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${ noResults }
86 Commits (1a36bc9dba8eae90963a586d37b6457b32b2fed4)
Author | SHA1 | Message | Date |
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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 |
3 years ago |
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33a377608f |
IS JSON predicate
This patch intrdocuces the SQL standard IS JSON predicate. It operates on text and bytea values representing JSON as well as on the json and jsonb types. Each test has an IS and IS NOT variant. The tests are: IS JSON [VALUE] IS JSON ARRAY IS JSON OBJECT IS JSON SCALAR IS JSON WITH | WITHOUT UNIQUE KEYS These are mostly self-explanatory, but note that IS JSON WITHOUT UNIQUE KEYS is true whenever IS JSON is true, and IS JSON WITH UNIQUE KEYS is true whenever IS JSON is true except it IS JSON OBJECT is true and there are duplicate keys (which is never the case when applied to jsonb values). 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 |
3 years ago |
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f4fb45d15c |
SQL/JSON constructors
This patch introduces the SQL/JSON standard constructors for JSON: JSON() JSON_ARRAY() JSON_ARRAYAGG() JSON_OBJECT() JSON_OBJECTAGG() For the most part these functions provide facilities that mimic existing json/jsonb functions. However, they also offer some useful additional functionality. In addition to text input, the JSON() function accepts bytea input, which it will decode and constuct a json value from. The other functions provide useful options for handling duplicate keys and null values. This series of patches will be followed by a consolidated documentation patch. 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 |
3 years ago |
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f79b803dcc |
Common SQL/JSON clauses
This introduces some of the building blocks used by the SQL/JSON constructor and query functions. Specifically, it provides node executor and grammar support for the FORMAT JSON [ENCODING foo] clause, and values decorated with it, and for the RETURNING clause. The following SQL/JSON patches will leverage these. Nikita Glukhov (who probably deserves an award for perseverance). 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 |
3 years ago |
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1460fc5942 |
Revert "Common SQL/JSON clauses"
This reverts commit
|
3 years ago |
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865fe4d5df |
Common SQL/JSON clauses
This introduces some of the building blocks used by the SQL/JSON constructor and query functions. Specifically, it provides node executor and grammar support for the FORMAT JSON [ENCODING foo] clause, and values decorated with it, and for the RETURNING clause. The following SQL/JSON patches will leverage these. Nikita Glukhov (who probably deserves an award for perseverance). Reviewers have included (in no particular order) Andres Freund, Alexander Korotkov, Pavel Stehule, Andrew Alsup. Erik Rijkers, Zihong Yu and Himanshu Upadhyaya. Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru |
3 years ago |
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ec62cb0aac |
Revert applying column aliases to the output of whole-row Vars.
In commit |
3 years ago |
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27b77ecf9f |
Update copyright for 2022
Backpatch-through: 10 |
4 years ago |
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bbc227e951 |
Always use ReleaseTupleDesc after lookup_rowtype_tupdesc et al.
The API spec for lookup_rowtype_tupdesc previously said you could use either ReleaseTupleDesc or DecrTupleDescRefCount. However, the latter choice means the caller must be certain that the returned tupdesc is refcounted. I don't recall right now whether that was always true when this spec was written, but it's certainly not always true since we introduced shared record typcaches for parallel workers. That means that callers using DecrTupleDescRefCount are dependent on typcache behavior details that they probably shouldn't be. Hence, change the API spec to say that you must call ReleaseTupleDesc, and fix the half-dozen callers that weren't. AFAICT this is just future-proofing, there's no live bug here. So no back-patch. Per gripe from Chapman Flack. Discussion: https://postgr.es/m/61B901A4.1050808@anastigmatix.net |
4 years ago |
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01fc652703 |
Fix variable lifespan in ExecInitCoerceToDomain().
This undoes a mistake in 1ec7679f1: domainval and domainnull were meant to live across loop iterations, but they were incorrectly moved inside the loop. The effect was only to emit useless extra EEOP_MAKE_READONLY steps, so it's not a big deal; nonetheless, back-patch to v13 where the mistake was introduced. Ranier Vilela Discussion: https://postgr.es/m/CAEudQAqXuhbkaAp-sGH6dR6Nsq7v28_0TPexHOm6FiDYqwQD-w@mail.gmail.com |
4 years ago |
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3e310d837a |
Fix assignment to array of domain over composite.
An update such as "UPDATE ... SET fld[n].subfld = whatever" failed if the array elements were domains rather than plain composites. That's because isAssignmentIndirectionExpr() failed to cope with the CoerceToDomain node that would appear in the expression tree in this case. The result would typically be a crash, and even if we accidentally didn't crash, we'd not correctly preserve other fields of the same array element. Per report from Onder Kalaci. Back-patch to v11 where arrays of domains came in. Discussion: https://postgr.es/m/PH0PR21MB132823A46AA36F0685B7A29AD8BD9@PH0PR21MB1328.namprd21.prod.outlook.com |
4 years ago |
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d9a38c52ce |
Rename NodeTag of ExprState
Rename from tag to type, for consistency with all other node structs. Discussion: https://www.postgresql.org/message-id/flat/c1097590-a6a4-486a-64b1-e1f9cc0533ce@enterprisedb.com |
4 years ago |
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29f45e299e |
Use a hash table to speed up NOT IN(values)
Similar to
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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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c2db458c10 |
Redesign the caching done by get_cached_rowtype().
Previously, get_cached_rowtype() cached a pointer to a reference-counted
tuple descriptor from the typcache, relying on the ExprContextCallback
mechanism to release the tupdesc refcount when the expression tree
using the tupdesc was destroyed. This worked fine when it was designed,
but the introduction of within-DO-block COMMITs broke it. The refcount
is logged in a transaction-lifespan resource owner, but plpgsql won't
destroy simple expressions made within the DO block (before its first
commit) until the DO block is exited. That results in a warning about
a leaked tupdesc refcount when the COMMIT destroys the original resource
owner, and then an error about the active resource owner not holding a
matching refcount when the expression is destroyed.
To fix, get rid of the need to have a shutdown callback at all, by
instead caching a pointer to the relevant typcache entry. Those
survive for the life of the backend, so we needn't worry about the
pointer becoming stale. (For registered RECORD types, we can still
cache a pointer to the tupdesc, knowing that it won't change for the
life of the backend.) This mechanism has been in use in plpgsql
and expandedrecord.c since commit
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4 years ago |
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50e17ad281 |
Speedup ScalarArrayOpExpr evaluation
ScalarArrayOpExprs with "useOr=true" and a set of Consts on the righthand side have traditionally been evaluated by using a linear search over the array. When these arrays contain large numbers of elements then this linear search could become a significant part of execution time. Here we add a new method of evaluating ScalarArrayOpExpr expressions to allow them to be evaluated by first building a hash table containing each element, then on subsequent evaluations, we just probe that hash table to determine if there is a match. The planner is in charge of determining when this optimization is possible and it enables it by setting hashfuncid in the ScalarArrayOpExpr. The executor will only perform the hash table evaluation when the hashfuncid is set. This means that not all cases are optimized. For example CHECK constraints containing an IN clause won't go through the planner, so won't get the hashfuncid set. We could maybe do something about that at some later date. The reason we're not doing it now is from fear that we may slow down cases where the expression is evaluated only once. Those cases can be common, for example, a single row INSERT to a table with a CHECK constraint containing an IN clause. In the planner, we enable this when there are suitable hash functions for the ScalarArrayOpExpr's operator and only when there is at least MIN_ARRAY_SIZE_FOR_HASHED_SAOP elements in the array. The threshold is currently set to 9. Author: James Coleman, David Rowley Reviewed-by: David Rowley, Tomas Vondra, Heikki Linnakangas Discussion: https://postgr.es/m/CAAaqYe8x62+=wn0zvNKCj55tPpg-JBHzhZFFc6ANovdqFw7-dA@mail.gmail.com |
4 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 |
4 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 |
4 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 |
4 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 |
4 years ago |
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a3367aa3c4 |
Don't add bailout adjustment for non-strict deserialize calls.
When building aggregate expression steps, strict checks need a bailout jump for when a null value is encountered, so there is a list of steps that require later adjustment. Adding entries to that list for steps that aren't actually strict would be harmless, except that there is an Assert which catches them. This leads to spurious errors on asserts builds, for data sets that trigger parallel aggregation of an aggregate with a non-strict deserialization function (no such aggregates exist in the core system). Repair by not adding the adjustment entry when it's not needed. Backpatch back to 11 where the code was introduced. Per a report from Darafei (Komzpa) of the PostGIS project; analysis and patch by me. Discussion: https://postgr.es/m/87mty7peb3.fsf@news-spur.riddles.org.uk |
4 years ago |
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ca3b37487b |
Update copyright for 2021
Backpatch-through: 9.5 |
5 years ago |
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653aa603f5 |
Provide an error cursor for "can't subscript" error messages.
Commit
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5 years ago |
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c7aba7c14e |
Support subscripting of arbitrary types, not only arrays.
This patch generalizes the subscripting infrastructure so that any data type can be subscripted, if it provides a handler function to define what that means. Traditional variable-length (varlena) arrays all use array_subscript_handler(), while the existing fixed-length types that support subscripting use raw_array_subscript_handler(). It's expected that other types that want to use subscripting notation will define their own handlers. (This patch provides no such new features, though; it only lays the foundation for them.) To do this, move the parser's semantic processing of subscripts (including coercion to whatever data type is required) into a method callback supplied by the handler. On the execution side, replace the ExecEvalSubscriptingRef* layer of functions with direct calls to callback-supplied execution routines. (Thus, essentially no new run-time overhead should be caused by this patch. Indeed, there is room to remove some overhead by supplying specialized execution routines. This patch does a little bit in that line, but more could be done.) Additional work is required here and there to remove formerly hard-wired assumptions about the result type, collation, etc of a SubscriptingRef expression node; and to remove assumptions that the subscript values must be integers. One useful side-effect of this is that we now have a less squishy mechanism for identifying whether a data type is a "true" array: instead of wiring in weird rules about typlen, we can look to see if pg_type.typsubscript == F_ARRAY_SUBSCRIPT_HANDLER. For this to be bulletproof, we have to forbid user-defined types from using that handler directly; but there seems no good reason for them to do so. This patch also removes assumptions that the number of subscripts is limited to MAXDIM (6), or indeed has any hard-wired limit. That limit still applies to types handled by array_subscript_handler or raw_array_subscript_handler, but to discourage other dependencies on this constant, I've moved it from c.h to utils/array.h. Dmitry Dolgov, reviewed at various times by Tom Lane, Arthur Zakirov, Peter Eisentraut, Pavel Stehule Discussion: https://postgr.es/m/CA+q6zcVDuGBv=M0FqBYX8DPebS3F_0KQ6OVFobGJPM507_SZ_w@mail.gmail.com Discussion: https://postgr.es/m/CA+q6zcVovR+XY4mfk-7oNk-rF91gH0PebnNfuUjuuDsyHjOcVA@mail.gmail.com |
5 years ago |
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0a2bc5d61e |
Move per-agg and per-trans duplicate finding to the planner.
This has the advantage that the cost estimates for aggregates can count the number of calls to transition and final functions correctly. Bump catalog version, because views can contain Aggrefs. Reviewed-by: Andres Freund Discussion: https://www.postgresql.org/message-id/b2e3536b-1dbc-8303-c97e-89cb0b4a9a48%40iki.fi |
5 years ago |
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8a15e735be |
Fix some grammar and typos in comments and docs
The documentation fixes are backpatched down to where they apply. Author: Justin Pryzby Discussion: https://postgr.es/m/20201031020801.GD3080@telsasoft.com Backpatch-through: 9.6 |
5 years ago |
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41efb83408 |
Move resolution of AlternativeSubPlan choices to the planner.
When commit
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5 years ago |
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5cbfce562f |
Initial pgindent and pgperltidy run for v13.
Includes some manual cleanup of places that pgindent messed up,
most of which weren't per project style anyway.
Notably, it seems some people didn't absorb the style rules of
commit
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5 years ago |
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dd0f37ecce |
Fix collection of typos and grammar mistakes in the tree
This fixes some comments and documentation new as of Postgres 13. Author: Justin Pryzby Discussion: https://postgr.es/m/20200408165653.GF2228@telsasoft.com |
5 years ago |
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3c173a53a8 |
Remove utils/acl.h from catalog/objectaddress.h
The need for this was removed by
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5 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 |
5 years ago |
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2742c45080 |
expression eval: Reduce number of steps for agg transition invocations.
Do so by combining the various steps that are part of aggregate transition function invocation into one larger step. As some of the current steps are only necessary for some aggregates, have one variant of the aggregate transition step for each possible combination. To avoid further manual copies of code in the different transition step implementations, move most of the code into helper functions marked as "always inline". The benefit of this change is an increase in performance when aggregating lots of rows. This comes in part due to the reduced number of indirect jumps due to the reduced number of steps, and in part by reducing redundant setup code across steps. This mainly benefits interpreted execution, but the code generated by JIT is also improved a bit. As a nice side-effect it also ends up making the code a bit simpler. A small additional optimization is removing the need to set aggstate->curaggcontext before calling ExecAggInitGroup, choosing to instead passign curaggcontext as an argument. It was, in contrast to other aggregate related functions, only needed to fetch a memory context to copy the transition value into. Author: Andres Freund Discussion: https://postgr.es/m/20191023163849.sosqbfs5yenocez3@alap3.anarazel.de https://postgr.es/m/5c371df7cee903e8cd4c685f90c6c72086d3a2dc.camel@j-davis.com |
5 years ago |
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1fdb7f9789 |
expression eval: Don't redundantly keep track of AggState.
It's already tracked via ExprState->parent, so we don't need to also
include it in ExprEvalStep. When that code originally was written
ExprState->parent didn't exist, but it since has been introduced in
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5 years ago |
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1ec7679f1b |
expression eval, jit: Minor code cleanups.
This mostly consists of using C99 style for loops, moving variables into narrower scopes, and a smattering of other minor improvements. Done separately to make it easier to review patches with actual functional changes. Author: Andres Freund Discussion: https://postgr.es/m/20191023163849.sosqbfs5yenocez3@alap3.anarazel.de |
5 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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181932a032 |
Remove redundant not-null test
Reported-by: Ranier Vilela Discussion: https://postgr.es/m/MN2PR18MB2927E73FADCA8967B2302469E3490@MN2PR18MB2927.namprd18.prod.outlook.com Author: Ranier Vilela Backpatch-through: master |
6 years ago |
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36d22dd95b |
Don't generate EEOP_*_FETCHSOME operations for slots know to be virtual.
That avoids unnecessary work during both interpreted execution, and JIT compiled expression evaluation. Both benefit from fewer expression steps needing be processed, and for interpreted execution there now is a fastpath dedicated to just fetching a value from a virtual slot. That's e.g. beneficial for hashjoins over nodes that perform projections, as the hashed columns are currently fetched individually. Author: Soumyadeep Chakraborty, Andres Freund Discussion: https://postgr.es/m/CAE-ML+9OKSN71+mHtfMD-L24oDp8dGTfaVjDU6U+j+FNAW5kRQ@mail.gmail.com |
6 years ago |
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97e971ee05 |
Fix determination when slot types for upper executor nodes are fixed.
For many queries the fact that the tuple descriptor from the lower node was not taken into account when determining whether the type of a slot is fixed, lead to tuple deforming for such upper nodes not to be JIT accelerated. I broke this in |
6 years ago |
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30d1379658 |
Fix ExprState's tag to be of type NodeTag rather than Node.
This appears to have been an oversight in
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6 years ago |
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c96581abe4 |
Fix inconsistencies and typos in the tree, take 11
This fixes various typos in docs and comments, and removes some orphaned definitions. Author: Alexander Lakhin Discussion: https://postgr.es/m/5da8e325-c665-da95-21e0-c8a99ea61fbf@gmail.com |
6 years ago |
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6a04d345fd |
Don't include utils/array.h from acl.h.
For most uses of acl.h the details of how "Acl" internally looks like are irrelevant. It might make sense to move a lot of the implementation details into a separate header at a later point. The main motivation of this change is to avoid including fmgr.h (via array.h, which needs it for exposed structs) in a lot of files that otherwise don't need it. A subsequent commit will remove the fmgr.h include from a lot of files. Directly include utils/array.h and utils/expandeddatum.h from the files that need them, but previously included them indirectly, via acl.h. Author: Andres Freund Discussion: https://postgr.es/m/20190803193733.g3l3x3o42uv4qj7l@alap3.anarazel.de |
6 years ago |
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d97b714a21 |
Avoid using lcons and list_delete_first where it's easy to do so.
Formerly, lcons was about the same speed as lappend, but with the new List implementation, that's not so; with a long List, data movement imposes an O(N) cost on lcons and list_delete_first, but not lappend. Hence, invent list_delete_last with semantics parallel to list_delete_first (but O(1) cost), and change various places to use lappend and list_delete_last where this can be done without much violence to the code logic. There are quite a few places that construct result lists using lcons not lappend. Some have semantic rationales for that; I added comments about it to a couple that didn't have them already. In many such places though, I think the coding is that way only because back in the dark ages lcons was faster than lappend. Hence, switch to lappend where this can be done without causing semantic changes. In ExecInitExprRec(), this results in aggregates and window functions that are in the same plan node being executed in a different order than before. Generally, the executions of such functions ought to be independent of each other, so this shouldn't result in visibly different query results. But if you push it, as one regression test case does, you can show that the order is different. The new order seems saner; it's closer to the order of the functions in the query text. And we never documented or promised anything about this, anyway. Also, in gistfinishsplit(), don't bother building a reverse-order list; it's easy now to iterate backwards through the original list. It'd be possible to go further towards removing uses of lcons and list_delete_first, but it'd require more extensive logic changes, and I'm not convinced it's worth it. Most of the remaining uses deal with queues that probably never get long enough to be worth sweating over. (Actually, I doubt that any of the changes in this patch will have measurable performance effects either. But better to have good examples than bad ones in the code base.) Patch by me, thanks to David Rowley and Daniel Gustafsson for review. Discussion: https://postgr.es/m/21272.1563318411@sss.pgh.pa.us |
6 years ago |
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c74d49d41c |
Fix many typos and inconsistencies
Author: Alexander Lakhin Discussion: https://postgr.es/m/af27d1b3-a128-9d62-46e0-88f424397f44@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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7e19929ea2 |
Fix duplicated words in comments
Author: Stephen Amell Discussion: https://postgr.es/m/539fa271-21b3-777e-a468-d96cffe9c768@gmail.com |
6 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 |
6 years ago |
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c94fb8e8ac |
Standardize some more loops that chase down parallel lists.
We have forboth() and forthree() macros that simplify iterating through several parallel lists, but not everyplace that could reasonably use those was doing so. Also invent forfour() and forfive() macros to do the same for four or five parallel lists, and use those where applicable. The immediate motivation for doing this is to reduce the number of ad-hoc lnext() calls, to reduce the footprint of a WIP patch. However, it seems like good cleanup and error-proofing anyway; the places that were combining forthree() with a manually iterated loop seem particularly illegible and bug-prone. There was some speculation about restructuring related parsetree representations to reduce the need for parallel list chasing of this sort. Perhaps that's a win, or perhaps not, but in any case it would be considerably more invasive than this patch; and it's not particularly related to my immediate goal of improving the List infrastructure. So I'll leave that question for another day. Patch by me; thanks to David Rowley for review. Discussion: https://postgr.es/m/11587.1550975080@sss.pgh.pa.us |
6 years ago |
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558d77f20e |
Renaming for new subscripting mechanism
Over at patch https://commitfest.postgresql.org/21/1062/ Dmitry wants to introduce a more generic subscription mechanism, which allows subscripting not only arrays but also other object types such as JSONB. That functionality is introduced in a largish invasive patch, out of which this internal renaming patch was extracted. Author: Dmitry Dolgov Reviewed-by: Tom Lane, Arthur Zakirov Discussion: https://postgr.es/m/CA+q6zcUK4EqPAu7XRRO5CCjMwhz5zvg+rfWuLzVoxp_5sKS6=w@mail.gmail.com |
7 years ago |
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f09346a9c6 |
Refactor planner's header files.
Create a new header optimizer/optimizer.h, which exposes just the planner functions that can be used "at arm's length", without need to access Paths or the other planner-internal data structures defined in nodes/relation.h. This is intended to provide the whole planner API seen by most of the rest of the system; although FDWs still need to use additional stuff, and more thought is also needed about just what selfuncs.c should rely on. The main point of doing this now is to limit the amount of new #include baggage that will be needed by "planner support functions", which I expect to introduce later, and which will be in relevant datatype modules rather than anywhere near the planner. This commit just moves relevant declarations into optimizer.h from other header files (a couple of which go away because everything got moved), and adjusts #include lists to match. There's further cleanup that could be done if we want to decide that some stuff being exposed by optimizer.h doesn't belong in the planner at all, but I'll leave that for another day. Discussion: https://postgr.es/m/11460.1548706639@sss.pgh.pa.us |
7 years ago |