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${ noResults }
313 Commits (ed7e686a031e5b9469e0813af2f513dfdd77560b)
Author | SHA1 | Message | Date |
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3c05284d83 |
Invent GENERIC_PLAN option for EXPLAIN.
This provides a very simple way to see the generic plan for a parameterized query. Without this, it's necessary to define a prepared statement and temporarily change plan_cache_mode, which is a bit tedious. One thing that's a bit of a hack perhaps is that we disable execution-time partition pruning when the GENERIC_PLAN option is given. That's because the pruning code may attempt to fetch the value of one of the parameters, which would fail. Laurenz Albe, reviewed by Julien Rouhaud, Christoph Berg, Michel Pelletier, Jim Jones, and myself Discussion: https://postgr.es/m/0a29b954b10b57f0d135fe12aa0909bd41883eb0.camel@cybertec.at |
3 years ago |
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19d8e2308b |
Ignore BRIN indexes when checking for HOT updates
When determining whether an index update may be skipped by using HOT, we can ignore attributes indexed by block summarizing indexes without references to individual tuples that need to be cleaned up. A new type TU_UpdateIndexes provides a signal to the executor to determine which indexes to update - no indexes, all indexes, or only the summarizing indexes. This also removes rd_indexattr list, and replaces it with rd_attrsvalid flag. The list was not used anywhere, and a simple flag is sufficient. This was originally committed as |
3 years ago |
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b803b7d132 |
Fill EState.es_rteperminfos more systematically.
While testing a fix for bug #17823, I discovered that EvalPlanQualStart
failed to copy es_rteperminfos from the parent EState, resulting in
failure if anything in EPQ execution wanted to consult that information.
This led me to conclude that commit
|
3 years ago |
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c8e1ba736b |
Update copyright for 2023
Backpatch-through: 11 |
3 years ago |
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a61b1f7482
|
Rework query relation permission checking
Currently, information about the permissions to be checked on relations mentioned in a query is stored in their range table entries. So the executor must scan the entire range table looking for relations that need to have permissions checked. This can make the permission checking part of the executor initialization needlessly expensive when many inheritance children are present in the range range. While the permissions need not be checked on the individual child relations, the executor still must visit every range table entry to filter them out. This commit moves the permission checking information out of the range table entries into a new plan node called RTEPermissionInfo. Every top-level (inheritance "root") RTE_RELATION entry in the range table gets one and a list of those is maintained alongside the range table. This new list is initialized by the parser when initializing the range table. The rewriter can add more entries to it as rules/views are expanded. Finally, the planner combines the lists of the individual subqueries into one flat list that is passed to the executor for checking. To make it quick to find the RTEPermissionInfo entry belonging to a given relation, RangeTblEntry gets a new Index field 'perminfoindex' that stores the corresponding RTEPermissionInfo's index in the query's list of the latter. ExecutorCheckPerms_hook has gained another List * argument; the signature is now: typedef bool (*ExecutorCheckPerms_hook_type) (List *rangeTable, List *rtePermInfos, bool ereport_on_violation); The first argument is no longer used by any in-core uses of the hook, but we leave it in place because there may be other implementations that do. Implementations should likely scan the rtePermInfos list to determine which operations to allow or deny. Author: Amit Langote <amitlangote09@gmail.com> Discussion: https://postgr.es/m/CA+HiwqGjJDmUhDSfv-U2qhKJjt9ST7Xh9JXC_irsAQ1TAUsJYg@mail.gmail.com |
3 years ago |
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fb958b5da8
|
Generalize ri_RootToPartitionMap to use for non-partition children
ri_RootToPartitionMap is currently only initialized for tuple routing target partitions, though a future commit will need the ability to use it even for the non-partition child tables, so make adjustments to the decouple it from the partitioning code. Also, make it lazily initialized via ExecGetRootToChildMap(), making that function its preferred access path. Existing third-party code accessing it directly should no longer do so; consequently, it's been renamed to ri_RootToChildMap, which also makes it consistent with ri_ChildToRootMap. ExecGetRootToChildMap() houses the logic of setting the map appropriately depending on whether a given child relation is partition or not. To support this, also add a separate entry point for TupleConversionMap creation that receives an AttrMap. No new code here, just split an existing function in two. Author: Amit Langote <amitlangote09@gmail.com> Discussion: https://postgr.es/m/CA+HiwqEYUhDXSK5BTvG_xk=eaAEJCD4GS3C6uH7ybBvv+Z_Tmg@mail.gmail.com |
3 years ago |
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bfcf1b3480 |
Harmonize parameter names in storage and AM code.
Make sure that function declarations use names that exactly match the corresponding names from function definitions in storage, catalog, access method, executor, and logical replication code, as well as in miscellaneous utility/library code. Like other recent commits that cleaned up function parameter names, this commit was written with help from clang-tidy. Later commits will do the same for other parts of the codebase. Author: Peter Geoghegan <pg@bowt.ie> Reviewed-By: David Rowley <dgrowleyml@gmail.com> Discussion: https://postgr.es/m/CAH2-WznJt9CMM9KJTMjJh_zbL5hD9oX44qdJ4aqZtjFi-zA3Tg@mail.gmail.com |
3 years ago |
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c35ba141de |
Future-proof the recursion inside ExecShutdownNode().
The API contract for planstate_tree_walker() callbacks is that they take a PlanState pointer and a context pointer. Somebody figured they could save a couple lines of code by ignoring that, and passing ExecShutdownNode itself as the walker even though it has but one argument. Somewhat remarkably, we've gotten away with that so far. However, it seems clear that the upcoming C2x standard means to forbid such cases, and compilers that actively break such code likely won't be far behind. So spend the extra few lines of code to do it honestly with a separate walker function. In HEAD, we might as well go further and remove ExecShutdownNode's useless return value. I left that as-is in back branches though, to forestall complaints about ABI breakage. Back-patch, with the thought that this might become of practical importance before our stable branches are all out of service. It doesn't seem to be fixing any live bug on any currently known platform, however. Discussion: https://postgr.es/m/208054.1663534665@sss.pgh.pa.us |
3 years ago |
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2f2b18bd3f |
Revert SQL/JSON features
The reverts the following and makes some associated cleanups: commit f79b803dc: Common SQL/JSON clauses commit f4fb45d15: SQL/JSON constructors commit 5f0adec25: Make STRING an unreserved_keyword. commit 33a377608: IS JSON predicate commit 1a36bc9db: SQL/JSON query functions commit 606948b05: SQL JSON functions commit 49082c2cc: RETURNING clause for JSON() and JSON_SCALAR() commit 4e34747c8: JSON_TABLE commit fadb48b00: PLAN clauses for JSON_TABLE commit 2ef6f11b0: Reduce running time of jsonb_sqljson test commit 14d3f24fa: Further improve jsonb_sqljson parallel test commit a6baa4bad: Documentation for SQL/JSON features commit b46bcf7a4: Improve readability of SQL/JSON documentation. commit 112fdb352: Fix finalization for json_objectagg and friends commit fcdb35c32: Fix transformJsonBehavior commit 4cd8717af: Improve a couple of sql/json error messages commit f7a605f63: Small cleanups in SQL/JSON code commit 9c3d25e17: Fix JSON_OBJECTAGG uniquefying bug commit a79153b7a: Claim SQL standard compliance for SQL/JSON features commit a1e7616d6: Rework SQL/JSON documentation commit 8d9f9634e: Fix errors in copyfuncs/equalfuncs support for JSON node types. commit 3c633f32b: Only allow returning string types or bytea from json_serialize commit 67b26703b: expression eval: Fix EEOP_JSON_CONSTRUCTOR and EEOP_JSONEXPR size. The release notes are also adjusted. Backpatch to release 15. Discussion: https://postgr.es/m/40d2c882-bcac-19a9-754d-4299e1d87ac7@postgresql.org |
3 years ago |
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23e7b38bfe |
Pre-beta mechanical code beautification.
Run pgindent, pgperltidy, and reformat-dat-files. I manually fixed a couple of comments that pgindent uglified. |
3 years ago |
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a90641eac2
|
Revert "Rewrite some RI code to avoid using SPI"
This reverts commit
|
3 years ago |
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99392cdd78
|
Rewrite some RI code to avoid using SPI
Modify the subroutines called by RI trigger functions that want to check
if a given referenced value exists in the referenced relation to simply
scan the foreign key constraint's unique index, instead of using SPI to
execute
SELECT 1 FROM referenced_relation WHERE ref_key = $1
This saves a lot of work, especially when inserting into or updating a
referencing relation.
This rewrite allows to fix a PK row visibility bug caused by a partition
descriptor hack which requires ActiveSnapshot to be set to come up with
the correct set of partitions for the RI query running under REPEATABLE
READ isolation. We now set that snapshot indepedently of the snapshot
to be used by the PK index scan, so the two no longer interfere. The
buggy output in src/test/isolation/expected/fk-snapshot.out of the
relevant test case added by commit
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3 years ago |
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1a36bc9dba |
SQL/JSON query functions
This introduces the SQL/JSON functions for querying JSON data using jsonpath expressions. The functions are: JSON_EXISTS() JSON_QUERY() JSON_VALUE() All of these functions only operate on jsonb. The workaround for now is to cast the argument to jsonb. JSON_EXISTS() tests if the jsonpath expression applied to the jsonb value yields any values. JSON_VALUE() must return a single value, and an error occurs if it tries to return multiple values. JSON_QUERY() must return a json object or array, and there are various WRAPPER options for handling scalar or multi-value results. Both these functions have options for handling EMPTY and ERROR conditions. Nikita Glukhov Reviewers have included (in no particular order) Andres Freund, Alexander Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zihong Yu, Himanshu Upadhyaya, Daniel Gustafsson, Justin Pryzby. Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru |
4 years ago |
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ba9a7e3921
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Enforce foreign key correctly during cross-partition updates
When an update on a partitioned table referenced in foreign key constraints causes a row to move from one partition to another, the fact that the move is implemented as a delete followed by an insert on the target partition causes the foreign key triggers to have surprising behavior. For example, a given foreign key's delete trigger which implements the ON DELETE CASCADE clause of that key will delete any referencing rows when triggered for that internal DELETE, although it should not, because the referenced row is simply being moved from one partition of the referenced root partitioned table into another, not being deleted from it. This commit teaches trigger.c to skip queuing such delete trigger events on the leaf partitions in favor of an UPDATE event fired on the root target relation. Doing so is sensible because both the old and the new tuple "logically" belong to the root relation. The after trigger event queuing interface now allows passing the source and the target partitions of a particular cross-partition update when registering the update event for the root partitioned table. Along with the two ctids of the old and the new tuple, the after trigger event now also stores the OIDs of those partitions. The tuples fetched from the source and the target partitions are converted into the root table format, if necessary, before they are passed to the trigger function. The implementation currently has a limitation that only the foreign keys pointing into the query's target relation are considered, not those of its sub-partitioned partitions. That seems like a reasonable limitation, because it sounds rare to have distinct foreign keys pointing to sub-partitioned partitions instead of to the root table. This misbehavior stems from commit |
4 years ago |
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27b77ecf9f |
Update copyright for 2022
Backpatch-through: 10 |
4 years ago |
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e3ec3c00d8 |
Remove arbitrary 64K-or-so limit on rangetable size.
Up to now the size of a query's rangetable has been limited by the constants INNER_VAR et al, which mustn't be equal to any real rangetable index. 65000 doubtless seemed like enough for anybody, and it still is orders of magnitude larger than the number of joins we can realistically handle. However, we need a rangetable entry for each child partition that is (or might be) processed by a query. Queries with a few thousand partitions are getting more realistic, so that the day when that limit becomes a problem is in sight, even if it's not here yet. Hence, let's raise the limit. Rather than just increase the values of INNER_VAR et al, this patch adopts the approach of making them small negative values, so that rangetables could theoretically become as long as INT_MAX. The bulk of the patch is concerned with changing Var.varno and some related variables from "Index" (unsigned int) to plain "int". This is basically cosmetic, with little actual effect other than to help debuggers print their values nicely. As such, I've only bothered with changing places that could actually see INNER_VAR et al, which the parser and most of the planner don't. We do have to be careful in places that are performing less/greater comparisons on varnos, but there are very few such places, other than the IS_SPECIAL_VARNO macro itself. A notable side effect of this patch is that while it used to be possible to add INNER_VAR et al to a Bitmapset, that will now draw an error. I don't see any likelihood that it wouldn't be a bug to include these fake varnos in a bitmapset of real varnos, so I think this is all to the good. Although this touches outfuncs/readfuncs, I don't think a catversion bump is required, since stored rules would never contain Vars with these fake varnos. Andrey Lepikhov and Tom Lane, after a suggestion by Peter Eisentraut Discussion: https://postgr.es/m/43c7f2f5-1e27-27aa-8c65-c91859d15190@postgrespro.ru |
4 years ago |
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049e1e2edb |
Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists.
It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028 |
4 years ago |
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c5b7ba4e67 |
Postpone some stuff out of ExecInitModifyTable.
Arrange to do some things on-demand, rather than immediately during
executor startup, because there's a fair chance of never having to do
them at all:
* Don't open result relations' indexes until needed.
* Don't initialize partition tuple routing, nor the child-to-root
tuple conversion map, until needed.
This wins in UPDATEs on partitioned tables when only some of the
partitions will actually receive updates; with larger partition
counts the savings is quite noticeable. Also, we can remove some
sketchy heuristics in ExecInitModifyTable about whether to set up
tuple routing.
Also, remove execPartition.c's private hash table tracking which
partitions were already opened by the ModifyTable node. Instead
use the hash added to ModifyTable itself by commit
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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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86dc90056d |
Rework planning and execution of UPDATE and DELETE.
This patch makes two closely related sets of changes: 1. For UPDATE, the subplan of the ModifyTable node now only delivers the new values of the changed columns (i.e., the expressions computed in the query's SET clause) plus row identity information such as CTID. ModifyTable must re-fetch the original tuple to merge in the old values of any unchanged columns. The core advantage of this is that the changed columns are uniform across all tables of an inherited or partitioned target relation, whereas the other columns might not be. A secondary advantage, when the UPDATE involves joins, is that less data needs to pass through the plan tree. The disadvantage of course is an extra fetch of each tuple to be updated. However, that seems to be very nearly free in context; even worst-case tests don't show it to add more than a couple percent to the total query cost. At some point it might be interesting to combine the re-fetch with the tuple access that ModifyTable must do anyway to mark the old tuple dead; but that would require a good deal of refactoring and it seems it wouldn't buy all that much, so this patch doesn't attempt it. 2. For inherited UPDATE/DELETE, instead of generating a separate subplan for each target relation, we now generate a single subplan that is just exactly like a SELECT's plan, then stick ModifyTable on top of that. To let ModifyTable know which target relation a given incoming row refers to, a tableoid junk column is added to the row identity information. This gets rid of the horrid hack that was inheritance_planner(), eliminating O(N^2) planning cost and memory consumption in cases where there were many unprunable target relations. Point 2 of course requires point 1, so that there is a uniform definition of the non-junk columns to be returned by the subplan. We can't insist on uniform definition of the row identity junk columns however, if we want to keep the ability to have both plain and foreign tables in a partitioning hierarchy. Since it wouldn't scale very far to have every child table have its own row identity column, this patch includes provisions to merge similar row identity columns into one column of the subplan result. In particular, we can merge the whole-row Vars typically used as row identity by FDWs into one column by pretending they are type RECORD. (It's still okay for the actual composite Datums to be labeled with the table's rowtype OID, though.) There is more that can be done to file down residual inefficiencies in this patch, but it seems to be committable now. FDW authors should note several API changes: * The argument list for AddForeignUpdateTargets() has changed, and so has the method it must use for adding junk columns to the query. Call add_row_identity_var() instead of manipulating the parse tree directly. You might want to reconsider exactly what you're adding, too. * PlanDirectModify() must now work a little harder to find the ForeignScan plan node; if the foreign table is part of a partitioning hierarchy then the ForeignScan might not be the direct child of ModifyTable. See postgres_fdw for sample code. * To check whether a relation is a target relation, it's no longer sufficient to compare its relid to root->parse->resultRelation. Instead, check it against all_result_relids or leaf_result_relids, as appropriate. Amit Langote and Tom Lane Discussion: https://postgr.es/m/CA+HiwqHpHdqdDn48yCEhynnniahH78rwcrv1rEX65-fsZGBOLQ@mail.gmail.com |
5 years ago |
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6214e2b228 |
Fix permission checks on constraint violation errors on partitions.
If a cross-partition UPDATE violates a constraint on the target partition,
and the columns in the new partition are in different physical order than
in the parent, the error message can reveal columns that the user does not
have SELECT permission on. A similar bug was fixed earlier in commit
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5 years ago |
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9dc718bdf2 |
Pass down "logically unchanged index" hint.
Add an executor aminsert() hint mechanism that informs index AMs that the incoming index tuple (the tuple that accompanies the hint) is not being inserted by execution of an SQL statement that logically modifies any of the index's key columns. The hint is received by indexes when an UPDATE takes place that does not apply an optimization like heapam's HOT (though only for indexes where all key columns are logically unchanged). Any index tuple that receives the hint on insert is expected to be a duplicate of at least one existing older version that is needed for the same logical row. Related versions will typically be stored on the same index page, at least within index AMs that apply the hint. Recognizing the difference between MVCC version churn duplicates and true logical row duplicates at the index AM level can help with cleanup of garbage index tuples. Cleanup can intelligently target tuples that are likely to be garbage, without wasting too many cycles on less promising tuples/pages (index pages with little or no version churn). This is infrastructure for an upcoming commit that will teach nbtree to perform bottom-up index deletion. No index AM actually applies the hint just yet. Author: Peter Geoghegan <pg@bowt.ie> Reviewed-By: Victor Yegorov <vyegorov@gmail.com> Discussion: https://postgr.es/m/CAH2-Wz=CEKFa74EScx_hFVshCOn6AA5T-ajFASTdzipdkLTNQQ@mail.gmail.com |
5 years ago |
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ca3b37487b |
Update copyright for 2021
Backpatch-through: 9.5 |
5 years ago |
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20d3fe9009 |
In INSERT/UPDATE, use the table's real tuple descriptor as target.
Previously, ExecInitModifyTable relied on ExecInitJunkFilter,
and thence ExecCleanTypeFromTL, to build the target descriptor from
the query tlist. While we just checked (in ExecCheckPlanOutput)
that the tlist produces compatible output, this is not a great
substitute for the relation's actual tuple descriptor that's
available from the relcache. For one thing, dropped columns will
not be correctly marked attisdropped; it's a bit surprising that
we've gotten away with that this long. But the real reason for
being concerned with this is that using the table's descriptor means
that the slot will have correct attrmissing data, allowing us to
revert the klugy fix of commit
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5 years ago |
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a04daa97a4 |
Remove es_result_relation_info from EState.
Maintaining 'es_result_relation_info' correctly at all times has become cumbersome, especially with partitioning where each partition gets its own result relation info. Having to set and reset it across arbitrary operations has caused bugs in the past. This changes all the places that used 'es_result_relation_info', to receive the currently active ResultRelInfo via function parameters instead. Author: Amit Langote Discussion: https://www.postgresql.org/message-id/CA%2BHiwqGEmiib8FLiHMhKB%2BCH5dRgHSLc5N5wnvc4kym%2BZYpQEQ%40mail.gmail.com |
5 years ago |
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1375422c78 |
Create ResultRelInfos later in InitPlan, index them by RT index.
Instead of allocating all the ResultRelInfos upfront in one big array, allocate them in ExecInitModifyTable(). es_result_relations is now an array of ResultRelInfo pointers, rather than an array of structs, and it is indexed by the RT index. This simplifies things: we get rid of the separate concept of a "result rel index", and don't need to set it in setrefs.c anymore. This also allows follow-up optimizations (not included in this commit yet) to skip initializing ResultRelInfos for target relations that were not needed at runtime, and removal of the es_result_relation_info pointer. The EState arrays of regular result rels and root result rels are merged into one array. Similarly, the resultRelations and rootResultRelations lists in PlannedStmt are merged into one. It's not actually clear to me why they were kept separate in the first place, but now that the es_result_relations array is indexed by RT index, it certainly seems pointless. The PlannedStmt->resultRelations list is now only needed for ExecRelationIsTargetRelation(). One visible effect of this change is that ExecRelationIsTargetRelation() will now return 'true' also for the partition root, if a partitioned table is updated. That seems like a good thing, although the function isn't used in core code, and I don't see any reason for an FDW to call it on a partition root. Author: Amit Langote Discussion: https://www.postgresql.org/message-id/CA%2BHiwqGEmiib8FLiHMhKB%2BCH5dRgHSLc5N5wnvc4kym%2BZYpQEQ%40mail.gmail.com |
5 years ago |
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200f6100a9 |
Fix LookupTupleHashEntryHash() pipeline-stall issue.
Refactor hash lookups in nodeAgg.c to improve performance. Author: Andres Freund and Jeff Davis Discussion: https://postgr.es/m/20200612213715.op4ye4q7gktqvpuo%40alap3.anarazel.de Backpatch-through: 13 |
5 years ago |
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50a38f6517 |
Create memory context for HashAgg with a reasonable maxBlockSize.
If the memory context's maxBlockSize is too big, a single block allocation can suddenly exceed work_mem. For Hash Aggregation, this can mean spilling to disk too early or reporting a confusing memory usage number for EXPLAN ANALYZE. Introduce CreateWorkExprContext(), which is like CreateExprContext(), except that it creates the AllocSet with a maxBlockSize that is reasonable in proportion to work_mem. Right now, CreateWorkExprContext() is only used by Hash Aggregation, but it may be generally useful in the future. Discussion: https://postgr.es/m/412a3fbf306f84d8d78c4009e11791867e62b87c.camel@j-davis.com |
6 years ago |
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bda6dedbea |
Go back to returning int from ereport auxiliary functions.
This reverts the parts of commit
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6 years ago |
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17a28b0364 |
Improve the internal implementation of ereport().
Change all the auxiliary error-reporting routines to return void, now that we no longer need to pretend they are passing something useful to errfinish(). While this probably doesn't save anything significant at the machine-code level, it allows detection of some additional types of mistakes. Pass the error location details (__FILE__, __LINE__, PG_FUNCNAME_MACRO) to errfinish not errstart. This shaves a few cycles off the case where errstart decides we're not going to emit anything. Re-implement elog() as a trivial wrapper around ereport(), removing the separate support infrastructure it used to have. Aside from getting rid of some now-surplus code, this means that elog() now really does have exactly the same semantics as ereport(), in particular that it can skip evaluation work if the message is not to be emitted. Andres Freund and Tom Lane Discussion: https://postgr.es/m/CA+fd4k6N8EjNvZpM8nme+y+05mz-SM8Z_BgkixzkA34R+ej0Kw@mail.gmail.com |
6 years ago |
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c954d49046 |
Extend ExecBuildAggTrans() to support a NULL pointer check.
Optionally push a step to check for a NULL pointer to the pergroup state. This will be important for disk-based hash aggregation in combination with grouping sets. When memory limits are reached, a given tuple may find its per-group state for some grouping sets but not others. For the former, it advances the per-group state as normal; for the latter, it skips evaluation and the calling code will have to spill the tuple and reprocess it in a later batch. Add the NULL check as a separate expression step because in some common cases it's not needed. Discussion: https://postgr.es/m/20200221202212.ssb2qpmdgrnx52sj%40alap3.anarazel.de |
6 years ago |
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11de6c903d |
Change signature of TupleHashTableHash().
Commit
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6 years ago |
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4eaea3db15 |
Introduce TupleHashTableHash() and LookupTupleHashEntryHash().
Expose two new entry points: one for only calculating the hash value of a tuple, and another for looking up a hash entry when the hash value is already known. This will be useful for disk-based Hash Aggregation to avoid recomputing the hash value for the same tuple after saving and restoring it from disk. Discussion: https://postgr.es/m/37091115219dd522fd9ed67333ee8ed1b7e09443.camel%40j-davis.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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27cc7cd2bc |
Reorder EPQ work, to fix rowmark related bugs and improve efficiency.
In |
6 years ago |
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fb3b098fe8 |
Remove fmgr.h includes from headers that don't really need it.
Most of the fmgr.h includes were obsoleted by
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6 years ago |
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3c926587b5 |
Remove EState.es_range_table_array.
Now that list_nth is O(1), there's no good reason to maintain a separate array of RTE pointers rather than indexing into estate->es_range_table. Deleting the array doesn't save all that much either; but just on cleanliness grounds, it's better not to have duplicate representations of the identical information. Discussion: https://postgr.es/m/14960.1565384592@sss.pgh.pa.us |
6 years ago |
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6b8548964b |
Fix inconsistencies in the code
This addresses a couple of issues in the code: - Typos and inconsistencies in comments and function declarations. - Removal of unreferenced function declarations. - Removal of unnecessary compile flags. - A cleanup error in regressplans.sh. Author: Alexander Lakhin Discussion: https://postgr.es/m/0c991fdf-2670-1997-c027-772a420c4604@gmail.com |
6 years ago |
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92c4abc736 |
Fix assorted inconsistencies.
There were a number of issues in the recent commits which include typos, code and comments mismatch, leftover function declarations. Fix them. Reported-by: Alexander Lakhin Author: Alexander Lakhin, Amit Kapila and Amit Langote Reviewed-by: Amit Kapila Discussion: https://postgr.es/m/ef0c0232-0c1d-3a35-63d4-0ebd06e31387@gmail.com |
6 years ago |
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8255c7a5ee |
Phase 2 pgindent run for v12.
Switch to 2.1 version of pg_bsd_indent. This formats multiline function declarations "correctly", that is with additional lines of parameter declarations indented to match where the first line's left parenthesis is. Discussion: https://postgr.es/m/CAEepm=0P3FeTXRcU5B2W3jv3PgRVZ-kGUXLGfd42FFhUROO3ug@mail.gmail.com |
6 years ago |
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be76af171c |
Initial pgindent run for v12.
This is still using the 2.0 version of pg_bsd_indent. I thought it would be good to commit this separately, so as to document the differences between 2.0 and 2.1 behavior. Discussion: https://postgr.es/m/16296.1558103386@sss.pgh.pa.us |
6 years ago |
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5db6df0c01 |
tableam: Add tuple_{insert, delete, update, lock} and use.
This adds new, required, table AM callbacks for insert/delete/update and lock_tuple. To be able to reasonably use those, the EvalPlanQual mechanism had to be adapted, moving more logic into the AM. Previously both delete/update/lock call-sites and the EPQ mechanism had to have awareness of the specific tuple format to be able to fetch the latest version of a tuple. Obviously that needs to be abstracted away. To do so, move the logic that find the latest row version into the AM. lock_tuple has a new flag argument, TUPLE_LOCK_FLAG_FIND_LAST_VERSION, that forces it to lock the last version, rather than the current one. It'd have been possible to do so via a separate callback as well, but finding the last version usually also necessitates locking the newest version, making it sensible to combine the two. This replaces the previous use of EvalPlanQualFetch(). Additionally HeapTupleUpdated, which previously signaled either a concurrent update or delete, is now split into two, to avoid callers needing AM specific knowledge to differentiate. The move of finding the latest row version into tuple_lock means that encountering a row concurrently moved into another partition will now raise an error about "tuple to be locked" rather than "tuple to be updated/deleted" - which is accurate, as that always happens when locking rows. While possible slightly less helpful for users, it seems like an acceptable trade-off. As part of this commit HTSU_Result has been renamed to TM_Result, and its members been expanded to differentiated between updating and deleting. HeapUpdateFailureData has been renamed to TM_FailureData. The interface to speculative insertion is changed so nodeModifyTable.c does not have to set the speculative token itself anymore. Instead there's a version of tuple_insert, tuple_insert_speculative, that performs the speculative insertion (without requiring a flag to signal that fact), and the speculative insertion is either made permanent with table_complete_speculative(succeeded = true) or aborted with succeeded = false). Note that multi_insert is not yet routed through tableam, nor is COPY. Changing multi_insert requires changes to copy.c that are large enough to better be done separately. Similarly, although simpler, CREATE TABLE AS and CREATE MATERIALIZED VIEW are also only going to be adjusted in a later commit. Author: Andres Freund and Haribabu Kommi Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de https://postgr.es/m/20190313003903.nwvrxi7rw3ywhdel@alap3.anarazel.de https://postgr.es/m/20160812231527.GA690404@alvherre.pgsql |
7 years ago |
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5e1963fb76 |
Collations with nondeterministic comparison
This adds a flag "deterministic" to collations. If that is false, such a collation disables various optimizations that assume that strings are equal only if they are byte-wise equal. That then allows use cases such as case-insensitive or accent-insensitive comparisons or handling of strings with different Unicode normal forms. This functionality is only supported with the ICU provider. At least glibc doesn't appear to have any locales that work in a nondeterministic way, so it's not worth supporting this for the libc provider. The term "deterministic comparison" in this context is from Unicode Technical Standard #10 (https://unicode.org/reports/tr10/#Deterministic_Comparison). This patch makes changes in three areas: - CREATE COLLATION DDL changes and system catalog changes to support this new flag. - Many executor nodes and auxiliary code are extended to track collations. Previously, this code would just throw away collation information, because the eventually-called user-defined functions didn't use it since they only cared about equality, which didn't need collation information. - String data type functions that do equality comparisons and hashing are changed to take the (non-)deterministic flag into account. For comparison, this just means skipping various shortcuts and tie breakers that use byte-wise comparison. For hashing, we first need to convert the input string to a canonical "sort key" using the ICU analogue of strxfrm(). Reviewed-by: Daniel Verite <daniel@manitou-mail.org> Reviewed-by: Peter Geoghegan <pg@bowt.ie> Discussion: https://www.postgresql.org/message-id/flat/1ccc668f-4cbc-0bef-af67-450b47cdfee7@2ndquadrant.com |
7 years ago |
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ad0bda5d24 |
Store tuples for EvalPlanQual in slots, rather than as HeapTuples.
For the upcoming pluggable table access methods it's quite inconvenient to store tuples as HeapTuples, as that'd require converting tuples from a their native format into HeapTuples. Instead use slots to manage epq tuples. To fit into that scheme, change the foreign data wrapper callback RefetchForeignRow, to store the tuple in a slot. Insist on using the caller provided slot, so it conveniently can be stored in the corresponding EPQ slot. As there is no in core user of RefetchForeignRow, that change was done blindly, but we plan to test that soon. To avoid duplicating that work for row locks, move row locks to just directly use the EPQ slots - it previously temporarily stored tuples in LockRowsState.lr_curtuples, but that doesn't seem beneficial, given we'd possibly end up with a significant number of additional slots. The behaviour of es_epqTupleSet[rti -1] is now checked by es_epqTupleSlot[rti -1] != NULL, as that is distinguishable from a slot containing an empty tuple. Author: Andres Freund, Haribabu Kommi, Ashutosh Bapat Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de |
7 years ago |
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ff11e7f4b9 |
Use slots in trigger infrastructure, except for the actual invocation.
In preparation for abstracting table storage, convert trigger.c to track tuples in slots. Which also happens to make code calling triggers simpler. As the calling interface for triggers themselves is not changed in this patch, HeapTuples still are extracted from the slot at that time. But that's handled solely inside trigger.c, not visible to callers. It's quite likely that we'll want to revise the external trigger interface, but that's a separate large project. As part of this work the slots used for old/new/return tuples are moved from EState into ResultRelInfo, as different updated tables might need different slots. The slots are now also now created on-demand, which is good both from an efficiency POV, but also makes the modifying code simpler. Author: Andres Freund, Amit Khandekar and Ashutosh Bapat Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de |
7 years ago |
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317ffdfeaa |
Allow to reset execGrouping.c style tuple hashtables.
This has the advantage that the comparator expression, the table's slot, etc do not have to be rebuilt. Additionally the simplehash.h hashtable within the tuple hashtable now keeps its previous size and doesn't need to be reallocated. That both reduces allocator overhead, and improves performance in cases where the input estimation was off by a significant factor. To avoid an API/ABI break, the new parameter is exposed via the new BuildTupleHashTableExt(), and BuildTupleHashTable() now is a wrapper around the former, that continues to allocate the table itself in the tablecxt. Using this fixes performance issues discovered in the two bugs referenced. This commit however has not converted the callers, that's done in a separate commit. Bug: #15592 #15486 Reported-By: Jakub Janeček, Dmitry Marakasov Author: Andres Freund Discussion: https://postgr.es/m/15486-05850f065da42931@postgresql.org https://postgr.es/m/20190114180423.ywhdg2iagzvh43we@alap3.anarazel.de Backpatch: 11, this is a prerequisite for other fixes |
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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4c850ecec6 |
Don't include heapam.h from others headers.
heapam.h previously was included in a number of widely used headers (e.g. execnodes.h, indirectly in executor.h, ...). That's problematic on its own, as heapam.h contains a lot of low-level details that don't need to be exposed that widely, but becomes more problematic with the upcoming introduction of pluggable table storage - it seems inappropriate for heapam.h to be included that widely afterwards. heapam.h was largely only included in other headers to get the HeapScanDesc typedef (which was defined in heapam.h, even though HeapScanDescData is defined in relscan.h). The better solution here seems to be to just use the underlying struct (forward declared where necessary). Similar for BulkInsertState. Another problem was that LockTupleMode was used in executor.h - parts of the file tried to cope without heapam.h, but due to the fact that it indirectly included it, several subsequent violations of that goal were not not noticed. We could just reuse the approach of declaring parameters as int, but it seems nicer to move LockTupleMode to lockoptions.h - that's not a perfect location, but also doesn't seem bad. As a number of files relied on implicitly included heapam.h, a significant number of files grew an explicit include. It's quite probably that a few external projects will need to do the same. Author: Andres Freund Reviewed-By: Alvaro Herrera Discussion: https://postgr.es/m/20190114000701.y4ttcb74jpskkcfb@alap3.anarazel.de |
7 years ago |