657 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
Fujii Masao	d780d7c088	Change data type of counters in BufferUsage and WalUsage from long to int64. ... Previously long was used as the data type for some counters in BufferUsage and WalUsage. But long is only four byte, e.g., on Windows, and it's entirely possible to wrap a four byte counter. For example, emitting more than four billion WAL records in one transaction isn't actually particularly rare. To avoid the overflows of those counters, this commit changes the data type of them from long to int64. Suggested-by: Andres Freund Author: Masahiro Ikeda Reviewed-by: Fujii Masao Discussion: https://postgr.es/m/20201221211650.k7b53tcnadrciqjo@alap3.anarazel.de Discussion: https://postgr.es/m/af0964ac-7080-1984-dc23-513754987716@oss.nttdata.com	5 years ago
Tom Lane	049e1e2edb	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
Tom Lane	1111b2668d	Undo decision to allow pg_proc.prosrc to be NULL. ... Commit e717a9a18 changed the longstanding rule that prosrc is NOT NULL because when a SQL-language function is written in SQL-standard style, we don't currently have anything useful to put there. This seems a poor decision though, as it could easily have negative impacts on external PLs (opening them to crashes they didn't use to have, for instance). SQL-function-related code can just as easily test "is prosqlbody not null" as "is prosrc null", so there's no real gain there either. Hence, revert the NOT NULL marking removal and adjust related logic. For now, we just put an empty string into prosrc for SQL-standard functions. Maybe we'll have a better idea later, although the history of things like pg_attrdef.adsrc suggests that it's not easy to maintain a string equivalent of a node tree. This also adds an assertion that queryDesc->sourceText != NULL to standard_ExecutorStart. We'd been silently relying on that for awhile, so let's make it less silent. Also fix some overlooked documentation and test cases. Discussion: https://postgr.es/m/2197698.1617984583@sss.pgh.pa.us	5 years ago
Tom Lane	c2db458c10	Redesign the caching done by get_cached_rowtype(). ... Previously, get_cached_rowtype() cached a pointer to a reference-counted tuple descriptor from the typcache, relying on the ExprContextCallback mechanism to release the tupdesc refcount when the expression tree using the tupdesc was destroyed. This worked fine when it was designed, but the introduction of within-DO-block COMMITs broke it. The refcount is logged in a transaction-lifespan resource owner, but plpgsql won't destroy simple expressions made within the DO block (before its first commit) until the DO block is exited. That results in a warning about a leaked tupdesc refcount when the COMMIT destroys the original resource owner, and then an error about the active resource owner not holding a matching refcount when the expression is destroyed. To fix, get rid of the need to have a shutdown callback at all, by instead caching a pointer to the relevant typcache entry. Those survive for the life of the backend, so we needn't worry about the pointer becoming stale. (For registered RECORD types, we can still cache a pointer to the tupdesc, knowing that it won't change for the life of the backend.) This mechanism has been in use in plpgsql and expandedrecord.c since commit 4b93f5799, and seems to work well. This change requires modifying the ExprEvalStep structs used by the relevant expression step types, which is slightly worrisome for back-patching. However, there seems no good reason for extensions to be familiar with the details of these particular sub-structs. Per report from Rohit Bhogate. Back-patch to v11 where within-DO-block COMMITs became a thing. Discussion: https://postgr.es/m/CAAV6ZkQRCVBh8qAY+SZiHnz+U+FqAGBBDaDTjF2yiKa2nJSLKg@mail.gmail.com	5 years ago
David Rowley	50e17ad281	Speedup ScalarArrayOpExpr evaluation ... ScalarArrayOpExprs with "useOr=true" and a set of Consts on the righthand side have traditionally been evaluated by using a linear search over the array. When these arrays contain large numbers of elements then this linear search could become a significant part of execution time. Here we add a new method of evaluating ScalarArrayOpExpr expressions to allow them to be evaluated by first building a hash table containing each element, then on subsequent evaluations, we just probe that hash table to determine if there is a match. The planner is in charge of determining when this optimization is possible and it enables it by setting hashfuncid in the ScalarArrayOpExpr. The executor will only perform the hash table evaluation when the hashfuncid is set. This means that not all cases are optimized. For example CHECK constraints containing an IN clause won't go through the planner, so won't get the hashfuncid set. We could maybe do something about that at some later date. The reason we're not doing it now is from fear that we may slow down cases where the expression is evaluated only once. Those cases can be common, for example, a single row INSERT to a table with a CHECK constraint containing an IN clause. In the planner, we enable this when there are suitable hash functions for the ScalarArrayOpExpr's operator and only when there is at least MIN_ARRAY_SIZE_FOR_HASHED_SAOP elements in the array. The threshold is currently set to 9. Author: James Coleman, David Rowley Reviewed-by: David Rowley, Tomas Vondra, Heikki Linnakangas Discussion: https://postgr.es/m/CAAaqYe8x62+=wn0zvNKCj55tPpg-JBHzhZFFc6ANovdqFw7-dA@mail.gmail.com	5 years ago
Peter Eisentraut	e717a9a18b	SQL-standard function body ... This adds support for writing CREATE FUNCTION and CREATE PROCEDURE statements for language SQL with a function body that conforms to the SQL standard and is portable to other implementations. Instead of the PostgreSQL-specific AS $$ string literal $$ syntax, this allows writing out the SQL statements making up the body unquoted, either as a single statement: CREATE FUNCTION add(a integer, b integer) RETURNS integer LANGUAGE SQL RETURN a + b; or as a block CREATE PROCEDURE insert_data(a integer, b integer) LANGUAGE SQL BEGIN ATOMIC INSERT INTO tbl VALUES (a); INSERT INTO tbl VALUES (b); END; The function body is parsed at function definition time and stored as expression nodes in a new pg_proc column prosqlbody. So at run time, no further parsing is required. However, this form does not support polymorphic arguments, because there is no more parse analysis done at call time. Dependencies between the function and the objects it uses are fully tracked. A new RETURN statement is introduced. This can only be used inside function bodies. Internally, it is treated much like a SELECT statement. psql needs some new intelligence to keep track of function body boundaries so that it doesn't send off statements when it sees semicolons that are inside a function body. Tested-by: Jaime Casanova <jcasanov@systemguards.com.ec> Reviewed-by: Julien Rouhaud <rjuju123@gmail.com> Discussion: https://www.postgresql.org/message-id/flat/1c11f1eb-f00c-43b7-799d-2d44132c02d7@2ndquadrant.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
Tom Lane	789d81de8a	Fix missing #include in nodeResultCache.h. ... Per cpluspluscheck.	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
Thomas Munro	7f7f25f15e	Revert "Fix race in Parallel Hash Join batch cleanup." ... This reverts commit 378802e371. This reverts commit 3b8981b6e1. Discussion: https://postgr.es/m/CA%2BhUKGJmcqAE3MZeDCLLXa62cWM0AJbKmp2JrJYaJ86bz36LFA%40mail.gmail.com	5 years ago
Thomas Munro	378802e371	Update the names of Parallel Hash Join phases. ... Commit 3048898e dropped -ING from some wait event names that correspond to barrier phases. Update the phases' names to match. While we're here making cosmetic changes, also rename "DONE" to "FREE". That pairs better with "ALLOCATE", and describes the activity that actually happens in that phase (as we do for the other phases) rather than describing a state. The distinction is clearer after bugfix commit 3b8981b6 split the phase into two. As for the growth barriers, rename their "ALLOCATE" phase to "REALLOCATE", which is probably a better description of what happens then. Also improve the comments about the phases a bit. Discussion: https://postgr.es/m/CA%2BhUKG%2BMDpwF2Eo2LAvzd%3DpOh81wUTsrwU1uAwR-v6OGBB6%2B7g%40mail.gmail.com	5 years ago
Thomas Munro	3b8981b6e1	Fix race in Parallel Hash Join batch cleanup. ... With very unlucky timing and parallel_leader_participation off, PHJ could attempt to access per-batch state just as it was being freed. There was code intended to prevent that by checking for a cleared pointer, but it was buggy. Fix, by introducing an extra barrier phase. The new phase PHJ_BUILD_RUNNING means that it's safe to access the per-batch state to find a batch to help with, and PHJ_BUILD_DONE means that it is too late. The last to detach will free the array of per-batch state as before, but now it will also atomically advance the phase at the same time, so that late attachers can avoid the hazard, without the data race. This mirrors the way per-batch hash tables are freed (see phases PHJ_BATCH_PROBING and PHJ_BATCH_DONE). Revealed by a one-off build farm failure, where BarrierAttach() failed a sanity check assertion, because the memory had been clobbered by dsa_free(). Back-patch to 11, where the code arrived. Reported-by: Michael Paquier <michael@paquier.xyz> Discussion: https://postgr.es/m/20200929061142.GA29096%40paquier.xyz	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	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
Tom Lane	d5a83d79c9	Rethink recently-added SPI interfaces. ... SPI_execute_with_receiver and SPI_cursor_parse_open_with_paramlist are new in v14 (cf. commit 2f48ede08). Before they can get out the door, let's change their APIs to follow the practice recently established by SPI_prepare_extended etc: shove all optional arguments into a struct that callers are supposed to pre-zero. The hope is to allow future addition of more options without either API breakage or a continuing proliferation of new SPI entry points. With that in mind, choose slightly more generic names for them: SPI_execute_extended and SPI_cursor_parse_open respectively. Discussion: https://postgr.es/m/CAFj8pRCLPdDAETvR7Po7gC5y_ibkn_-bOzbeJb39WHms01194Q@mail.gmail.com	5 years ago
Tom Lane	ee895a655c	Improve performance of repeated CALLs within plpgsql procedures. ... This patch essentially is cleaning up technical debt left behind by the original implementation of plpgsql procedures, particularly commit d92bc83c4. That patch (or more precisely, follow-on patches fixing its worst bugs) forced us to re-plan CALL and DO statements each time through, if we're in a non-atomic context. That wasn't for any fundamental reason, but just because use of a saved plan requires having a ResourceOwner to hold a reference count for the plan, and we had no suitable resowner at hand, nor would the available APIs support using one if we did. While it's not that expensive to create a "plan" for CALL/DO, the cycles do add up in repeated executions. This patch therefore makes the following API changes: * GetCachedPlan/ReleaseCachedPlan are modified to let the caller specify which resowner to use to pin the plan, rather than forcing use of CurrentResourceOwner. * spi.c gains a "SPI_execute_plan_extended" entry point that lets callers say which resowner to use to pin the plan. This borrows the idea of an options struct from the recently added SPI_prepare_extended, hopefully allowing future options to be added without more API breaks. This supersedes SPI_execute_plan_with_paramlist (which I've marked deprecated) as well as SPI_execute_plan_with_receiver (which is new in v14, so I just took it out altogether). * I also took the opportunity to remove the crude hack of letting plpgsql reach into SPI private data structures to mark SPI plans as "no_snapshot". It's better to treat that as an option of SPI_prepare_extended. Now, when running a non-atomic procedure or DO block that contains any CALL or DO commands, plpgsql creates a ResourceOwner that will be used to pin the plans of the CALL/DO commands. (In an atomic context, we just use CurrentResourceOwner, as before.) Having done this, we can just save CALL/DO plans normally, whether or not they are used across transaction boundaries. This seems to be good for something like 2X speedup of a CALL of a trivial procedure with a few simple argument expressions. By restricting the creation of an extra ResourceOwner like this, there's essentially zero penalty in cases that can't benefit. Pavel Stehule, with some further hacking by me Discussion: https://postgr.es/m/CAFj8pRCLPdDAETvR7Po7gC5y_ibkn_-bOzbeJb39WHms01194Q@mail.gmail.com	5 years ago
Peter Geoghegan	9dc718bdf2	Pass down "logically unchanged index" hint. ... Add an executor aminsert() hint mechanism that informs index AMs that the incoming index tuple (the tuple that accompanies the hint) is not being inserted by execution of an SQL statement that logically modifies any of the index's key columns. The hint is received by indexes when an UPDATE takes place that does not apply an optimization like heapam's HOT (though only for indexes where all key columns are logically unchanged). Any index tuple that receives the hint on insert is expected to be a duplicate of at least one existing older version that is needed for the same logical row. Related versions will typically be stored on the same index page, at least within index AMs that apply the hint. Recognizing the difference between MVCC version churn duplicates and true logical row duplicates at the index AM level can help with cleanup of garbage index tuples. Cleanup can intelligently target tuples that are likely to be garbage, without wasting too many cycles on less promising tuples/pages (index pages with little or no version churn). This is infrastructure for an upcoming commit that will teach nbtree to perform bottom-up index deletion. No index AM actually applies the hint just yet. Author: Peter Geoghegan <pg@bowt.ie> Reviewed-By: Victor Yegorov <vyegorov@gmail.com> Discussion: https://postgr.es/m/CAH2-Wz=CEKFa74EScx_hFVshCOn6AA5T-ajFASTdzipdkLTNQQ@mail.gmail.com	5 years ago
Tom Lane	844fe9f159	Add the ability for the core grammar to have more than one parse target. ... This patch essentially allows gram.y to implement a family of related syntax trees, rather than necessarily always parsing a list of SQL statements. raw_parser() gains a new argument, enum RawParseMode, to say what to do. As proof of concept, add a mode that just parses a TypeName without any other decoration, and use that to greatly simplify typeStringToTypeName(). In addition, invent a new SPI entry point SPI_prepare_extended() to allow SPI users (particularly plpgsql) to get at this new functionality. In hopes of making this the last variant of SPI_prepare(), set up its additional arguments as a struct rather than direct arguments, and promise that future additions to the struct can default to zero. SPI_prepare_cursor() and SPI_prepare_params() can perhaps go away at some point. Discussion: https://postgr.es/m/4165684.1607707277@sss.pgh.pa.us	5 years ago
Bruce Momjian	ca3b37487b	Update copyright for 2021 ... Backpatch-through: 9.5	5 years ago
Tom Lane	c7aba7c14e	Support subscripting of arbitrary types, not only arrays. ... This patch generalizes the subscripting infrastructure so that any data type can be subscripted, if it provides a handler function to define what that means. Traditional variable-length (varlena) arrays all use array_subscript_handler(), while the existing fixed-length types that support subscripting use raw_array_subscript_handler(). It's expected that other types that want to use subscripting notation will define their own handlers. (This patch provides no such new features, though; it only lays the foundation for them.) To do this, move the parser's semantic processing of subscripts (including coercion to whatever data type is required) into a method callback supplied by the handler. On the execution side, replace the ExecEvalSubscriptingRef* layer of functions with direct calls to callback-supplied execution routines. (Thus, essentially no new run-time overhead should be caused by this patch. Indeed, there is room to remove some overhead by supplying specialized execution routines. This patch does a little bit in that line, but more could be done.) Additional work is required here and there to remove formerly hard-wired assumptions about the result type, collation, etc of a SubscriptingRef expression node; and to remove assumptions that the subscript values must be integers. One useful side-effect of this is that we now have a less squishy mechanism for identifying whether a data type is a "true" array: instead of wiring in weird rules about typlen, we can look to see if pg_type.typsubscript == F_ARRAY_SUBSCRIPT_HANDLER. For this to be bulletproof, we have to forbid user-defined types from using that handler directly; but there seems no good reason for them to do so. This patch also removes assumptions that the number of subscripts is limited to MAXDIM (6), or indeed has any hard-wired limit. That limit still applies to types handled by array_subscript_handler or raw_array_subscript_handler, but to discourage other dependencies on this constant, I've moved it from c.h to utils/array.h. Dmitry Dolgov, reviewed at various times by Tom Lane, Arthur Zakirov, Peter Eisentraut, Pavel Stehule Discussion: https://postgr.es/m/CA+q6zcVDuGBv=M0FqBYX8DPebS3F_0KQ6OVFobGJPM507_SZ_w@mail.gmail.com Discussion: https://postgr.es/m/CA+q6zcVovR+XY4mfk-7oNk-rF91gH0PebnNfuUjuuDsyHjOcVA@mail.gmail.com	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
Tom Lane	20d3fe9009	In INSERT/UPDATE, use the table's real tuple descriptor as target. ... Previously, ExecInitModifyTable relied on ExecInitJunkFilter, and thence ExecCleanTypeFromTL, to build the target descriptor from the query tlist. While we just checked (in ExecCheckPlanOutput) that the tlist produces compatible output, this is not a great substitute for the relation's actual tuple descriptor that's available from the relcache. For one thing, dropped columns will not be correctly marked attisdropped; it's a bit surprising that we've gotten away with that this long. But the real reason for being concerned with this is that using the table's descriptor means that the slot will have correct attrmissing data, allowing us to revert the klugy fix of commit ba9f18abd. (This commit undoes that one's changes in trigger.c, but keeps the new test case.) Thus we can solve the bogus-trigger-tuple problem with fewer cycles rather than more. No back-patch, since this doesn't fix any additional bug, and it seems somewhat more likely to have unforeseen side effects than ba9f18abd's narrow fix. Discussion: https://postgr.es/m/16644-5da7ef98a7ac4545@postgresql.org	5 years ago
Tom Lane	c8ab970179	Fix list-munging bug that broke SQL function result coercions. ... Since commit 913bbd88d, check_sql_fn_retval() can either insert type coercion steps in-line in the Query that produces the SQL function's results, or generate a new top-level Query to perform the coercions, if modifying the Query's output in-place wouldn't be safe. However, it appears that the latter case has never actually worked, because the code tried to inject the new Query back into the query list it was passed ... which is not the list that will be used for later processing when we execute the SQL function "normally" (without inlining it). So we ended up with no coercion happening at run-time, leading to wrong results or crashes depending on the datatypes involved. While the regression tests look like they cover this area well enough, through a huge bit of bad luck all the test cases that exercise the separate-Query path were checking either inline-able cases (which accidentally didn't have the bug) or cases that are no-ops at runtime (e.g., varchar to text), so that the failure to perform the coercion wasn't obvious. The fact that the cases that don't work weren't allowed at all before v13 probably contributed to not noticing the problem sooner, too. To fix, get rid of the separate "flat" list of Query nodes and instead pass the real two-level list that is going to be used later. I chose to make the same change in check_sql_fn_statements(), although that has no actual bug, just so that we don't need that data structure at all. This is an API change, as evidenced by the adjustments needed to callers outside functions.c. That's a bit scary to be doing in a released branch, but so far as I can tell from a quick search, there are no outside callers of these functions (and they are sufficiently specific to our semantics for SQL-language functions that it's not apparent why any extension would need to call them). In any case, v13 already changed the API of check_sql_fn_retval() compared to prior branches. Per report from pinker. Back-patch to v13 where this code came in. Discussion: https://postgr.es/m/1603050466566-0.post@n3.nabble.com	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	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	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
Michael Paquier	7b1110d2fd	Fix comment in instrument.h ... local_blks_dirtied tracks the number of local blocks dirtied, not shared ones. Author: Kirk Jamison Discussion: https://postgr.es/m/OSBPR01MB2341760686DC056DE89D2AB9EF710@OSBPR01MB2341.jpnprd01.prod.outlook.com	5 years ago
Peter Geoghegan	d6c08e29e7	Add hash_mem_multiplier GUC. ... Add a GUC that acts as a multiplier on work_mem. It gets applied when sizing executor node hash tables that were previously size constrained using work_mem alone. The new GUC can be used to preferentially give hash-based nodes more memory than the generic work_mem limit. It is intended to enable admin tuning of the executor's memory usage. Overall system throughput and system responsiveness can be improved by giving hash-based executor nodes more memory (especially over sort-based alternatives, which are often much less sensitive to being memory constrained). The default value for hash_mem_multiplier is 1.0, which is also the minimum valid value. This means that hash-based nodes continue to apply work_mem in the traditional way by default. hash_mem_multiplier is generally useful. However, it is being added now due to concerns about hash aggregate performance stability for users that upgrade to Postgres 13 (which added disk-based hash aggregation in commit 1f39bce0). While the old hash aggregate behavior risked out-of-memory errors, it is nevertheless likely that many users actually benefited. Hash agg's previous indifference to work_mem during query execution was not just faster; it also accidentally made aggregation resilient to grouping estimate problems (at least in cases where this didn't create destabilizing memory pressure). hash_mem_multiplier can provide a certain kind of continuity with the behavior of Postgres 12 hash aggregates in cases where the planner incorrectly estimates that all groups (plus related allocations) will fit in work_mem/hash_mem. This seems necessary because hash-based aggregation is usually much slower when only a small fraction of all groups can fit. Even when it isn't possible to totally avoid hash aggregates that spill, giving hash aggregation more memory will reliably improve performance (the same cannot be said for external sort operations, which appear to be almost unaffected by memory availability provided it's at least possible to get a single merge pass). The PostgreSQL 13 release notes should advise users that increasing hash_mem_multiplier can help with performance regressions associated with hash aggregation. That can be taken care of by a later commit. Author: Peter Geoghegan Reviewed-By: Álvaro Herrera, Jeff Davis Discussion: https://postgr.es/m/20200625203629.7m6yvut7eqblgmfo@alap3.anarazel.de Discussion: https://postgr.es/m/CAH2-WzmD%2Bi1pG6rc1%2BCjc4V6EaFJ_qSuKCCHVnH%3DoruqD-zqow%40mail.gmail.com Backpatch: 13-, where disk-based hash aggregation was introduced.	6 years ago
Jeff Davis	9878b643f3	HashAgg: use better cardinality estimate for recursive spilling. ... Use HyperLogLog to estimate the group cardinality in a spilled partition. This estimate is used to choose the number of partitions if we recurse. The previous behavior was to use the number of tuples in a spilled partition as the estimate for the number of groups, which lead to overpartitioning. That could cause the number of batches to be much higher than expected (with each batch being very small), which made it harder to interpret EXPLAIN ANALYZE results. Reviewed-by: Peter Geoghegan Discussion: https://postgr.es/m/a856635f9284bc36f7a77d02f47bbb6aaf7b59b3.camel@j-davis.com Backpatch-through: 13	6 years ago
Jeff Davis	200f6100a9	Fix LookupTupleHashEntryHash() pipeline-stall issue. ... Refactor hash lookups in nodeAgg.c to improve performance. Author: Andres Freund and Jeff Davis Discussion: https://postgr.es/m/20200612213715.op4ye4q7gktqvpuo%40alap3.anarazel.de Backpatch-through: 13	6 years ago
Thomas Munro	cdc7169509	Use MinimalTuple for tuple queues. ... This representation saves 8 bytes per tuple compared to HeapTuple, and avoids the need to allocate, copy and free on the receiving side. Gather can emit the returned MinimalTuple directly, but GatherMerge now needs to make an explicit copy because it buffers multiple tuples at a time. That should be no worse than before. Reviewed-by: Soumyadeep Chakraborty <soumyadeep2007@gmail.com> Discussion: https://postgr.es/m/CA%2BhUKG%2B8T_ggoUTAE-U%3DA%2BOcPc4%3DB0nPPHcSfffuQhvXXjML6w%40mail.gmail.com	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	2f48ede080	Avoid using a cursor in plpgsql's RETURN QUERY statement. ... plpgsql has always executed the query given in a RETURN QUERY command by opening it as a cursor and then fetching a few rows at a time, which it turns around and dumps into the function's result tuplestore. The point of this was to keep from blowing out memory with an oversized SPITupleTable result (note that while a tuplestore can spill tuples to disk, SPITupleTable cannot). However, it's rather inefficient, both because of extra data copying and because of executor entry/exit overhead. In recent versions, a new performance problem has emerged: use of a cursor prevents use of a parallel plan for the executed query. We can improve matters by skipping use of a cursor and having the executor push result tuples directly into the function's result tuplestore. However, a moderate amount of new infrastructure is needed to make that idea work: * We can use the existing tstoreReceiver.c DestReceiver code to funnel executor output to the tuplestore, but it has to be extended to support plpgsql's requirement for possibly applying a tuple conversion map. * SPI needs to be extended to allow use of a caller-supplied DestReceiver instead of its usual receiver that puts tuples into a SPITupleTable. Two new API calls are needed to handle both the RETURN QUERY and RETURN QUERY EXECUTE cases. I also felt that I didn't want these new API calls to use the legacy method of specifying query parameter values with "char" null flags (the old ' '/'n' convention); rather they should accept ParamListInfo objects containing the parameter type and value info. This required a bit of additional new infrastructure since we didn't yet have any parse analysis callback that would interpret $N parameter symbols according to type data supplied in a ParamListInfo. There seems to be no harm in letting makeParamList install that callback by default, rather than leaving a new ParamListInfo's parserSetup hook as NULL. (Indeed, as of HEAD, I couldn't find anyplace that was using the parserSetup field at all; plpgsql was using parserSetupArg for its own purposes, but parserSetup seemed to be write-only.) We can actually get plpgsql out of the business of using legacy null flags altogether, and using ParamListInfo instead of its ad-hoc PreparedParamsData structure; but this requires inventing one more SPI API call that can replace SPI_cursor_open_with_args. That seems worth doing, though. SPI_execute_with_args and SPI_cursor_open_with_args are now unused anywhere in the core PG distribution. Perhaps someday we could deprecate/remove them. But cleaning up the crufty bits of the SPI API is a task for a different patch. Per bug #16040 from Jeremy Smith. This is unfortunately too invasive to consider back-patching. Patch by me; thanks to Hamid Akhtar for review. Discussion: https://postgr.es/m/16040-eaacad11fecfb198@postgresql.org	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
Amit Kapila	69bfaf2e1d	Change the display of WAL usage statistics in Explain. ... In commit 33e05f89c5, we have added the option to display WAL usage statistics in Explain and auto_explain. The display format used two spaces between each field which is inconsistent with Buffer usage statistics which is using one space between each field. Change the format to make WAL usage statistics consistent with Buffer usage statistics. This commit also changed the usage of "full page writes" to "full page images" for WAL usage statistics to make it consistent with other parts of code and docs. Author: Julien Rouhaud, Amit Kapila Reviewed-by: Justin Pryzby, Kyotaro Horiguchi and Amit Kapila Discussion: https://postgr.es/m/CAB-hujrP8ZfUkvL5OYETipQwA=e3n7oqHFU=4ZLxWS_Cza3kQQ@mail.gmail.com	6 years ago
Amit Kapila	ef08ca113f	Cosmetic fixups for WAL usage work. ... Reported-by: Justin Pryzby and Euler Taveira Author: Justin Pryzby and Julien Rouhaud Reviewed-by: Amit Kapila Discussion: https://postgr.es/m/CAB-hujrP8ZfUkvL5OYETipQwA=e3n7oqHFU=4ZLxWS_Cza3kQQ@mail.gmail.com	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
Jeff Davis	50a38f6517	Create memory context for HashAgg with a reasonable maxBlockSize. ... If the memory context's maxBlockSize is too big, a single block allocation can suddenly exceed work_mem. For Hash Aggregation, this can mean spilling to disk too early or reporting a confusing memory usage number for EXPLAN ANALYZE. Introduce CreateWorkExprContext(), which is like CreateExprContext(), except that it creates the AllocSet with a maxBlockSize that is reasonable in proportion to work_mem. Right now, CreateWorkExprContext() is only used by Hash Aggregation, but it may be generally useful in the future. Discussion: https://postgr.es/m/412a3fbf306f84d8d78c4009e11791867e62b87c.camel@j-davis.com	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
Amit Kapila	df3b181499	Add infrastructure to track WAL usage. ... This allows gathering the WAL generation statistics for each statement execution. The three statistics that we collect are the number of WAL records, the number of full page writes and the amount of WAL bytes generated. This helps the users who have write-intensive workload to see the impact of I/O due to WAL. This further enables us to see approximately what percentage of overall WAL is due to full page writes. In the future, we can extend this functionality to allow us to compute the the exact amount of WAL data due to full page writes. This patch in itself is just an infrastructure to compute WAL usage data. The upcoming patches will expose this data via explain, auto_explain, pg_stat_statements and verbose (auto)vacuum output. Author: Kirill Bychik, Julien Rouhaud Reviewed-by: Dilip Kumar, Fujii Masao and Amit Kapila Discussion: https://postgr.es/m/CAB-hujrP8ZfUkvL5OYETipQwA=e3n7oqHFU=4ZLxWS_Cza3kQQ@mail.gmail.com	6 years ago
Jeff Davis	0588ee63aa	Include chunk overhead in hash table entry size estimate. ... Don't try to be precise about it, just use a constant 16 bytes of chunk overhead. Being smarter would require knowing the memory context where the chunk will be allocated, which is not known by all callers. Discussion: https://postgr.es/m/20200325220936.il3ni2fj2j2b45y5@alap3.anarazel.de	6 years ago
Fujii Masao	4a539a25eb	Expose BufferUsageAccumDiff(). ... Previously pg_stat_statements calculated the difference of buffer counters by its own code even while BufferUsageAccumDiff() had the same code. This commit expose BufferUsageAccumDiff() and makes pg_stat_statements use it for the calculation, in order to simply the code. This change also would be useful for the upcoming patch for the planning counters in pg_stat_statements because the patch will add one more code for the calculation of difference of buffer counters and that can easily be done by using BufferUsageAccumDiff(). Author: Julien Rouhaud Reviewed-by: Fujii Masao Discussion: https://postgr.es/m/bdfee4e0-a304-2498-8da5-3cb52c0a193e@oss.nttdata.com	6 years ago
Tom Lane	bda6dedbea	Go back to returning int from ereport auxiliary functions. ... This reverts the parts of commit 17a28b0364 that changed ereport's auxiliary functions from returning dummy integer values to returning void. It turns out that a minority of compilers complain (not entirely unreasonably) about constructs such as (condition) ? errdetail(...) : 0 if errdetail() returns void rather than int. We could update those call sites to say "(void) 0" perhaps, but the expectation for this patch set was that ereport callers would not have to change anything. And this aspect of the patch set was already the most invasive and least compelling part of it, so let's just drop it. Per buildfarm. Discussion: https://postgr.es/m/CA+fd4k6N8EjNvZpM8nme+y+05mz-SM8Z_BgkixzkA34R+ej0Kw@mail.gmail.com	6 years ago