61 Commits (44933010ceb3ac06d4c01b559aafed4bef16c45d)

Author	SHA1	Message	Date
David Rowley	47ca483644	Change the name of the Result Cache node to Memoize ... "Result Cache" was never a great name for this node, but nobody managed to come up with another name that anyone liked enough. That was until David Johnston mentioned "Node Memoization", which Tom Lane revised to just "Memoize". People seem to like "Memoize", so let's do the rename. Reviewed-by: Justin Pryzby Discussion: https://postgr.es/m/20210708165145.GG1176@momjian.us Backpatch-through: 14, where Result Cache was introduced	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
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
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
Andres Freund	01368e5d9d	Split all OBJS style lines in makefiles into one-line-per-entry style. ... When maintaining or merging patches, one of the most common sources for conflicts are the list of objects in makefiles. Especially when the split across lines has been changed on both sides, which is somewhat common due to attempting to stay below 80 columns, those conflicts are unnecessarily laborious to resolve. By splitting, and alphabetically sorting, OBJS style lines into one object per line, conflicts should be less frequent, and easier to resolve when they still occur. Author: Andres Freund Discussion: https://postgr.es/m/20191029200901.vww4idgcxv74cwes@alap3.anarazel.de	6 years ago
Simon Riggs	08ea7a2291	Revert MERGE patch ... This reverts commits d204ef6377, 83454e3c2b and a few more commits thereafter (complete list at the end) related to MERGE feature. While the feature was fully functional, with sufficient test coverage and necessary documentation, it was felt that some parts of the executor and parse-analyzer can use a different design and it wasn't possible to do that in the available time. So it was decided to revert the patch for PG11 and retry again in the future. Thanks again to all reviewers and bug reporters. List of commits reverted, in reverse chronological order: f1464c5380 Improve parse representation for MERGE ddb4158579 MERGE syntax diagram correction 530e69e59b Allow cpluspluscheck to pass by renaming variable 01b88b4df5 MERGE minor errata 3af7b2b0d4 MERGE fix variable warning in non-assert builds a5d86181ec MERGE INSERT allows only one VALUES clause 4b2d44031f MERGE post-commit review 4923550c20 Tab completion for MERGE aa3faa3c7a WITH support in MERGE 83454e3c2b New files for MERGE d204ef6377 MERGE SQL Command following SQL:2016 Author: Pavan Deolasee Reviewed-by: Michael Paquier	8 years ago
Simon Riggs	4b2d44031f	MERGE post-commit review ... Review comments from Andres Freund * Consolidate code into AfterTriggerGetTransitionTable() * Rename nodeMerge.c to execMerge.c * Rename nodeMerge.h to execMerge.h * Move MERGE handling in ExecInitModifyTable() into a execMerge.c ExecInitMerge() * Move mt_merge_subcommands flags into execMerge.h * Rename opt_and_condition to opt_merge_when_and_condition * Wordsmith various comments Author: Pavan Deolasee Reviewer: Simon Riggs	8 years ago
Simon Riggs	d204ef6377	MERGE SQL Command following SQL:2016 ... MERGE performs actions that modify rows in the target table using a source table or query. MERGE provides a single SQL statement that can conditionally INSERT/UPDATE/DELETE rows a task that would other require multiple PL statements. e.g. MERGE INTO target AS t USING source AS s ON t.tid = s.sid WHEN MATCHED AND t.balance > s.delta THEN UPDATE SET balance = t.balance - s.delta WHEN MATCHED THEN DELETE WHEN NOT MATCHED AND s.delta > 0 THEN INSERT VALUES (s.sid, s.delta) WHEN NOT MATCHED THEN DO NOTHING; MERGE works with regular and partitioned tables, including column and row security enforcement, as well as support for row, statement and transition triggers. MERGE is optimized for OLTP and is parameterizable, though also useful for large scale ETL/ELT. MERGE is not intended to be used in preference to existing single SQL commands for INSERT, UPDATE or DELETE since there is some overhead. MERGE can be used statically from PL/pgSQL. MERGE does not yet support inheritance, write rules, RETURNING clauses, updatable views or foreign tables. MERGE follows SQL Standard per the most recent SQL:2016. Includes full tests and documentation, including full isolation tests to demonstrate the concurrent behavior. This version written from scratch in 2017 by Simon Riggs, using docs and tests originally written in 2009. Later work from Pavan Deolasee has been both complex and deep, leaving the lead author credit now in his hands. Extensive discussion of concurrency from Peter Geoghegan, with thanks for the time and effort contributed. Various issues reported via sqlsmith by Andreas Seltenreich Authors: Pavan Deolasee, Simon Riggs Reviewer: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs Discussion: https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.com https://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com	8 years ago
Simon Riggs	7cf8a5c302	Revert "Modified files for MERGE" ... This reverts commit 354f13855e.	8 years ago
Simon Riggs	354f13855e	Modified files for MERGE	8 years ago
Robert Haas	4e5fe9ad19	Centralize executor-related partitioning code. ... Some code is moved from partition.c, which has grown very quickly lately; splitting the executor parts out might help to keep it from getting totally out of control. Other code is moved from execMain.c. All is moved to a new file execPartition.c. get_partition_for_tuple now has a new interface that more clearly separates executor concerns from generic concerns. Amit Langote. A slight comment tweak by me. Discussion: http://postgr.es/m/1f0985f8-3b61-8bc4-4350-baa6d804cb6d@lab.ntt.co.jp	8 years ago
Kevin Grittner	18ce3a4ab2	Add infrastructure to support EphemeralNamedRelation references. ... A QueryEnvironment concept is added, which allows new types of objects to be passed into queries from parsing on through execution. At this point, the only thing implemented is a collection of EphemeralNamedRelation objects -- relations which can be referenced by name in queries, but do not exist in the catalogs. The only type of ENR implemented is NamedTuplestore, but provision is made to add more types fairly easily. An ENR can carry its own TupleDesc or reference a relation in the catalogs by relid. Although these features can be used without SPI, convenience functions are added to SPI so that ENRs can easily be used by code run through SPI. The initial use of all this is going to be transition tables in AFTER triggers, but that will be added to each PL as a separate commit. An incidental effect of this patch is to produce a more informative error message if an attempt is made to modify the contents of a CTE from a referencing DML statement. No tests previously covered that possibility, so one is added. Kevin Grittner and Thomas Munro Reviewed by Heikki Linnakangas, David Fetter, and Thomas Munro with valuable comments and suggestions from many others	9 years ago
Andres Freund	b8d7f053c5	Faster expression evaluation and targetlist projection. ... This replaces the old, recursive tree-walk based evaluation, with non-recursive, opcode dispatch based, expression evaluation. Projection is now implemented as part of expression evaluation. This both leads to significant performance improvements, and makes future just-in-time compilation of expressions easier. The speed gains primarily come from: - non-recursive implementation reduces stack usage / overhead - simple sub-expressions are implemented with a single jump, without function calls - sharing some state between different sub-expressions - reduced amount of indirect/hard to predict memory accesses by laying out operation metadata sequentially; including the avoidance of nearly all of the previously used linked lists - more code has been moved to expression initialization, avoiding constant re-checks at evaluation time Future just-in-time compilation (JIT) has become easier, as demonstrated by released patches intended to be merged in a later release, for primarily two reasons: Firstly, due to a stricter split between expression initialization and evaluation, less code has to be handled by the JIT. Secondly, due to the non-recursive nature of the generated "instructions", less performance-critical code-paths can easily be shared between interpreted and compiled evaluation. The new framework allows for significant future optimizations. E.g.: - basic infrastructure for to later reduce the per executor-startup overhead of expression evaluation, by caching state in prepared statements. That'd be helpful in OLTPish scenarios where initialization overhead is measurable. - optimizing the generated "code". A number of proposals for potential work has already been made. - optimizing the interpreter. Similarly a number of proposals have been made here too. The move of logic into the expression initialization step leads to some backward-incompatible changes: - Function permission checks are now done during expression initialization, whereas previously they were done during execution. In edge cases this can lead to errors being raised that previously wouldn't have been, e.g. a NULL array being coerced to a different array type previously didn't perform checks. - The set of domain constraints to be checked, is now evaluated once during expression initialization, previously it was re-built every time a domain check was evaluated. For normal queries this doesn't change much, but e.g. for plpgsql functions, which caches ExprStates, the old set could stick around longer. The behavior around might still change. Author: Andres Freund, with significant changes by Tom Lane, changes by Heikki Linnakangas Reviewed-By: Tom Lane, Heikki Linnakangas Discussion: https://postgr.es/m/20161206034955.bh33paeralxbtluv@alap3.anarazel.de	9 years ago
Robert Haas	355d3993c5	Add a Gather Merge executor node. ... Like Gather, we spawn multiple workers and run the same plan in each one; however, Gather Merge is used when each worker produces the same output ordering and we want to preserve that output ordering while merging together the streams of tuples from various workers. (In a way, Gather Merge is like a hybrid of Gather and MergeAppend.) This works out to a win if it saves us from having to perform an expensive Sort. In cases where only a small amount of data would need to be sorted, it may actually be faster to use a regular Gather node and then sort the results afterward, because Gather Merge sometimes needs to wait synchronously for tuples whereas a pure Gather generally doesn't. But if this avoids an expensive sort then it's a win. Rushabh Lathia, reviewed and tested by Amit Kapila, Thomas Munro, and Neha Sharma, and reviewed and revised by me. Discussion: http://postgr.es/m/CAGPqQf09oPX-cQRpBKS0Gq49Z+m6KBxgxd_p9gX8CKk_d75HoQ@mail.gmail.com	9 years ago
Alvaro Herrera	fcec6caafa	Support XMLTABLE query expression ... XMLTABLE is defined by the SQL/XML standard as a feature that allows turning XML-formatted data into relational form, so that it can be used as a <table primary> in the FROM clause of a query. This new construct provides significant simplicity and performance benefit for XML data processing; what in a client-side custom implementation was reported to take 20 minutes can be executed in 400ms using XMLTABLE. (The same functionality was said to take 10 seconds using nested PostgreSQL XPath function calls, and 5 seconds using XMLReader under PL/Python). The implemented syntax deviates slightly from what the standard requires. First, the standard indicates that the PASSING clause is optional and that multiple XML input documents may be given to it; we make it mandatory and accept a single document only. Second, we don't currently support a default namespace to be specified. This implementation relies on a new executor node based on a hardcoded method table. (Because the grammar is fixed, there is no extensibility in the current approach; further constructs can be implemented on top of this such as JSON_TABLE, but they require changes to core code.) Author: Pavel Stehule, Álvaro Herrera Extensively reviewed by: Craig Ringer Discussion: https://postgr.es/m/CAFj8pRAgfzMD-LoSmnMGybD0WsEznLHWap8DO79+-GTRAPR4qA@mail.gmail.com	9 years ago
Peter Eisentraut	665d1fad99	Logical replication ... - Add PUBLICATION catalogs and DDL - Add SUBSCRIPTION catalog and DDL - Define logical replication protocol and output plugin - Add logical replication workers From: Petr Jelinek <petr@2ndquadrant.com> Reviewed-by: Steve Singer <steve@ssinger.info> Reviewed-by: Andres Freund <andres@anarazel.de> Reviewed-by: Erik Rijkers <er@xs4all.nl> Reviewed-by: Peter Eisentraut <peter.eisentraut@2ndquadrant.com>	9 years ago
Andres Freund	69f4b9c85f	Move targetlist SRF handling from expression evaluation to new executor node. ... Evaluation of set returning functions (SRFs_ in the targetlist (like SELECT generate_series(1,5)) so far was done in the expression evaluation (i.e. ExecEvalExpr()) and projection (i.e. ExecProject/ExecTargetList) code. This meant that most executor nodes performing projection, and most expression evaluation functions, had to deal with the possibility that an evaluated expression could return a set of return values. That's bad because it leads to repeated code in a lot of places. It also, and that's my (Andres's) motivation, made it a lot harder to implement a more efficient way of doing expression evaluation. To fix this, introduce a new executor node (ProjectSet) that can evaluate targetlists containing one or more SRFs. To avoid the complexity of the old way of handling nested expressions returning sets (e.g. having to pass up ExprDoneCond, and dealing with arguments to functions returning sets etc.), those SRFs can only be at the top level of the node's targetlist. The planner makes sure (via split_pathtarget_at_srfs()) that SRF evaluation is only necessary in ProjectSet nodes and that SRFs are only present at the top level of the node's targetlist. If there are nested SRFs the planner creates multiple stacked ProjectSet nodes. The ProjectSet nodes always get input from an underlying node. We also discussed and prototyped evaluating targetlist SRFs using ROWS FROM(), but that turned out to be more complicated than we'd hoped. While moving SRF evaluation to ProjectSet would allow to retain the old "least common multiple" behavior when multiple SRFs are present in one targetlist (i.e. continue returning rows until all SRFs are at the end of their input at the same time), we decided to instead only return rows till all SRFs are exhausted, returning NULL for already exhausted ones. We deemed the previous behavior to be too confusing, unexpected and actually not particularly useful. As a side effect, the previously prohibited case of multiple set returning arguments to a function, is now allowed. Not because it's particularly desirable, but because it ends up working and there seems to be no argument for adding code to prohibit it. Currently the behavior for COALESCE and CASE containing SRFs has changed, returning multiple rows from the expression, even when the SRF containing "arm" of the expression is not evaluated. That's because the SRFs are evaluated in a separate ProjectSet node. As that's quite confusing, we're likely to instead prohibit SRFs in those places. But that's still being discussed, and the code would reside in places not touched here, so that's a task for later. There's a lot of, now superfluous, code dealing with set return expressions around. But as the changes to get rid of those are verbose largely boring, it seems better for readability to keep the cleanup as a separate commit. Author: Tom Lane and Andres Freund Discussion: https://postgr.es/m/20160822214023.aaxz5l4igypowyri@alap3.anarazel.de	9 years ago
Robert Haas	3bd909b220	Add a Gather executor node. ... A Gather executor node runs any number of copies of a plan in an equal number of workers and merges all of the results into a single tuple stream. It can also run the plan itself, if the workers are unavailable or haven't started up yet. It is intended to work with the Partial Seq Scan node which will be added in future commits. It could also be used to implement parallel query of a different sort by itself, without help from Partial Seq Scan, if the single_copy mode is used. In that mode, a worker executes the plan, and the parallel leader does not, merely collecting the worker's results. So, a Gather node could be inserted into a plan to split the execution of that plan across two processes. Nested Gather nodes aren't currently supported, but we might want to add support for that in the future. There's nothing in the planner to actually generate Gather nodes yet, so it's not quite time to break out the champagne. But we're getting close. Amit Kapila. Some designs suggestions were provided by me, and I also reviewed the patch. Single-copy mode, documentation, and other minor changes also by me.	10 years ago
Robert Haas	d1b7c1ffe7	Parallel executor support. ... This code provides infrastructure for a parallel leader to start up parallel workers to execute subtrees of the plan tree being executed in the master. User-supplied parameters from ParamListInfo are passed down, but PARAM_EXEC parameters are not. Various other constructs, such as initplans, subplans, and CTEs, are also not currently shared. Nevertheless, there's enough here to support a basic implementation of parallel query, and we can lift some of the current restrictions as needed. Amit Kapila and Robert Haas	10 years ago
Robert Haas	4a4e6893aa	Glue layer to connect the executor to the shm_mq mechanism. ... The shm_mq mechanism was built to send error (and notice) messages and tuples between backends. However, shm_mq itself only deals in raw bytes. Since commit 2bd9e412f9, we have had infrastructure for one message to redirect protocol messages to a queue and for another backend to parse them and do useful things with them. This commit introduces a somewhat analogous facility for tuples by adding a new type of DestReceiver, DestTupleQueue, which writes each tuple generated by a query into a shm_mq, and a new TupleQueueFunnel facility which reads raw tuples out of the queue and reconstructs the HeapTuple format expected by the executor. The TupleQueueFunnel abstraction supports reading from multiple tuple streams at the same time, but only in round-robin fashion. Someone could imaginably want other policies, but this should be good enough to meet our short-term needs related to parallel query, and we can always extend it later. This also makes one minor addition to the shm_mq API that didn' seem worth breaking out as a separate patch. Extracted from Amit Kapila's parallel sequential scan patch. This code was originally written by me, and then it was revised by Amit, and then it was revised some more by me.	10 years ago
Simon Riggs	f6d208d6e5	TABLESAMPLE, SQL Standard and extensible ... Add a TABLESAMPLE clause to SELECT statements that allows user to specify random BERNOULLI sampling or block level SYSTEM sampling. Implementation allows for extensible sampling functions to be written, using a standard API. Basic version follows SQLStandard exactly. Usable concrete use cases for the sampling API follow in later commits. Petr Jelinek Reviewed by Michael Paquier and Simon Riggs	11 years ago
Heikki Linnakangas	62420ae7d6	Move functions related to index maintenance to separate source file. ... There is enough code here to deserve a file of their own, not be buried in the middle of execUtils.c.	11 years ago
Robert Haas	0b03e5951b	Introduce custom path and scan providers. ... This allows extension modules to define their own methods for scanning a relation, and get the core code to use them. It's unclear as yet how much use this capability will find, but we won't find out if we never commit it. KaiGai Kohei, reviewed at various times and in various levels of detail by Shigeru Hanada, Tom Lane, Andres Freund, Álvaro Herrera, and myself.	11 years ago
Tom Lane	a0185461dd	Rearrange the implementation of index-only scans. ... This commit changes index-only scans so that data is read directly from the index tuple without first generating a faux heap tuple. The only immediate benefit is that indexes on system columns (such as OID) can be used in index-only scans, but this is necessary infrastructure if we are ever to support index-only scans on expression indexes. The executor is now ready for that, though the planner still needs substantial work to recognize the possibility. To do this, Vars in index-only plan nodes have to refer to index columns not heap columns. I introduced a new special varno, INDEX_VAR, to mark such Vars to avoid confusion. (In passing, this commit renames the two existing special varnos to OUTER_VAR and INNER_VAR.) This allows ruleutils.c to handle them with logic similar to what we use for subplan reference Vars. Since index-only scans are now fundamentally different from regular indexscans so far as their expression subtrees are concerned, I also chose to change them to have their own plan node type (and hence, their own executor source file).	14 years ago
Tom Lane	bb74240794	Implement an API to let foreign-data wrappers actually be functional. ... This commit provides the core code and documentation needed. A contrib module test case will follow shortly. Shigeru Hanada, Jan Urbanski, Heikki Linnakangas	15 years ago
Tom Lane	11cad29c91	Support MergeAppend plans, to allow sorted output from append relations. ... This patch eliminates the former need to sort the output of an Append scan when an ordered scan of an inheritance tree is wanted. This should be particularly useful for fast-start cases such as queries with LIMIT. Original patch by Greg Stark, with further hacking by Hans-Jurgen Schonig, Robert Haas, and Tom Lane.	15 years ago
Magnus Hagander	9f2e211386	Remove cvs keywords from all files.	16 years ago
Tom Lane	0adaf4cb31	Move the handling of SELECT FOR UPDATE locking and rechecking out of ... execMain.c and into a new plan node type LockRows. Like the recent change to put table updating into a ModifyTable plan node, this increases planning flexibility by allowing the operations to occur below the top level of the plan tree. It's necessary in any case to restore the previous behavior of having FOR UPDATE locking occur before ModifyTable does. This partially refactors EvalPlanQual to allow multiple rows-under-test to be inserted into the EPQ machinery before starting an EPQ test query. That isn't sufficient to fix EPQ's general bogosity in the face of plans that return multiple rows per test row, though. Since this patch is mostly about getting some plan node infrastructure in place and not about fixing ten-year-old bugs, I will leave EPQ improvements for another day. Another behavioral change that we could now think about is doing FOR UPDATE before LIMIT, but that too seems like it should be treated as a followon patch.	16 years ago
Tom Lane	8a5849b7ff	Split the processing of INSERT/UPDATE/DELETE operations out of execMain.c. ... They are now handled by a new plan node type called ModifyTable, which is placed at the top of the plan tree. In itself this change doesn't do much, except perhaps make the handling of RETURNING lists and inherited UPDATEs a tad less klugy. But it is necessary preparation for the intended extension of allowing RETURNING queries inside WITH. Marko Tiikkaja	16 years ago
Tom Lane	95b07bc7f5	Support window functions a la SQL:2008. ... Hitoshi Harada, with some kibitzing from Heikki and Tom.	17 years ago
Tom Lane	44d5be0e53	Implement SQL-standard WITH clauses, including WITH RECURSIVE. ... There are some unimplemented aspects: recursive queries must use UNION ALL (should allow UNION too), and we don't have SEARCH or CYCLE clauses. These might or might not get done for 8.4, but even without them it's a pretty useful feature. There are also a couple of small loose ends and definitional quibbles, which I'll send a memo about to pgsql-hackers shortly. But let's land the patch now so we can get on with other development. Yoshiyuki Asaba, with lots of help from Tatsuo Ishii and Tom Lane	18 years ago
Peter Eisentraut	0474dcb608	Refactor backend makefiles to remove lots of duplicate code	18 years ago
Tom Lane	6808f1b1de	Support UPDATE/DELETE WHERE CURRENT OF cursor_name, per SQL standard. ... Along the way, allow FOR UPDATE in non-WITH-HOLD cursors; there may once have been a reason to disallow that, but it seems to work now, and it's really rather necessary if you want to select a row via a cursor and then update it in a concurrent-safe fashion. Original patch by Arul Shaji, rather heavily editorialized by Tom Lane.	19 years ago
Peter Eisentraut	2cc01004c6	Remove remains of old depend target.	19 years ago
Joe Conway	9caafda579	Add support for multi-row VALUES clauses as part of INSERT statements ... (e.g. "INSERT ... VALUES (...), (...), ...") and elsewhere as allowed by the spec. (e.g. similar to a FROM clause subselect). initdb required. Joe Conway and Tom Lane.	20 years ago
Tom Lane	4a8c5d0375	Create executor and planner-backend support for decoupled heap and index ... scans, using in-memory tuple ID bitmaps as the intermediary. The planner frontend (path creation and cost estimation) is not there yet, so none of this code can be executed. I have tested it using some hacked planner code that is far too ugly to see the light of day, however. Committing now so that the bulk of the infrastructure changes go in before the tree drifts under me.	21 years ago
PostgreSQL Daemon	969685ad44	$Header: -> $PostgreSQL Changes ...	22 years ago
Bruce Momjian	54f7338fa1	This patch implements holdable cursors, following the proposal ... (materialization into a tuple store) discussed on pgsql-hackers earlier. I've updated the documentation and the regression tests. Notes on the implementation: - I needed to change the tuple store API slightly -- it assumes that it won't be used to hold data across transaction boundaries, so the temp files that it uses for on-disk storage are automatically reclaimed at end-of-transaction. I added a flag to tuplestore_begin_heap() to control this behavior. Is changing the tuple store API in this fashion OK? - in order to store executor results in a tuple store, I added a new CommandDest. This works well for the most part, with one exception: the current DestFunction API doesn't provide enough information to allow the Executor to store results into an arbitrary tuple store (where the particular tuple store to use is chosen by the call site of ExecutorRun). To workaround this, I've temporarily hacked up a solution that works, but is not ideal: since the receiveTuple DestFunction is passed the portal name, we can use that to lookup the Portal data structure for the cursor and then use that to get at the tuple store the Portal is using. This unnecessarily ties the Portal code with the tupleReceiver code, but it works... The proper fix for this is probably to change the DestFunction API -- Tom suggested passing the full QueryDesc to the receiveTuple function. In that case, callers of ExecutorRun could "subclass" QueryDesc to add any additional fields that their particular CommandDest needed to get access to. This approach would work, but I'd like to think about it for a little bit longer before deciding which route to go. In the mean time, the code works fine, so I don't think a fix is urgent. - (semi-related) I added a NO SCROLL keyword to DECLARE CURSOR, and adjusted the behavior of SCROLL in accordance with the discussion on -hackers. - (unrelated) Cleaned up some SGML markup in sql.sgml, copy.sgml Neil Conway	23 years ago
Tom Lane	1afac12910	Create a new file executor/execGrouping.c to centralize utility routines ... shared by nodeGroup, nodeAgg, and soon nodeSubplan.	23 years ago
Tom Lane	3389a110d4	Get rid of long-since-vestigial Iter node type, in favor of adding a ... returns-set boolean field in Func and Oper nodes. This allows cleaner, more reliable tests for expressions returning sets in the planner and parser. For example, a WHERE clause returning a set is now detected and complained of in the parser, not only at runtime.	24 years ago
Tom Lane	f9e4f611a1	First pass at set-returning-functions in FROM, by Joe Conway with ... some kibitzing from Tom Lane. Not everything works yet, and there's no documentation or regression test, but let's commit this so Joe doesn't need to cope with tracking changes in so many files ...	24 years ago
Tom Lane	89fa551808	EXPLAIN ANALYZE feature to measure and show actual runtimes and tuple ... counts alongside the planner's estimates. By Martijn van Oosterhout, with some further work by Tom Lane.	25 years ago
Tom Lane	2f35b4efdb	Re-implement LIMIT/OFFSET as a plan node type, instead of a hack in ... ExecutorRun. This allows LIMIT to work in a view. Also, LIMIT in a cursor declaration will behave in a reasonable fashion, whereas before it was overridden by the FETCH count.	26 years ago
Tom Lane	05e3d0ee86	Reimplementation of UNION/INTERSECT/EXCEPT. INTERSECT/EXCEPT now meet the ... SQL92 semantics, including support for ALL option. All three can be used in subqueries and views. DISTINCT and ORDER BY work now in views, too. This rewrite fixes many problems with cross-datatype UNIONs and INSERT/SELECT where the SELECT yields different datatypes than the INSERT needs. I did that by making UNION subqueries and SELECT in INSERT be treated like subselects-in-FROM, thereby allowing an extra level of targetlist where the datatype conversions can be inserted safely. INITDB NEEDED!	26 years ago
Tom Lane	3a94e789f5	Subselects in FROM clause, per ISO syntax: FROM (SELECT ...) [AS] alias. ... (Don't forget that an alias is required.) Views reimplemented as expanding to subselect-in-FROM. Grouping, aggregates, DISTINCT in views actually work now (he says optimistically). No UNION support in subselects/views yet, but I have some ideas about that. Rule-related permissions checking moved out of rewriter and into executor. INITDB REQUIRED!	26 years ago
Peter Eisentraut	424f0edcb8	Fix relative path references so that make knowns which dependencies refer ... to one another. Sort out builddir vs srcdir variable namings. Remove some now obsoleted make variables.	26 years ago
Tom Lane	091126fa28	Generated header files parse.h and fmgroids.h are now copied into ... the src/include tree, so that -I backend is no longer necessary anywhere. Also, clean up some bit rot in contrib tree.	26 years ago