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release-6-3
${ noResults }
164 Commits (77bae396df3f6f883f58f1877b7c08eb3ebb6b63)
| Author | SHA1 | Message | Date |
|---|---|---|---|
|
|
27b77ecf9f |
Update copyright for 2022
Backpatch-through: 10 |
4 years ago |
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83f4fcc655 |
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 |
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955b3e0f92 |
Allow CustomScan providers to say whether they support projections.
Previously, all CustomScan providers had to support projections, but there may be cases where this is inconvenient. Add a flag bit to say if it's supported. Important item for the release notes: this is non-backwards-compatible since the default is now to assume that CustomScan providers can't project, instead of assuming that they can. It's fail-soft, but could result in visible performance penalties due to adding unnecessary Result nodes. Sven Klemm, reviewed by Aleksander Alekseev; some cosmetic fiddling by me. Discussion: https://postgr.es/m/CAMCrgp1kyakOz6c8aKhNDJXjhQ1dEjEnp+6KNT3KxPrjNtsrDg@mail.gmail.com |
5 years ago |
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def5b065ff |
Initial pgindent and pgperltidy run for v14.
Also "make reformat-dat-files". The only change worthy of note is that pgindent messed up the formatting of launcher.c's struct LogicalRepWorkerId, which led me to notice that that struct wasn't used at all anymore, so I just took it out. |
5 years ago |
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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 |
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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 |
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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 |
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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 |
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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 |
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ca3b37487b |
Update copyright for 2021
Backpatch-through: 9.5 |
5 years ago |
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660b89928d |
Properly check index mark/restore in ExecSupportsMarkRestore.
Previously this code assumed that all IndexScan nodes supported mark/restore, which is not true since it depends on optional index AM support functions. This could lead to errors about missing support functions in rare edge cases of mergejoins with no sort keys, where an unordered non-btree index scan was placed on the inner path without a protecting Materialize node. (Normally, the fact that merge join requires ordered input would avoid this error.) Backpatch all the way since this bug is ancient. Per report from Eugen Konkov on irc. Discussion: https://postgr.es/m/87o8jn50be.fsf@news-spur.riddles.org.uk |
5 years ago |
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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 |
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7559d8ebfa |
Update copyrights for 2020
Backpatch-through: update all files in master, backpatch legal files through 9.4 |
6 years ago |
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7854e07f25 |
Revert "Rename files and headers related to index AM"
This follows multiple complains from Peter Geoghegan, Andres Freund and Alvaro Herrera that this issue ought to be dug more before actually happening, if it happens. Discussion: https://postgr.es/m/20191226144606.GA5659@alvherre.pgsql |
6 years ago |
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8ce3aa9b59 |
Rename files and headers related to index AM
The following renaming is done so as source files related to index access methods are more consistent with table access methods (the original names used for index AMs ware too generic, and could be confused as including features related to table AMs): - amapi.h -> indexam.h. - amapi.c -> indexamapi.c. Here we have an equivalent with backend/access/table/tableamapi.c. - amvalidate.c -> indexamvalidate.c. - amvalidate.h -> indexamvalidate.h. - genam.c -> indexgenam.c. - genam.h -> indexgenam.h. This has been discussed during the development of v12 when table AM was worked on, but the renaming never happened. Author: Michael Paquier Reviewed-by: Fabien Coelho, Julien Rouhaud Discussion: https://postgr.es/m/20191223053434.GF34339@paquier.xyz |
6 years ago |
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14aec03502 |
Make the order of the header file includes consistent in backend modules.
Similar to commits |
6 years ago |
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8edd0e7946 |
Suppress Append and MergeAppend plan nodes that have a single child.
If there's only one child relation, the Append or MergeAppend isn't doing anything useful, and can be elided. It does have a purpose during planning though, which is to serve as a buffer between parent and child Var numbering. Therefore we keep it all the way through to setrefs.c, and get rid of it only after fixing references in the plan level(s) above it. This works largely the same as setrefs.c's ancient hack to get rid of no-op SubqueryScan nodes, and can even share some code with that. Note the change to make setrefs.c use apply_tlist_labeling rather than ad-hoc code. This has the effect of propagating the child's resjunk and ressortgroupref labels, which formerly weren't propagated when removing a SubqueryScan. Doing that is demonstrably necessary for the [Merge]Append cases, and seems harmless for SubqueryScan, if only because trivial_subqueryscan is afraid to collapse cases where the resjunk marking differs. (I suspect that restriction could now be removed, though it's unclear that it'd make any new matches possible, since the outer query can't have references to a child resjunk column.) David Rowley, reviewed by Alvaro Herrera and Tomas Vondra Discussion: https://postgr.es/m/CAKJS1f_7u8ATyJ1JGTMHFoKDvZdeF-iEBhs+sM_SXowOr9cArg@mail.gmail.com |
7 years ago |
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fa2cf164aa |
Rename nodes/relation.h to nodes/pathnodes.h.
The old name of this file was never a very good indication of what it was for. Now that there's also access/relation.h, we have a potential confusion hazard as well, so let's rename it to something more apropos. Per discussion, "pathnodes.h" is reasonable, since a good fraction of the file is Path node definitions. While at it, tweak a couple of other headers that were gratuitously importing relation.h into modules that don't need it. Discussion: https://postgr.es/m/7719.1548688728@sss.pgh.pa.us |
7 years ago |
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4be058fe9e |
In the planner, replace an empty FROM clause with a dummy RTE.
The fact that "SELECT expression" has no base relations has long been a thorn in the side of the planner. It makes it hard to flatten a sub-query that looks like that, or is a trivial VALUES() item, because the planner generally uses relid sets to identify sub-relations, and such a sub-query would have an empty relid set if we flattened it. prepjointree.c contains some baroque logic that works around this in certain special cases --- but there is a much better answer. We can replace an empty FROM clause with a dummy RTE that acts like a table of one row and no columns, and then there are no such corner cases to worry about. Instead we need some logic to get rid of useless dummy RTEs, but that's simpler and covers more cases than what was there before. For really trivial cases, where the query is just "SELECT expression" and nothing else, there's a hazard that adding the extra RTE makes for a noticeable slowdown; even though it's not much processing, there's not that much for the planner to do overall. However testing says that the penalty is very small, close to the noise level. In more complex queries, this is able to find optimizations that we could not find before. The new RTE type is called RTE_RESULT, since the "scan" plan type it gives rise to is a Result node (the same plan we produced for a "SELECT expression" query before). To avoid confusion, rename the old ResultPath path type to GroupResultPath, reflecting that it's only used in degenerate grouping cases where we know the query produces just one grouped row. (It wouldn't work to unify the two cases, because there are different rules about where the associated quals live during query_planner.) Note: although this touches readfuncs.c, I don't think a catversion bump is required, because the added case can't occur in stored rules, only plans. Patch by me, reviewed by David Rowley and Mark Dilger Discussion: https://postgr.es/m/15944.1521127664@sss.pgh.pa.us |
7 years ago |
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97c39498e5 |
Update copyright for 2019
Backpatch-through: certain files through 9.4 |
7 years ago |
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9d4649ca49 |
Update copyright for 2018
Backpatch-through: certain files through 9.3 |
8 years ago |
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1295a77788 |
Add missing call to ExecReScanGatherMerge.
Amit Kapila Discussion: http://postgr.es/m/CAA4eK1KeQWZOoDmDmGMwuqzPW9JhRS+ditQVFdAfGjNmMZzqMQ@mail.gmail.com |
9 years ago |
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a6fd7b7a5f |
Post-PG 10 beta1 pgindent run
perltidy run not included. |
9 years ago |
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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 |
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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 |
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9ba8a9ce45 |
Use the new castNode() macro in a number of places.
This is far from a pervasive conversion, but it's a good starting point. Author: Peter Eisentraut, with some minor changes by me Reviewed-By: Tom Lane Discussion: https://postgr.es/m/c5d387d9-3440-f5e0-f9d4-71d53b9fbe52@2ndquadrant.com |
9 years ago |
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ea15e18677 |
Remove obsoleted code relating to targetlist SRF evaluation.
Since
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9 years ago |
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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 |
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1d25779284 |
Update copyright via script for 2017
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9 years ago |
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ed0097e4f9 |
Add SQL-accessible functions for inspecting index AM properties.
Per discussion, we should provide such functions to replace the lost ability to discover AM properties by inspecting pg_am (cf commit |
10 years ago |
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4bc424b968 |
pgindent run for 9.6
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10 years ago |
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3fc6e2d7f5 |
Make the upper part of the planner work by generating and comparing Paths.
I've been saying we needed to do this for more than five years, and here it finally is. This patch removes the ever-growing tangle of spaghetti logic that grouping_planner() used to use to try to identify the best plan for post-scan/join query steps. Now, there is (nearly) independent consideration of each execution step, and entirely separate construction of Paths to represent each of the possible ways to do that step. We choose the best Path or set of Paths using the same add_path() logic that's been used inside query_planner() for years. In addition, this patch removes the old restriction that subquery_planner() could return only a single Plan. It now returns a RelOptInfo containing a set of Paths, just as query_planner() does, and the parent query level can use each of those Paths as the basis of a SubqueryScanPath at its level. This allows finding some optimizations that we missed before, wherein a subquery was capable of returning presorted data and thereby avoiding a sort in the parent level, making the overall cost cheaper even though delivering sorted output was not the cheapest plan for the subquery in isolation. (A couple of regression test outputs change in consequence of that. However, there is very little change in visible planner behavior overall, because the point of this patch is not to get immediate planning benefits but to create the infrastructure for future improvements.) There is a great deal left to do here. This patch unblocks a lot of planner work that was basically impractical in the old code structure, such as allowing FDWs to implement remote aggregation, or rewriting plan_set_operations() to allow consideration of multiple implementation orders for set operations. (The latter will likely require a full rewrite of plan_set_operations(); what I've done here is only to fix it to return Paths not Plans.) I have also left unfinished some localized refactoring in createplan.c and planner.c, because it was not necessary to get this patch to a working state. Thanks to Robert Haas, David Rowley, and Amit Kapila for review. |
10 years ago |
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65c5fcd353 |
Restructure index access method API to hide most of it at the C level.
This patch reduces pg_am to just two columns, a name and a handler function. All the data formerly obtained from pg_am is now provided in a C struct returned by the handler function. This is similar to the designs we've adopted for FDWs and tablesample methods. There are multiple advantages. For one, the index AM's support functions are now simple C functions, making them faster to call and much less error-prone, since the C compiler can now check function signatures. For another, this will make it far more practical to define index access methods in installable extensions. A disadvantage is that SQL-level code can no longer see attributes of index AMs; in particular, some of the crosschecks in the opr_sanity regression test are no longer possible from SQL. We've addressed that by adding a facility for the index AM to perform such checks instead. (Much more could be done in that line, but for now we're content if the amvalidate functions more or less replace what opr_sanity used to do.) We might also want to expose some sort of reporting functionality, but this patch doesn't do that. Alexander Korotkov, reviewed by Petr Jelínek, and rather heavily editorialized on by me. |
10 years ago |
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ee94300446 |
Update copyright for 2016
Backpatch certain files through 9.1 |
10 years ago |
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f0661c4e8c |
Make sequential scans parallel-aware.
In addition, this path fills in a number of missing bits and pieces in the parallel infrastructure. Paths and plans now have a parallel_aware flag indicating whether whatever parallel-aware logic they have should be engaged. It is believed that we will need this flag for a number of path/plan types, not just sequential scans, which is why the flag is generic rather than part of the SeqScan structures specifically. Also, execParallel.c now gives parallel nodes a chance to initialize their PlanState nodes from the DSM during parallel worker startup. Amit Kapila, with a fair amount of adjustment by me. Review of previous patch versions by Haribabu Kommi and others. |
10 years ago |
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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 |
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dd7a8f66ed |
Redesign tablesample method API, and do extensive code review.
The original implementation of TABLESAMPLE modeled the tablesample method API on index access methods, which wasn't a good choice because, without specialized DDL commands, there's no way to build an extension that can implement a TSM. (Raw inserts into system catalogs are not an acceptable thing to do, because we can't undo them during DROP EXTENSION, nor will pg_upgrade behave sanely.) Instead adopt an API more like procedural language handlers or foreign data wrappers, wherein the only SQL-level support object needed is a single handler function identified by having a special return type. This lets us get rid of the supporting catalog altogether, so that no custom DDL support is needed for the feature. Adjust the API so that it can support non-constant tablesample arguments (the original coding assumed we could evaluate the argument expressions at ExecInitSampleScan time, which is undesirable even if it weren't outright unsafe), and discourage sampling methods from looking at invisible tuples. Make sure that the BERNOULLI and SYSTEM methods are genuinely repeatable within and across queries, as required by the SQL standard, and deal more honestly with methods that can't support that requirement. Make a full code-review pass over the tablesample additions, and fix assorted bugs, omissions, infelicities, and cosmetic issues (such as failure to put the added code stanzas in a consistent ordering). Improve EXPLAIN's output of tablesample plans, too. Back-patch to 9.5 so that we don't have to support the original API in production. |
11 years ago |
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807b9e0dff |
pgindent run for 9.5
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11 years ago |
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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 |
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4baaf863ec |
Update copyright for 2015
Backpatch certain files through 9.0 |
11 years ago |
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adbfab119b |
Remove dead code supporting mark/restore in SeqScan, TidScan, ValuesScan.
There seems no prospect that any of this will ever be useful, and indeed it's questionable whether some of it would work if it ever got called; it's certainly not been exercised in a very long time, if ever. So let's get rid of it, and make the comments about mark/restore in execAmi.c less wishy-washy. The mark/restore support for Result nodes is also currently dead code, but that's due to planner limitations not because it's impossible that it could be useful. So I left it in. |
11 years ago |
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a34fa8ee7c |
Initial code review for CustomScan patch.
Get rid of the pernicious entanglement between planner and executor headers
introduced by commit
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11 years ago |
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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 |
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0a78320057 |
pgindent run for 9.4
This includes removing tabs after periods in C comments, which was applied to back branches, so this change should not effect backpatching. |
12 years ago |
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7e04792a1c |
Update copyright for 2014
Update all files in head, and files COPYRIGHT and legal.sgml in all back branches. |
12 years ago |
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bd61a623ac |
Update copyrights for 2013
Fully update git head, and update back branches in ./COPYRIGHT and legal.sgml files. |
13 years ago |
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c219d9b0a5 |
Split tuple struct defs from htup.h to htup_details.h
This reduces unnecessary exposure of other headers through htup.h, which is very widely included by many files. I have chosen to move the function prototypes to the new file as well, because that means htup.h no longer needs to include tupdesc.h. In itself this doesn't have much effect in indirect inclusion of tupdesc.h throughout the tree, because it's also required by execnodes.h; but it's something to explore in the future, and it seemed best to do the htup.h change now while I'm busy with it. |
14 years ago |
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e126958c2e |
Update copyright notices for year 2012.
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14 years ago |
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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 |
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f197272365 |
Make EXPLAIN ANALYZE report the numbers of rows rejected by filter steps.
This provides information about the numbers of tuples that were visited but not returned by table scans, as well as the numbers of join tuples that were considered and discarded within a join plan node. There is still some discussion going on about the best way to report counts for outer-join situations, but I think most of what's in the patch would not change if we revise that, so I'm going to go ahead and commit it as-is. Documentation changes to follow (they weren't in the submitted patch either). Marko Tiikkaja, reviewed by Marc Cousin, somewhat revised by Tom |
14 years ago |