 years ago
Heikki Linnakangas	f49b85d783	Clean up code to resolve the "root target relation" in nodeModifyTable.c ... When executing DDL on a partitioned table or on a table with inheritance children, statement-level triggers must be fired against the table given in the original statement. The code to look that up was a bit messy and duplicative. Commit 501ed02cf6 added a helper function, getASTriggerResultRelInfo() (later renamed to getTargetResultRelInfo()) for it, but for some reason it was only used when firing AFTER STATEMENT triggers and the code to fire BEFORE STATEMENT triggers duplicated the logic. Determine the target relation in ExecInitModifyTable(), and set it always in ModifyTableState. Code that used to call getTargetResultRelInfo() can now use ModifyTableState->rootResultRelInfo directly. Discussion: https://www.postgresql.org/message-id/CA%2BHiwqFViT47Zbr_ASBejiK7iDG8%3DQ1swQ-tjM6caRPQ67pT%3Dw%40mail.gmail.com	5 years ago
Heikki Linnakangas	a04daa97a4	Remove es_result_relation_info from EState. ... Maintaining 'es_result_relation_info' correctly at all times has become cumbersome, especially with partitioning where each partition gets its own result relation info. Having to set and reset it across arbitrary operations has caused bugs in the past. This changes all the places that used 'es_result_relation_info', to receive the currently active ResultRelInfo via function parameters instead. Author: Amit Langote Discussion: https://www.postgresql.org/message-id/CA%2BHiwqGEmiib8FLiHMhKB%2BCH5dRgHSLc5N5wnvc4kym%2BZYpQEQ%40mail.gmail.com	5 years ago
Heikki Linnakangas	178f2d560d	Include result relation info in direct modify ForeignScan nodes. ... FDWs that can perform an UPDATE/DELETE remotely using the "direct modify" set of APIs need to access the ResultRelInfo of the target table. That's currently available in EState.es_result_relation_info, but the next commit will remove that field. This commit adds a new resultRelation field in ForeignScan, to store the target relation's RT index, and the corresponding ResultRelInfo in ForeignScanState. The FDW's PlanDirectModify callback is expected to set 'resultRelation' along with 'operation'. The core code doesn't need them for anything, they are for the convenience of FDW's Begin- and IterateDirectModify callbacks. Authors: Amit Langote, Etsuro Fujita Discussion: https://www.postgresql.org/message-id/CA%2BHiwqGEmiib8FLiHMhKB%2BCH5dRgHSLc5N5wnvc4kym%2BZYpQEQ%40mail.gmail.com	5 years ago
Heikki Linnakangas	1375422c78	Create ResultRelInfos later in InitPlan, index them by RT index. ... Instead of allocating all the ResultRelInfos upfront in one big array, allocate them in ExecInitModifyTable(). es_result_relations is now an array of ResultRelInfo pointers, rather than an array of structs, and it is indexed by the RT index. This simplifies things: we get rid of the separate concept of a "result rel index", and don't need to set it in setrefs.c anymore. This also allows follow-up optimizations (not included in this commit yet) to skip initializing ResultRelInfos for target relations that were not needed at runtime, and removal of the es_result_relation_info pointer. The EState arrays of regular result rels and root result rels are merged into one array. Similarly, the resultRelations and rootResultRelations lists in PlannedStmt are merged into one. It's not actually clear to me why they were kept separate in the first place, but now that the es_result_relations array is indexed by RT index, it certainly seems pointless. The PlannedStmt->resultRelations list is now only needed for ExecRelationIsTargetRelation(). One visible effect of this change is that ExecRelationIsTargetRelation() will now return 'true' also for the partition root, if a partitioned table is updated. That seems like a good thing, although the function isn't used in core code, and I don't see any reason for an FDW to call it on a partition root. Author: Amit Langote Discussion: https://www.postgresql.org/message-id/CA%2BHiwqGEmiib8FLiHMhKB%2BCH5dRgHSLc5N5wnvc4kym%2BZYpQEQ%40mail.gmail.com	5 years ago
Tom Lane	41efb83408	Move resolution of AlternativeSubPlan choices to the planner. ... When commit bd3daddaf introduced AlternativeSubPlans, I had some ambitions towards allowing the choice of subplan to change during execution. That has not happened, or even been thought about, in the ensuing twelve years; so it seems like a failed experiment. So let's rip that out and resolve the choice of subplan at the end of planning (in setrefs.c) rather than during executor startup. This has a number of positive benefits: * Removal of a few hundred lines of executor code, since AlternativeSubPlans need no longer be supported there. * Removal of executor-startup overhead (particularly, initialization of subplans that won't be used). * Removal of incidental costs of having a larger plan tree, such as tree-scanning and copying costs in the plancache; not to mention setrefs.c's own costs of processing the discarded subplans. * EXPLAIN no longer has to print a weird (and undocumented) representation of an AlternativeSubPlan choice; it sees only the subplan actually used. This should mean less confusion for users. * Since setrefs.c knows which subexpression of a plan node it's working on at any instant, it's possible to adjust the estimated number of executions of the subplan based on that. For example, we should usually estimate more executions of a qual expression than a targetlist expression. The implementation used here is pretty simplistic, because we don't want to expend a lot of cycles on the issue; but it's better than ignoring the point entirely, as the executor had to. That last point might possibly result in shifting the choice between hashed and non-hashed EXISTS subplans in a few cases, but in general this patch isn't meant to change planner choices. Since we're doing the resolution so late, it's really impossible to change any plan choices outside the AlternativeSubPlan itself. Patch by me; thanks to David Rowley for review. Discussion: https://postgr.es/m/1992952.1592785225@sss.pgh.pa.us	5 years ago
Tom Lane	2000b6c10a	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
Tom Lane	1e7629d2c9	Be more careful about the shape of hashable subplan clauses. ... nodeSubplan.c expects that the testexpr for a hashable ANY SubPlan has the form of one or more OpExprs whose LHS is an expression of the outer query's, while the RHS is an expression over Params representing output columns of the subquery. However, the planner only went as far as verifying that the clauses were all binary OpExprs. This works 99.99% of the time, because the clauses have the right shape when emitted by the parser --- but it's possible for function inlining to break that, as reported by PegoraroF10. To fix, teach the planner to check that the LHS and RHS contain the right things, or more accurately don't contain the wrong things. Given that this has been broken for years without anyone noticing, it seems sufficient to just give up hashing when it happens, rather than go to the trouble of commuting the clauses back again (which wouldn't necessarily work anyway). While poking at that, I also noticed that nodeSubplan.c had a baked-in assumption that the number of hash clauses is identical to the number of subquery output columns. Again, that's fine as far as parser output goes, but it's not hard to break it via function inlining. There seems little reason for that assumption though --- AFAICS, the only thing it's buying us is not having to store the number of hash clauses explicitly. Adding code to the planner to reject such cases would take more code than getting nodeSubplan.c to cope, so I fixed it that way. This has been broken for as long as we've had hashable SubPlans, so back-patch to all supported branches. Discussion: https://postgr.es/m/1549209182255-0.post@n3.nabble.com	5 years ago
David Rowley	6ee3b5fb99	Use int64 instead of long in incremental sort code ... Windows 64bit has 4-byte long values which is not suitable for tracking disk space usage in the incremental sort code. Let's just make all these fields int64s. Author: James Coleman Discussion: https://postgr.es/m/CAApHDvpky%2BUhof8mryPf5i%3D6e6fib2dxHqBrhp0Qhu0NeBhLJw%40mail.gmail.com Backpatch-through: 13, where the incremental sort code was added	5 years ago
Jeff Davis	2302302236	HashAgg: before spilling tuples, set unneeded columns to NULL. ... This is a replacement for 4cad2534. Instead of projecting all tuples going into a HashAgg, only remove unnecessary attributes when actually spilling. This avoids the regression for the in-memory case. Discussion: https://postgr.es/m/a2fb7dfeb4f50aa0a123e42151ee3013933cb802.camel%40j-davis.com Backpatch-through: 13	6 years ago
Andres Freund	a9a4a7ad56	code: replace most remaining uses of 'master'. ... Author: Andres Freund Reviewed-By: David Steele Discussion: https://postgr.es/m/20200615182235.x7lch5n6kcjq4aue@alap3.anarazel.de	6 years ago
David Rowley	9bdb300ded	Fix EXPLAIN ANALYZE for parallel HashAgg plans ... Since 1f39bce02, HashAgg nodes have had the ability to spill to disk when memory consumption exceeds work_mem. That commit added new properties to EXPLAIN ANALYZE to show the maximum memory usage and disk usage, however, it didn't quite go as far as showing that information for parallel workers. Since workers may have experienced something very different from the main process, we should show this information per worker, as is done in Sort. Reviewed-by: Justin Pryzby Reviewed-by: Jeff Davis Discussion: https://postgr.es/m/CAApHDvpEKbfZa18mM1TD7qV6PG+w97pwCWq5tVD0dX7e11gRJw@mail.gmail.com Backpatch-through: 13, where the hashagg spilling code was added.	6 years ago
Tom Lane	5cbfce562f	Initial pgindent and pgperltidy run for v13. ... Includes some manual cleanup of places that pgindent messed up, most of which weren't per project style anyway. Notably, it seems some people didn't absorb the style rules of commit c9d297751, because there were a bunch of new occurrences of function calls with a newline just after the left paren, all with faulty expectations about how the rest of the call would get indented.	6 years ago
Tom Lane	969f9d0b4b	Make EXPLAIN report maximum hashtable usage across multiple rescans. ... Before discarding the old hash table in ExecReScanHashJoin, capture its statistics, ensuring that we report the maximum hashtable size across repeated rescans of the hash input relation. We can repurpose the existing code for reporting hashtable size in parallel workers to help with this, making the patch pretty small. This also ensures that if rescans happen within parallel workers, we get the correct maximums across all instances. Konstantin Knizhnik and Tom Lane, per diagnosis by Thomas Munro of a trouble report from Alvaro Herrera. Discussion: https://postgr.es/m/20200323165059.GA24950@alvherre.pgsql	6 years ago
Alvaro Herrera	357889eb17	Support FETCH FIRST WITH TIES ... WITH TIES is an option to the FETCH FIRST N ROWS clause (the SQL standard's spelling of LIMIT), where you additionally get rows that compare equal to the last of those N rows by the columns in the mandatory ORDER BY clause. There was a proposal by Andrew Gierth to implement this functionality in a more powerful way that would yield more features, but the other patch had not been finished at this time, so we decided to use this one for now in the spirit of incremental development. Author: Surafel Temesgen <surafel3000@gmail.com> Reviewed-by: Álvaro Herrera <alvherre@alvh.no-ip.org> Reviewed-by: Tomas Vondra <tomas.vondra@2ndquadrant.com> Discussion: https://postgr.es/m/CALAY4q9ky7rD_A4vf=FVQvCGngm3LOes-ky0J6euMrg=_Se+ag@mail.gmail.com Discussion: https://postgr.es/m/87o8wvz253.fsf@news-spur.riddles.org.uk	6 years ago
Tomas Vondra	d2d8a229bc	Implement Incremental Sort ... Incremental Sort is an optimized variant of multikey sort for cases when the input is already sorted by a prefix of the requested sort keys. For example when the relation is already sorted by (key1, key2) and we need to sort it by (key1, key2, key3) we can simply split the input rows into groups having equal values in (key1, key2), and only sort/compare the remaining column key3. This has a number of benefits: - Reduced memory consumption, because only a single group (determined by values in the sorted prefix) needs to be kept in memory. This may also eliminate the need to spill to disk. - Lower startup cost, because Incremental Sort produce results after each prefix group, which is beneficial for plans where startup cost matters (like for example queries with LIMIT clause). We consider both Sort and Incremental Sort, and decide based on costing. The implemented algorithm operates in two different modes: - Fetching a minimum number of tuples without check of equality on the prefix keys, and sorting on all columns when safe. - Fetching all tuples for a single prefix group and then sorting by comparing only the remaining (non-prefix) keys. We always start in the first mode, and employ a heuristic to switch into the second mode if we believe it's beneficial - the goal is to minimize the number of unnecessary comparions while keeping memory consumption below work_mem. This is a very old patch series. The idea was originally proposed by Alexander Korotkov back in 2013, and then revived in 2017. In 2018 the patch was taken over by James Coleman, who wrote and rewrote most of the current code. There were many reviewers/contributors since 2013 - I've done my best to pick the most active ones, and listed them in this commit message. Author: James Coleman, Alexander Korotkov Reviewed-by: Tomas Vondra, Andreas Karlsson, Marti Raudsepp, Peter Geoghegan, Robert Haas, Thomas Munro, Antonin Houska, Andres Freund, Alexander Kuzmenkov Discussion: https://postgr.es/m/CAPpHfdscOX5an71nHd8WSUH6GNOCf=V7wgDaTXdDd9=goN-gfA@mail.gmail.com Discussion: https://postgr.es/m/CAPpHfds1waRZ=NOmueYq0sx1ZSCnt+5QJvizT8ndT2=etZEeAQ@mail.gmail.com	6 years ago
Alexander Korotkov	911e702077	Implement operator class parameters ... PostgreSQL provides set of template index access methods, where opclasses have much freedom in the semantics of indexing. These index AMs are GiST, GIN, SP-GiST and BRIN. There opclasses define representation of keys, operations on them and supported search strategies. So, it's natural that opclasses may be faced some tradeoffs, which require user-side decision. This commit implements opclass parameters allowing users to set some values, which tell opclass how to index the particular dataset. This commit doesn't introduce new storage in system catalog. Instead it uses pg_attribute.attoptions, which is used for table column storage options but unused for index attributes. In order to evade changing signature of each opclass support function, we implement unified way to pass options to opclass support functions. Options are set to fn_expr as the constant bytea expression. It's possible due to the fact that opclass support functions are executed outside of expressions, so fn_expr is unused for them. This commit comes with some examples of opclass options usage. We parametrize signature length in GiST. That applies to multiple opclasses: tsvector_ops, gist__intbig_ops, gist_ltree_ops, gist__ltree_ops, gist_trgm_ops and gist_hstore_ops. Also we parametrize maximum number of integer ranges for gist__int_ops. However, the main future usage of this feature is expected to be json, where users would be able to specify which way to index particular json parts. Catversion is bumped. Discussion: https://postgr.es/m/d22c3a18-31c7-1879-fc11-4c1ce2f5e5af%40postgrespro.ru Author: Nikita Glukhov, revised by me Reviwed-by: Nikolay Shaplov, Robert Haas, Tom Lane, Tomas Vondra, Alvaro Herrera	6 years ago
Jeff Davis	1f39bce021	Disk-based Hash Aggregation. ... While performing hash aggregation, track memory usage when adding new groups to a hash table. If the memory usage exceeds work_mem, enter "spill mode". In spill mode, new groups are not created in the hash table(s), but existing groups continue to be advanced if input tuples match. Tuples that would cause a new group to be created are instead spilled to a logical tape to be processed later. The tuples are spilled in a partitioned fashion. When all tuples from the outer plan are processed (either by advancing the group or spilling the tuple), finalize and emit the groups from the hash table. Then, create new batches of work from the spilled partitions, and select one of the saved batches and process it (possibly spilling recursively). Author: Jeff Davis Reviewed-by: Tomas Vondra, Adam Lee, Justin Pryzby, Taylor Vesely, Melanie Plageman Discussion: https://postgr.es/m/507ac540ec7c20136364b5272acbcd4574aa76ef.camel@j-davis.com	6 years ago
Peter Eisentraut	c6679e4fca	Optimize update of tables with generated columns ... When updating a table row with generated columns, only recompute those generated columns whose base columns have changed in this update and keep the rest unchanged. This can result in a significant performance benefit. The required information was already kept in RangeTblEntry.extraUpdatedCols; we just have to make use of it. Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com> Discussion: https://www.postgresql.org/message-id/flat/b05e781a-fa16-6b52-6738-761181204567@2ndquadrant.com	6 years ago
Andres Freund	1fdb7f9789	expression eval: Don't redundantly keep track of AggState. ... It's already tracked via ExprState->parent, so we don't need to also include it in ExprEvalStep. When that code originally was written ExprState->parent didn't exist, but it since has been introduced in 6719b238e8. Author: Andres Freund Discussion: https://postgr.es/m/20191023163849.sosqbfs5yenocez3@alap3.anarazel.de	6 years ago
Tom Lane	41c6f9db25	Repair more failures with SubPlans in multi-row VALUES lists. ... Commit 9b63c13f0 turns out to have been fundamentally misguided: the parent node's subPlan list is by no means the only way in which a child SubPlan node can be hooked into the outer execution state. As shown in bug #16213 from Matt Jibson, we can also get short-lived tuple table slots added to the outer es_tupleTable list. At this point I have little faith that there aren't other possible connections as well; the long time it took to notice this problem shows that this isn't a heavily-exercised situation. Therefore, revert that fix, returning to the coding that passed a NULL parent plan pointer down to the transiently-built subexpressions. That gives us a pretty good guarantee that they won't hook into the outer executor state in any way. But then we need some other solution to make SubPlans work. Adopt the solution speculated about in the previous commit's log message: do expression initialization at plan startup for just those VALUES rows containing SubPlans, abandoning the goal of reclaiming memory intra-query for those rows. In practice it seems unlikely that queries containing a vast number of VALUES rows would be using SubPlans in them, so this should not give up much. (BTW, this test case also refutes my claim in connection with the prior commit that the issue only arises with use of LATERAL. That was just wrong: some variants of SubLink always produce SubPlans.) As with previous patch, back-patch to all supported branches. Discussion: https://postgr.es/m/16213-871ac3bc208ecf23@postgresql.org	6 years ago
Bruce Momjian	7559d8ebfa	Update copyrights for 2020 ... Backpatch-through: update all files in master, backpatch legal files through 9.4	6 years ago
Tom Lane	5935917ce5	Allow executor startup pruning to prune all child nodes. ... Previously, if the startup pruning logic proved that all child nodes of an Append or MergeAppend could be pruned, we still kept one, just to keep EXPLAIN from failing. The previous commit removed the ruleutils.c limitation that required this kluge, so drop it. That results in less-confusing EXPLAIN output, as per a complaint from Yuzuko Hosoya. David Rowley Discussion: https://postgr.es/m/001001d4f44b$2a2cca50$7e865ef0$@lab.ntt.co.jp	6 years ago
Tom Lane	6ef77cf46e	Further adjust EXPLAIN's choices of table alias names. ... This patch causes EXPLAIN to always assign a separate table alias to the parent RTE of an append relation (inheritance set); before, such RTEs were ignored if not actually scanned by the plan. Since the child RTEs now always have that same alias to start with (cf. commit 55a1954da), the net effect is that the parent RTE usually gets the alias used or implied by the query text, and the children all get that alias with "_N" appended. (The exception to "usually" is if there are duplicate aliases in different subtrees of the original query; then some of those original RTEs will also have "_N" appended.) This results in more uniform output for partitioned-table plans than we had before: the partitioned table itself gets the original alias, and all child tables have aliases with "_N", rather than the previous behavior where one of the children would get an alias without "_N". The reason for giving the parent RTE an alias, even if it isn't scanned by the plan, is that we now use the parent's alias to qualify Vars that refer to an appendrel output column and appear above the Append or MergeAppend that computes the appendrel. But below the append, Vars refer to some one of the child relations, and are displayed that way. This seems clearer than the old behavior where a Var that could carry values from any child relation was displayed as if it referred to only one of them. While at it, change ruleutils.c so that the code paths used by EXPLAIN deal in Plan trees not PlanState trees. This effectively reverts a decision made in commit 1cc29fe7c, which seemed like a good idea at the time to make ruleutils.c consistent with explain.c. However, it's problematic because we'd really like to allow executor startup pruning to remove all the children of an append node when possible, leaving no child PlanState to resolve Vars against. (That's not done here, but will be in the next patch.) This requires different handling of subplans and initplans than before, but is otherwise a pretty straightforward change. Discussion: https://postgr.es/m/001001d4f44b$2a2cca50$7e865ef0$@lab.ntt.co.jp	6 years ago
Jeff Davis	30d47723fd	Fix comments in execGrouping.c ... Commit 5dfc1981 missed updating some comments. Also, fix a comment typo found in passing. Author: Jeff Davis Discussion: https://postgr.es/m/9723131d247b919f94699152647fa87ee0bc02c2.camel%40j-davis.com	6 years ago
Amit Kapila	e0487223ec	Make the order of the header file includes consistent. ... Similar to commits 14aec03502, 7e735035f2 and dddf4cdc33, this commit makes the order of header file inclusion consistent in more places. Author: Vignesh C Reviewed-by: Amit Kapila Discussion: https://postgr.es/m/CALDaNm2Sznv8RR6Ex-iJO6xAdsxgWhCoETkaYX=+9DW3q0QCfA@mail.gmail.com	6 years ago
Andres Freund	30d1379658	Fix ExprState's tag to be of type NodeTag rather than Node. ... This appears to have been an oversight in b8d7f053c5. As it's effectively harmless, though confusing, only fix in master. Author: Andres Freund	6 years ago
Andres Freund	27cc7cd2bc	Reorder EPQ work, to fix rowmark related bugs and improve efficiency. ... In ad0bda5d24 I changed the EvalPlanQual machinery to store substitution tuples in slot, instead of using plain HeapTuples. The main motivation for that was that using HeapTuples will be inefficient for future tableams. But it turns out that that conversion was buggy for non-locking rowmarks - the wrong tuple descriptor was used to create the slot. As a secondary issue 5db6df0c0 changed ExecLockRows() to begin EPQ earlier, to allow to fetch the locked rows directly into the EPQ slots, instead of having to copy tuples around. Unfortunately, as Tom complained, that forces some expensive initialization to happen earlier. As a third issue, the test coverage for EPQ was clearly insufficient. Fixing the first issue is unfortunately not trivial: Non-locked row marks were fetched at the start of EPQ, and we don't have the type information for the rowmarks available at that point. While we could change that, it's not easy. It might be worthwhile to change that at some point, but to fix this bug, it seems better to delay fetching non-locking rowmarks when they're actually needed, rather than eagerly. They're referenced at most once, and in cases where EPQ fails, might never be referenced. Fetching them when needed also increases locality a bit. To be able to fetch rowmarks during execution, rather than initialization, we need to be able to access the active EPQState, as that contains necessary data. To do so move EPQ related data from EState to EPQState, and, only for EStates creates as part of EPQ, reference the associated EPQState from EState. To fix the second issue, change EPQ initialization to allow use of EvalPlanQualSlot() to be used before EvalPlanQualBegin() (but obviously still requiring EvalPlanQualInit() to have been done). As these changes made struct EState harder to understand, e.g. by adding multiple EStates, significantly reorder the members, and add a lot more comments. Also add a few more EPQ tests, including one that fails for the first issue above. More is needed. Reported-By: yi huang Author: Andres Freund Reviewed-By: Tom Lane Discussion: https://postgr.es/m/CAHU7rYZo_C4ULsAx_LAj8az9zqgrD8WDd4hTegDTMM1LMqrBsg@mail.gmail.com https://postgr.es/m/24530.1562686693@sss.pgh.pa.us Backpatch: 12-, where the EPQ changes were introduced	6 years ago
Andres Freund	fb3b098fe8	Remove fmgr.h includes from headers that don't really need it. ... Most of the fmgr.h includes were obsoleted by 352a24a1f9. A few others can be obsoleted using the underlying struct type in an implementation detail. Author: Andres Freund Discussion: https://postgr.es/m/20190803193733.g3l3x3o42uv4qj7l@alap3.anarazel.de	6 years ago
Tom Lane	3c926587b5	Remove EState.es_range_table_array. ... Now that list_nth is O(1), there's no good reason to maintain a separate array of RTE pointers rather than indexing into estate->es_range_table. Deleting the array doesn't save all that much either; but just on cleanliness grounds, it's better not to have duplicate representations of the identical information. Discussion: https://postgr.es/m/14960.1565384592@sss.pgh.pa.us	6 years ago
Andres Freund	2abd7ae9b2	Fix representation of hash keys in Hash/HashJoin nodes. ... In 5f32b29c18 I changed the creation of HashState.hashkeys to actually use HashState as the parent (instead of HashJoinState, which was incorrect, as they were executed below HashState), to fix the problem of hashkeys expressions otherwise relying on slot types appropriate for HashJoinState, rather than HashState as would be correct. That reliance was only introduced in 12, which is why it previously worked to use HashJoinState as the parent (although I'd be unsurprised if there were problematic cases). Unfortunately that's not a sufficient solution, because before this commit, the to-be-hashed expressions referenced inner/outer as appropriate for the HashJoin, not Hash. That didn't have obvious bad consequences, because the slots containing the tuples were put into ecxt_innertuple when hashing a tuple for HashState (even though Hash doesn't have an inner plan). There are less common cases where this can cause visible problems however (rather than just confusion when inspecting such executor trees). E.g. "ERROR: bogus varno: 65000", when explaining queries containing a HashJoin where the subsidiary Hash node's hash keys reference a subplan. While normally hashkeys aren't displayed by EXPLAIN, if one of those expressions references a subplan, that subplan may be printed as part of the Hash node - which then failed because an inner plan was referenced, and Hash doesn't have that. It seems quite possible that there's other broken cases, too. Fix the problem by properly splitting the expression for the HashJoin and Hash nodes at plan time, and have them reference the proper subsidiary node. While other workarounds are possible, fixing this correctly seems easy enough. It was a pretty ugly hack to have ExecInitHashJoin put the expression into the already initialized HashState, in the first place. I decided to not just split inner/outer hashkeys inside make_hashjoin(), but also to separate out hashoperators and hashcollations at plan time. Otherwise we would have ended up having two very similar loops, one at plan time and the other during executor startup. The work seems to more appropriately belong to plan time, anyway. Reported-By: Nikita Glukhov, Alexander Korotkov Author: Andres Freund Reviewed-By: Tom Lane, in an earlier version Discussion: https://postgr.es/m/CAPpHfdvGVegF_TKKRiBrSmatJL2dR9uwFCuR+teQ_8tEXU8mxg@mail.gmail.com Backpatch: 12-	6 years ago
Michael Paquier	6b8548964b	Fix inconsistencies in the code ... This addresses a couple of issues in the code: - Typos and inconsistencies in comments and function declarations. - Removal of unreferenced function declarations. - Removal of unnecessary compile flags. - A cleanup error in regressplans.sh. Author: Alexander Lakhin Discussion: https://postgr.es/m/0c991fdf-2670-1997-c027-772a420c4604@gmail.com	7 years ago
Heikki Linnakangas	cd96389d71	Fix confusion on different kinds of slots in IndexOnlyScans. ... We used the same slot to store a tuple from the index, and to store a tuple from the table. That's not OK. It worked with the heap, because heapam_getnextslot() stores a HeapTuple to the slot, and doesn't care how large the tts_values/nulls arrays are. But when I played with a toy table AM implementation that used a virtual tuple, it caused memory overruns. In the passing, tidy up comments on the ioss_PscanLen fields.	7 years ago
Michael Paquier	1fb6f62a84	Fix typos in various places ... Author: Andrea Gelmini Reviewed-by: Michael Paquier, Justin Pryzby Discussion: https://postgr.es/m/20190528181718.GA39034@glet	7 years ago