| Commit message (Collapse) | Author | Age |
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In the historical implementation of SQL functions (if they don't get
inlined), we built plans for all the contained queries at first call
within an outer query, and then re-used those plans for the duration
of the outer query, and then forgot everything. This was not ideal,
not least because the plans could not be customized to specific values
of the function's parameters. Our plancache infrastructure seems
mature enough to be used here. That will solve both the problem with
not being able to build custom plans and the problem with not being
able to share work across successive outer queries.
Aside from those performance concerns, this change fixes a
longstanding bugaboo with SQL functions: you could not write DDL that
would affect later statements in the same function. That's mostly
still true with new-style SQL functions, since the results of parse
analysis are baked into the stored query trees (and protected by
dependency records). But for old-style SQL functions, it will now
work much as it does with PL/pgSQL functions, because we delay parse
analysis and planning of each query until we're ready to run it.
Some edge cases that require replanning are now handled better too;
see for example the new rowsecurity test, where we now detect an RLS
context change that was previously missed.
One other edge-case change that might be worthy of a release note
is that we now insist that a SQL function's result be generated
by the physically-last query within it. Previously, if the last
original query was deleted by a DO INSTEAD NOTHING rule, we'd be
willing to take the result from the preceding query instead.
This behavior was undocumented except in source-code comments,
and it seems hard to believe that anyone's relying on it.
Along the way to this feature, we needed a few infrastructure changes:
* The plancache can now take either a raw parse tree or an
analyzed-but-not-rewritten Query as the starting point for a
CachedPlanSource. If given a Query, it is caller's responsibility
that nothing will happen to invalidate that form of the query.
We use this for new-style SQL functions, where what's in pg_proc is
serialized Query(s) and we trust the dependency mechanism to disallow
DDL that would break those.
* The plancache now offers a way to invoke a post-rewrite callback
to examine/modify the rewritten parse tree when it is rebuilding
the parse trees after a cache invalidation. We need this because
SQL functions sometimes adjust the parse tree to make its output
exactly match the declared result type; if the plan gets rebuilt,
that has to be re-done.
* There is a new backend module utils/cache/funccache.c that
abstracts the idea of caching data about a specific function
usage (a particular function and set of input data types).
The code in it is moved almost verbatim from PL/pgSQL, which
has done that for a long time. We use that logic now for
SQL-language functions too, and maybe other PLs will have use
for it in the future.
Author: Alexander Pyhalov <a.pyhalov@postgrespro.ru>
Co-authored-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
Discussion: https://postgr.es/m/8216639.NyiUUSuA9g@aivenlaptop
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This was left out of the original patch for virtual generated columns
(commit 83ea6c54025).
This just involves a bit of extra work in the executor to expand the
generation expressions and run a "IS NOT NULL" test against them.
There is also a bit of work to make sure that not-null constraints are
checked during a table rewrite.
Author: jian he <jian.universality@gmail.com>
Reviewed-by: Xuneng Zhou <xunengzhou@gmail.com>
Reviewed-by: Navneet Kumar <thanit3111@gmail.com>
Reviewed-by: Álvaro Herrera <alvherre@alvh.no-ip.org>
Discussion: https://postgr.es/m/CACJufxHArQysbDkWFmvK+D1TPHQWWTxWN15cMuUaTYX3xhQXgg@mail.gmail.com
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Reduces memory required for hash aggregation by avoiding an allocation
and a pointer in the TupleHashEntryData structure. That structure is
used for all buckets, whether occupied or not, so the savings is
substantial.
Discussion: https://postgr.es/m/AApHDvpN4v3t_sdz4dvrv1Fx_ZPw=twSnxuTEytRYP7LFz5K9A@mail.gmail.com
Reviewed-by: David Rowley <dgrowleyml@gmail.com>
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Allows an "extra" argument that allocates extra memory at the end of
the MinimalTuple. This is important for callers that need to store
additional data, but do not want to perform an additional allocation.
Suggested-by: David Rowley <dgrowleyml@gmail.com>
Discussion: https://postgr.es/m/CAApHDvppeqw2pNM-+ahBOJwq2QmC0hOAGsmCpC89QVmEoOvsdg@mail.gmail.com
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Refactor for upcoming optimizations.
Reviewed-by: David Rowley <dgrowleyml@gmail.com>
Discussion: https://postgr.es/m/1cc3b400a0e8eead18ff967436fa9e42c0c14cfb.camel@j-davis.com
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Commit cbc127917e introduced tracking of unpruned relids to avoid
processing pruned relations, and changed ExecInitModifyTable() to
initialize only unpruned result relations. As a result, MERGE
statements that prune all target partitions can now lead to crashes
or incorrect behavior during execution.
The crash occurs because some executor code paths rely on
ModifyTableState.resultRelInfo[0] being present and initialized,
even when no result relations remain after pruning. For example,
ExecMerge() and ExecMergeNotMatched() use the first resultRelInfo
to determine the appropriate action. Similarly,
ExecInitPartitionInfo() assumes that at least one result relation
exists.
To preserve these assumptions, ExecInitModifyTable() now includes the
first result relation in the initialized result relation list if all
result relations for that ModifyTable were pruned. To enable that,
ExecDoInitialPruning() ensures the first relation is locked if it was
pruned and locking is necessary.
To support this exception to the pruning logic, PlannedStmt now
includes a list of RT indexes identifying the first result relation
of each ModifyTable node in the plan. This allows
ExecDoInitialPruning() to check whether each such relation was
pruned and, if so, lock it if necessary.
Bug: #18830
Reported-by: Robins Tharakan <tharakan@gmail.com>
Diagnozed-by: Tender Wang <tndrwang@gmail.com>
Diagnozed-by: Dean Rasheed <dean.a.rasheed@gmail.com>
Co-authored-by: Dean Rasheed <dean.a.rasheed@gmail.com>
Reviewed-by: Tender Wang <tndrwang@gmail.com>
Reviewed-by: Dean Rasheed <dean.a.rasheed@gmail.com>
Discussion: https://postgr.es/m/18830-1f31ea1dc930d444%40postgresql.org
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Expose the count of index searches/index descents in EXPLAIN ANALYZE's
output for index scan/index-only scan/bitmap index scan nodes. This
information is particularly useful with scans that use ScalarArrayOp
quals, where the number of index searches can be unpredictable due to
implementation details that interact with physical index characteristics
(at least with nbtree SAOP scans, since Postgres 17 commit 5bf748b8).
The information shown also provides useful context when EXPLAIN ANALYZE
runs a plan with an index scan node that successfully applied the skip
scan optimization (set to be added to nbtree by an upcoming patch).
The instrumentation works by teaching all index AMs to increment a new
nsearches counter whenever a new index search begins. The counter is
incremented at exactly the same point that index AMs already increment
the pg_stat_*_indexes.idx_scan counter (we're counting the same event,
but at the scan level rather than the relation level). Parallel queries
have workers copy their local counter struct into shared memory when an
index scan node ends -- even when it isn't a parallel aware scan node.
An earlier version of this patch that only worked with parallel aware
scans became commit 5ead85fb (though that was quickly reverted by commit
d00107cd following "debug_parallel_query=regress" buildfarm failures).
Our approach doesn't match the approach used when tracking other index
scan related costs (e.g., "Rows Removed by Filter:"). It is comparable
to the approach used in similar cases involving costs that are only
readily accessible inside an access method, not from the executor proper
(e.g., "Heap Blocks:" output for a Bitmap Heap Scan, which was recently
enhanced to show per-worker costs by commit 5a1e6df3, using essentially
the same scheme as the one used here). It is necessary for index AMs to
have direct responsibility for maintaining the new counter, since the
counter might need to be incremented multiple times per amgettuple call
(or per amgetbitmap call). But it is also necessary for the executor
proper to manage the shared memory now used to transfer each worker's
counter struct to the leader.
Author: Peter Geoghegan <pg@bowt.ie>
Reviewed-By: Robert Haas <robertmhaas@gmail.com>
Reviewed-By: Tomas Vondra <tomas@vondra.me>
Reviewed-By: Masahiro Ikeda <ikedamsh@oss.nttdata.com>
Reviewed-By: Matthias van de Meent <boekewurm+postgres@gmail.com>
Discussion: https://postgr.es/m/CAH2-WzkRqvaqR2CTNqTZP0z6FuL4-3ED6eQB0yx38XBNj1v-4Q@mail.gmail.com
Discussion: https://postgr.es/m/CAH2-Wz=PKR6rB7qbx+Vnd7eqeB5VTcrW=iJvAsTsKbdG+kW_UA@mail.gmail.com
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Many STRICT function calls will have one or two arguments, in which
case we can speed up checking for NULL input by avoiding setting up
a loop over the arguments. This adds EEOP_FUNCEXPR_STRICT_1 and the
corresponding EEOP_FUNCEXPR_STRICT_2 for functions with one and two
arguments respectively.
Author: Andres Freund <andres@anarazel.de>
Co-authored-by: Daniel Gustafsson <daniel@yesql.se>
Reviewed-by: Andreas Karlsson <andreas@proxel.se>
Discussion: https://postgr.es/m/415721CE-7D2E-4B74-B5D9-1950083BA03E@yesql.se
Discussion: https://postgr.es/m/20191023163849.sosqbfs5yenocez3@alap3.anarazel.de
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Knowing when the side-effects of an expression is the intended result
of the execution, rather than the returnvalue, is important for being
able generate more efficient JITed code. This replaces EEOP_DONE with
two new steps: EEOP_DONE_RETURN and EEOP_DONE_NO_RETURN. Expressions
which return a value should use the former step; expressions used for
their side-effects which don't return value should use the latter.
Author: Andres Freund <andres@anarazel.de>
Co-authored-by: Daniel Gustafsson <daniel@yesql.se>
Reviewed-by: Andreas Karlsson <andreas@proxel.se>
Discussion: https://postgr.es/m/415721CE-7D2E-4B74-B5D9-1950083BA03E@yesql.se
Discussion: https://postgr.es/m/20191023163849.sosqbfs5yenocez3@alap3.anarazel.de
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Before executing a cached generic plan, AcquireExecutorLocks() in
plancache.c locks all relations in a plan's range table to ensure the
plan is safe for execution. However, this locks runtime-prunable
relations that will later be pruned during "initial" runtime pruning,
introducing unnecessary overhead.
This commit defers locking for such relations to executor startup and
ensures that if the CachedPlan is invalidated due to concurrent DDL
during this window, replanning is triggered. Deferring these locks
avoids unnecessary locking overhead for pruned partitions, resulting
in significant speedup, particularly when many partitions are pruned
during initial runtime pruning.
* Changes to locking when executing generic plans:
AcquireExecutorLocks() now locks only unprunable relations, that is,
those found in PlannedStmt.unprunableRelids (introduced in commit
cbc127917e), to avoid locking runtime-prunable partitions
unnecessarily. The remaining locks are taken by
ExecDoInitialPruning(), which acquires them only for partitions that
survive pruning.
This deferral does not affect the locks required for permission
checking in InitPlan(), which takes place before initial pruning.
ExecCheckPermissions() now includes an Assert to verify that all
relations undergoing permission checks, none of which can be in the
set of runtime-prunable relations, are properly locked.
* Plan invalidation handling:
Deferring locks introduces a window where prunable relations may be
altered by concurrent DDL, invalidating the plan. A new function,
ExecutorStartCachedPlan(), wraps ExecutorStart() to detect and handle
invalidation caused by deferred locking. If invalidation occurs,
ExecutorStartCachedPlan() updates CachedPlan using the new
UpdateCachedPlan() function and retries execution with the updated
plan. To ensure all code paths that may be affected by this handle
invalidation properly, all callers of ExecutorStart that may execute a
PlannedStmt from a CachedPlan have been updated to use
ExecutorStartCachedPlan() instead.
UpdateCachedPlan() replaces stale plans in CachedPlan.stmt_list. A new
CachedPlan.stmt_context, created as a child of CachedPlan.context,
allows freeing old PlannedStmts while preserving the CachedPlan
structure and its statement list. This ensures that loops over
statements in upstream callers of ExecutorStartCachedPlan() remain
intact.
ExecutorStart() and ExecutorStart_hook implementations now return a
boolean value indicating whether plan initialization succeeded with a
valid PlanState tree in QueryDesc.planstate, or false otherwise, in
which case QueryDesc.planstate is NULL. Hook implementations are
required to call standard_ExecutorStart() at the beginning, and if it
returns false, they should do the same without proceeding.
* Testing:
To verify these changes, the delay_execution module tests scenarios
where cached plans become invalid due to changes in prunable relations
after deferred locks.
* Note to extension authors:
ExecutorStart_hook implementations must verify plan validity after
calling standard_ExecutorStart(), as explained earlier. For example:
if (prev_ExecutorStart)
plan_valid = prev_ExecutorStart(queryDesc, eflags);
else
plan_valid = standard_ExecutorStart(queryDesc, eflags);
if (!plan_valid)
return false;
<extension-code>
return true;
Extensions accessing child relations, especially prunable partitions,
via ExecGetRangeTableRelation() must now ensure their RT indexes are
present in es_unpruned_relids (introduced in commit cbc127917e), or
they will encounter an error. This is a strict requirement after this
change, as only relations in that set are locked.
The idea of deferring some locks to executor startup, allowing locks
for prunable partitions to be skipped, was first proposed by Tom Lane.
Reviewed-by: Robert Haas <robertmhaas@gmail.com> (earlier versions)
Reviewed-by: David Rowley <dgrowleyml@gmail.com> (earlier versions)
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us> (earlier versions)
Reviewed-by: Tomas Vondra <tomas@vondra.me>
Reviewed-by: Junwang Zhao <zhjwpku@gmail.com>
Discussion: https://postgr.es/m/CA+HiwqFGkMSge6TgC9KQzde0ohpAycLQuV7ooitEEpbKB0O_mg@mail.gmail.com
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wal_buffers_full has been introduced in pg_stat_wal in 8d9a935965f, as
some information providing metrics for the tuning of the GUC
wal_buffers. WalUsage has been introduced before that in df3b181499.
Moving this field is proving to be beneficial for several reasons:
- This information can now be made available in more layers, providing
more granularity than just pg_stat_wal, on a per-query basis: EXPLAIN,
pgss and VACUUM/ANALYZE logs.
- A patch is under discussion to provide statistics for WAL at backend
level, and this move simplifies a bit the handling of pending
statistics. The remaining data in PgStat_PendingWalStats now relates to
write/sync counters and times, with equivalents present in pg_stat_io,
that backend statistics are able to already track. So this should cut
all the dependencies between PgStat_PendingWalStats and WAL stats at
backend level.
As of this change, wal_buffers_full only shows in pg_stat_wal.
Author: Bertrand Drouvot
Reviewed-by: Ilia Evdokimov
Discussion: https://postgr.es/m/Z6SOha5YFFgvpwQY@ip-10-97-1-34.eu-west-3.compute.internal
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If a read/write expanded variable is declared locally to the
assignment statement that is updating it, and it is referenced
exactly once in the assignment RHS, then we can optimize the
operation as a direct update of the expanded value, whether
or not the function(s) operating on it can be trusted not to
modify the value before throwing an error. This works because
if an error does get thrown, we no longer care what value the
variable has.
In cases where that doesn't work, fall back to the previous
rule that checks for safety of the top-level function.
In any case, postpone determination of whether these optimizations
are feasible until we are executing a Param referencing the target
variable and that variable holds a R/W expanded object. While the
previous incarnation of exec_check_rw_parameter was pretty cheap,
this is a bit less so, and our plan to invoke support functions
will make it even less so. So avoiding the check for variables
where it couldn't be useful should be a win.
Author: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Andrey Borodin <x4mmm@yandex-team.ru>
Reviewed-by: Pavel Borisov <pashkin.elfe@gmail.com>
Discussion: https://postgr.es/m/CACxu=vJaKFNsYxooSnW1wEgsAO5u_v1XYBacfVJ14wgJV_PYeg@mail.gmail.com
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This adds a new variant of generated columns that are computed on read
(like a view, unlike the existing stored generated columns, which are
computed on write, like a materialized view).
The syntax for the column definition is
... GENERATED ALWAYS AS (...) VIRTUAL
and VIRTUAL is also optional. VIRTUAL is the default rather than
STORED to match various other SQL products. (The SQL standard makes
no specification about this, but it also doesn't know about VIRTUAL or
STORED.) (Also, virtual views are the default, rather than
materialized views.)
Virtual generated columns are stored in tuples as null values. (A
very early version of this patch had the ambition to not store them at
all. But so much stuff breaks or gets confused if you have tuples
where a column in the middle is completely missing. This is a
compromise, and it still saves space over being forced to use stored
generated columns. If we ever find a way to improve this, a bit of
pg_upgrade cleverness could allow for upgrades to a newer scheme.)
The capabilities and restrictions of virtual generated columns are
mostly the same as for stored generated columns. In some cases, this
patch keeps virtual generated columns more restricted than they might
technically need to be, to keep the two kinds consistent. Some of
that could maybe be relaxed later after separate careful
considerations.
Some functionality that is currently not supported, but could possibly
be added as incremental features, some easier than others:
- index on or using a virtual column
- hence also no unique constraints on virtual columns
- extended statistics on virtual columns
- foreign-key constraints on virtual columns
- not-null constraints on virtual columns (check constraints are supported)
- ALTER TABLE / DROP EXPRESSION
- virtual column cannot have domain type
- virtual columns are not supported in logical replication
The tests in generated_virtual.sql have been copied over from
generated_stored.sql with the keyword replaced. This way we can make
sure the behavior is mostly aligned, and the differences can be
visible. Some tests for currently not supported features are
currently commented out.
Reviewed-by: Jian He <jian.universality@gmail.com>
Reviewed-by: Dean Rasheed <dean.a.rasheed@gmail.com>
Tested-by: Shlok Kyal <shlok.kyal.oss@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/a368248e-69e4-40be-9c07-6c3b5880b0a6@eisentraut.org
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This commit introduces changes to track unpruned relations explicitly,
making it possible for top-level plan nodes, such as ModifyTable and
LockRows, to avoid processing partitions pruned during initial
pruning. Scan-level nodes, such as Append and MergeAppend, already
avoid the unnecessary processing by accessing partition pruning
results directly via part_prune_index. In contrast, top-level nodes
cannot access pruning results directly and need to determine which
partitions remain unpruned.
To address this, this commit introduces a new bitmapset field,
es_unpruned_relids, which the executor uses to track the set of
unpruned relations. This field is referenced during plan
initialization to skip initializing certain nodes for pruned
partitions. It is initialized with PlannedStmt.unprunableRelids,
a new field that the planner populates with RT indexes of relations
that cannot be pruned during runtime pruning. These include relations
not subject to partition pruning and those required for execution
regardless of pruning.
PlannedStmt.unprunableRelids is computed during set_plan_refs() by
removing the RT indexes of runtime-prunable relations, identified
from PartitionPruneInfos, from the full set of relation RT indexes.
ExecDoInitialPruning() then updates es_unpruned_relids by adding
partitions that survive initial pruning.
To support this, PartitionedRelPruneInfo and PartitionedRelPruningData
now include a leafpart_rti_map[] array that maps partition indexes to
their corresponding RT indexes. The former is used in set_plan_refs()
when constructing unprunableRelids, while the latter is used in
ExecDoInitialPruning() to convert partition indexes returned by
get_matching_partitions() into RT indexes, which are then added to
es_unpruned_relids.
These changes make it possible for ModifyTable and LockRows nodes to
process only relations that remain unpruned after initial pruning.
ExecInitModifyTable() trims lists, such as resultRelations,
withCheckOptionLists, returningLists, and updateColnosLists, to
consider only unpruned partitions. It also creates ResultRelInfo
structs only for these partitions. Similarly, child RowMarks for
pruned relations are skipped.
By avoiding unnecessary initialization of structures for pruned
partitions, these changes improve the performance of updates and
deletes on partitioned tables during initial runtime pruning.
Due to ExecInitModifyTable() changes as described above, EXPLAIN on a
plan for UPDATE and DELETE that uses runtime initial pruning no longer
lists partitions pruned during initial pruning.
Reviewed-by: Robert Haas <robertmhaas@gmail.com> (earlier versions)
Reviewed-by: Tomas Vondra <tomas@vondra.me>
Discussion: https://postgr.es/m/CA+HiwqFGkMSge6TgC9KQzde0ohpAycLQuV7ooitEEpbKB0O_mg@mail.gmail.com
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This turns GistTranslateCompareType() into a callback function of the
gist index AM instead of a standalone function. The existing callers
are changed to use IndexAmTranslateCompareType(). This then makes
that code not hardcoded toward gist.
This means in particular that the temporal keys code is now
independent of gist. Also, this generalizes commit 74edabce7a3, so
other index access methods other than the previously hardcoded ones
could now work as REPLICA IDENTITY in a logical replication
subscriber.
Author: Mark Dilger <mark.dilger@enterprisedb.com>
Co-authored-by: Peter Eisentraut <peter@eisentraut.org>
Discussion: https://www.postgresql.org/message-id/flat/E72EAA49-354D-4C2E-8EB9-255197F55330@enterprisedb.com
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Consistently use "Size" (or size_t, or in some places int64 or double)
as the type for variables holding memory allocation sizes. In most
places variables' data types were fine already, but we had an ancient
habit of computing bytes from kilobytes-units GUCs with code like
"work_mem * 1024L". That risks overflow on Win64 where they did not
make "long" as wide as "size_t". We worked around that by restricting
such GUCs' ranges, so you couldn't set work_mem et al higher than 2GB
on Win64. This patch removes that restriction, after replacing such
calculations with "work_mem * (Size) 1024" or variants of that.
It should be noted that this patch was constructed by searching
outwards from the GUCs that have MAX_KILOBYTES as upper limit.
So I can't positively guarantee there are no other places doing
memory-size arithmetic in int or long variables. I do however feel
pretty confident that increasing MAX_KILOBYTES on Win64 is safe now.
Also, nothing in our code should be dealing in multiple-gigabyte
allocations without authorization from a relevant GUC, so it seems
pretty likely that this search caught everything that could be at
risk of overflow.
Author: Vladlen Popolitov <v.popolitov@postgrespro.ru>
Co-authored-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://postgr.es/m/1a01f0-66ec2d80-3b-68487680@27595217
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This commit builds on the prior change that moved PartitionPruneInfos
out of individual plan nodes into a list in PlannedStmt, making it
possible to initialize PartitionPruneStates without traversing the
plan tree and perform runtime initial pruning before ExecInitNode()
initializes the plan trees. These tasks are now handled in a new
routine, ExecDoInitialPruning(), which is called by InitPlan()
before calling ExecInitNode() on various plan trees.
ExecDoInitialPruning() performs the initial pruning and saves the
result -- a Bitmapset of indexes for surviving child subnodes -- in
es_part_prune_results, a list in EState.
PartitionPruneStates created for initial pruning are stored in
es_part_prune_states, another list in EState, for later use during
exec pruning. Both lists are parallel to es_part_prune_infos, which
holds the PartitionPruneInfos from PlannedStmt, enabling shared
indexing.
PartitionPruneStates initialized in ExecDoInitialPruning() now
include only the PartitionPruneContexts for initial pruning steps.
Exec pruning contexts are initialized later in
ExecInitPartitionExecPruning() when the parent plan node is
initialized, as the exec pruning step expressions depend on the parent
node's PlanState.
The existing function PartitionPruneFixSubPlanMap() has been
repurposed for this initialization to avoid duplicating a similar
loop structure for finding PartitionedRelPruningData to initialize
exec pruning contexts for. It has been renamed to
InitExecPruningContexts() to reflect its new primary responsibility.
The original logic to "fix subplan maps" remains intact but is now
encapsulated within the renamed function.
This commit removes two obsolete Asserts in partkey_datum_from_expr().
The ExprContext used for pruning expression evaluation is now
independent of the parent PlanState, making these Asserts unnecessary.
By centralizing pruning logic and decoupling it from the plan
initialization step (ExecInitNode()), this change sets the stage for
future patches that will use the result of initial pruning to
save the overhead of redundant processing for pruned partitions.
Reviewed-by: Robert Haas <robertmhaas@gmail.com>
Reviewed-by: Tomas Vondra <tomas@vondra.me>
Discussion: https://postgr.es/m/CA+HiwqFGkMSge6TgC9KQzde0ohpAycLQuV7ooitEEpbKB0O_mg@mail.gmail.com
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Instead of deciding at runtime whether to read from casetest.value
or caseValue_datum, split EEOP_CASE_TESTVAL into two opcodes and
make the decision during expression compilation. Similarly for
EEOP_DOMAIN_TESTVAL. This actually results in net less code,
mainly because llvmjit_expr.c's code for handling these opcodes
gets shorter. The performance gain is doubtless negligible, but
this seems worth changing anyway on grounds of simplicity and
understandability.
Author: Andreas Karlsson <andreas@proxel.se>
Co-authored-by: Xing Guo <higuoxing@gmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://postgr.es/m/CACpMh+AiBYAWn+D1aU7Rsy-V1tox06Cbc0H3qA7rwL5zdJ=anQ@mail.gmail.com
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This moves PartitionPruneInfo from plan nodes to PlannedStmt,
simplifying traversal by centralizing all PartitionPruneInfo
structures in a single list in it, which holds all instances for the
main query and its subqueries. Instead of plan nodes (Append or
MergeAppend) storing PartitionPruneInfo pointers, they now reference
an index in this list.
A bitmapset field is added to PartitionPruneInfo to store the RT
indexes corresponding to the apprelids field in Append or MergeAppend.
This allows execution pruning logic to verify that it operates on the
correct plan node, mainly to facilitate debugging.
Duplicated code in set_append_references() and
set_mergeappend_references() is refactored into a new function,
register_pruneinfo(). This updates RT indexes by applying rtoffet
and adds PartitionPruneInfo to the global list in PlannerGlobal.
By allowing pruning to be performed without traversing the plan tree,
this change lays the groundwork for runtime initial pruning to occur
independently of plan tree initialization.
Reviewed-by: Alvaro Herrera <alvherre@alvh.no-ip.org> (earlier version)
Reviewed-by: Robert Haas <robertmhaas@gmail.com>
Reviewed-by: Tomas Vondra <tomas@vondra.me>
Discussion: https://postgr.es/m/CA+HiwqFGkMSge6TgC9KQzde0ohpAycLQuV7ooitEEpbKB0O_mg@mail.gmail.com
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This commit refactors ExecScan() by moving its tuple-fetching,
filtering, and projection logic into an inline-able function,
ExecScanExtended(), defined in src/include/executor/execScan.h.
ExecScanExtended() accepts parameters for EvalPlanQual state,
qualifiers (ExprState), and projection (ProjectionInfo).
Specialized variants of the execution function of a given Scan node
(for example, ExecSeqScan() for SeqScan) can then pass const-NULL for
unused parameters. This allows the compiler to inline the logic and
eliminate unnecessary branches or checks. Each variant function thus
contains only the necessary code, optimizing execution for scans
where these features are not needed.
The variant function to be used is determined in the ExecInit*()
function of the node and assigned to the ExecProcNode function pointer
in the node's PlanState, effectively turning runtime checks and
conditional branches on the NULLness of epqstate, qual, and projInfo
into static ones, provided the compiler successfully eliminates
unnecessary checks from the inlined code of ExecScanExtended().
Currently, only ExecSeqScan() is modified to take advantage of this
inline-ability. Other Scan nodes might benefit from such specialized
variant functions but that is left as future work.
Benchmarks performed by Junwang Zhao, David Rowley and myself show up
to a 5% reduction in execution time for queries that rely heavily on
Seq Scans. The most significant improvements were observed in
scenarios where EvalPlanQual, qualifiers, and projection were not
required, but other cases also benefit from reduced runtime overhead
due to the inlining and removal of unnecessary code paths.
The idea for this patch first came from Andres Freund in an off-list
discussion. The refactoring approach implemented here is based on a
proposal by David Rowley, significantly improving upon the patch I
(amitlan) initially proposed.
Suggested-by: Andres Freund <andres@anarazel.de>
Co-authored-by: David Rowley <dgrowleyml@gmail.com>
Reviewed-by: David Rowley <dgrowleyml@gmail.com>
Reviewed-by: Junwang Zhao <zhjwpku@gmail.com>
Tested-by: Junwang Zhao <zhjwpku@gmail.com>
Tested-by: David Rowley <dgrowleyml@gmail.com>
Discussion: https://postgr.es/m/CA+HiwqGaH-otvqW_ce-paL=96JvU4j+Xbuk+14esJNDwefdkOg@mail.gmail.com
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This allows the RETURNING list of INSERT/UPDATE/DELETE/MERGE queries
to explicitly return old and new values by using the special aliases
"old" and "new", which are automatically added to the query (if not
already defined) while parsing its RETURNING list, allowing things
like:
RETURNING old.colname, new.colname, ...
RETURNING old.*, new.*
Additionally, a new syntax is supported, allowing the names "old" and
"new" to be changed to user-supplied alias names, e.g.:
RETURNING WITH (OLD AS o, NEW AS n) o.colname, n.colname, ...
This is useful when the names "old" and "new" are already defined,
such as inside trigger functions, allowing backwards compatibility to
be maintained -- the interpretation of any existing queries that
happen to already refer to relations called "old" or "new", or use
those as aliases for other relations, is not changed.
For an INSERT, old values will generally be NULL, and for a DELETE,
new values will generally be NULL, but that may change for an INSERT
with an ON CONFLICT ... DO UPDATE clause, or if a query rewrite rule
changes the command type. Therefore, we put no restrictions on the use
of old and new in any DML queries.
Dean Rasheed, reviewed by Jian He and Jeff Davis.
Discussion: https://postgr.es/m/CAEZATCWx0J0-v=Qjc6gXzR=KtsdvAE7Ow=D=mu50AgOe+pvisQ@mail.gmail.com
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RowCompareType served as a way to describe the fundamental meaning of
an operator, notionally independent of an operator class (although so
far this was only really supported for btrees). Its original purpose
was for use inside RowCompareExpr, and it has also found some small
use outside, such as for get_op_btree_interpretation().
We want to expand this now, as a more general way to describe operator
semantics for other index access methods, including gist (to improve
GistTranslateStratnum()) and others not written yet. To avoid future
confusion, we rename the type to CompareType and the symbols from
ROWCOMPARE_XXX to COMPARE_XXX to reflect their more general purpose.
Reviewed-by: Mark Dilger <mark.dilger@enterprisedb.com>
Discussion: https://www.postgresql.org/message-id/flat/E72EAA49-354D-4C2E-8EB9-255197F55330@enterprisedb.com
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This reverts commit e0ece2a981ee9068f50c4423e303836c2585eb02 due to
performance regressions.
Reported-by: David Rowley
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Previously, the caller needed to allocate the memory and the
TupleHashTable would store a pointer to it. That wastes space for the
palloc overhead as well as the size of the pointer itself.
Now, the TupleHashTable relies on the caller to correctly specify the
additionalsize, and allocates that amount of space. The caller can
then request a pointer into that space.
Discussion: https://postgr.es/m/b9cbf0219a9859dc8d240311643ff4362fd9602c.camel@j-davis.com
Reviewed-by: Heikki Linnakangas
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Discussion: https://postgr.es/m/7530bd8783b1a78d53a3c70383e38d8da0a5ffe5.camel%40j-davis.com
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Backpatch-through: 13
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It was reasonable to preserve the old API of BuildTupleHashTable()
in the back branches, but in HEAD we should actively discourage use
of that version. There are no remaining callers in core, so just
get rid of it. Then rename BuildTupleHashTableExt() back to
BuildTupleHashTable().
While at it, fix up the miserably-poorly-maintained header comment
for BuildTupleHashTable[Ext]. It looks like more than one patch in
this area has had the opinion that updating comments is beneath them.
Discussion: https://postgr.es/m/538343.1734646986@sss.pgh.pa.us
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The original design for set operations involved appending the two
input relations into one and adding a flag column that allows
distinguishing which side each row came from. Then the SetOp node
pries them apart again based on the flag. This is bizarre. The
only apparent reason to do it is that when sorting, we'd only need
one Sort node not two. But since sorting is at least O(N log N),
sorting all the data is actually worse than sorting each side
separately --- plus, we have no chance of taking advantage of
presorted input. On top of that, adding the flag column frequently
requires an additional projection step that adds cycles, and then
the Append node isn't free either. Let's get rid of all of that
and make the SetOp node have two separate children, using the
existing outerPlan/innerPlan infrastructure.
This initial patch re-implements nodeSetop.c and does a bare minimum
of work on the planner side to generate correctly-shaped plans.
In particular, I've tried not to change the cost estimates here,
so that the visible changes in the regression test results will only
involve removal of useless projection steps and not any changes in
whether to use sorted vs hashed mode.
For SORTED mode, we combine successive identical tuples from each
input into groups, and then merge-join the groups. The tuple
comparisons now use SortSupport instead of simple equality, but
the group-formation part should involve roughly the same number of
tuple comparisons as before. The cross-comparisons between left and
right groups probably add to that, but I'm not sure to quantify how
many more comparisons we might need.
For HASHED mode, nodeSetop's logic is almost the same as before,
just refactored into two separate loops instead of one loop that
has an assumption that it will see all the left-hand inputs first.
In both modes, I added early-exit logic to not bother reading the
right-hand relation if the left-hand input is empty, since neither
INTERSECT nor EXCEPT modes can produce any output if the left input
is empty. This could have been done before in the hashed mode, but
not in sorted mode. Sorted mode can also stop as soon as it exhausts
the left input; any remaining right-hand tuples cannot have matches.
Also, this patch adds some infrastructure for detecting whether
child plan nodes all output the same type of tuple table slot.
If they do, the hash table logic can use slightly more efficient
code based on assuming that that's the input slot type it will see.
We'll make use of that infrastructure in other plan node types later.
Patch by me; thanks to Richard Guo and David Rowley for review.
Discussion: https://postgr.es/m/1850138.1731549611@sss.pgh.pa.us
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0f5738202 adjusted the execGrouping.c code so it made use of ExprStates to
generate hash values. That commit made a wrong assumption that the slot
type to pass to ExecBuildHash32FromAttrs() is always &TTSOpsMinimalTuple.
That's not the case as the slot type depends on the slot type passed to
LookupTupleHashEntry(), which for nodeRecursiveunion.c, could be any of
the current slot types.
Here we fix this by adding a new parameter to BuildTupleHashTableExt()
to allow the slot type to be passed in. In the case of nodeSubplan.c
and nodeAgg.c the slot type is always &TTSOpsVirtual, so for both of
those cases, it's beneficial to pass the known slot type as that allows
ExecBuildHash32FromAttrs() to skip adding the tuple deform step to the
resulting ExprState. Another possible fix would have been to have
ExecBuildHash32FromAttrs() set "fetch.kind" to NULL so that
ExecComputeSlotInfo() always determines the EEOP_INNER_FETCHSOME is
required, however, that option isn't favorable as slows down aggregation
and hashed subplan evaluation due to the extra (needless) deform step.
Thanks to Nathan Bossart for bisecting to find the offending commit
based on Paul's report.
Reported-by: Paul Ramsey <pramsey@cleverelephant.ca>
Discussion: https://postgr.es/m/99F064C1-B3EB-4BE7-97D2-D2A0AA487A71@cleverelephant.ca
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This speeds up obtaining hash values for GROUP BY and hashed SubPlans by
using the ExprState support for hashing, thus allowing JIT compilation for
obtaining hash values for these operations.
This, even without JIT compilation, has been shown to improve Hash
Aggregate performance in some cases by around 15% and hashed NOT IN
queries in one case by over 30%, however, real-world cases are likely to
see smaller gains as the test cases used were purposefully designed to
have high hashing overheads by keeping the hash table small to prevent
additional memory overheads that would be a factor when working with large
hash tables.
In passing, fix a hypothetical bug in ExecBuildHash32Expr() so that the
initial value is stored directly in the ExprState's result field if
there are no expressions to hash. None of the current users of this
function use an initial value, so the bug is only hypothetical.
Reviewed-by: Andrei Lepikhov <lepihov@gmail.com>
Discussion: https://postgr.es/m/CAApHDvpYSO3kc9UryMevWqthTBrxgfd9djiAjKHMPUSQeX9vdQ@mail.gmail.com
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get_equal_strategy_number_for_am() gets the equal strategy number for
an AM. This currently only supports btree and hash. In the more
general case, this also depends on the operator class (see for example
GistTranslateStratnum()). To support that, replace this function with
get_equal_strategy_number() that takes an opclass and derives it from
there. (This function already existed before as a static function, so
the signature is kept for simplicity.)
This patch is only a refactoring, it doesn't add support for other
index AMs such as gist. This will be done separately.
Reviewed-by: Paul Jungwirth <pj@illuminatedcomputing.com>
Reviewed-by: vignesh C <vignesh21@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/CA+renyUApHgSZF9-nd-a0+OPGharLQLO=mDHcY4_qQ0+noCUVg@mail.gmail.com
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Our parallel-mode code only works when we are executing a query
in full, so ExecutePlan must disable parallel mode when it is
asked to do partial execution. The previous logic for this
involved passing down a flag (variously named execute_once or
run_once) from callers of ExecutorRun or PortalRun. This is
overcomplicated, and unsurprisingly some of the callers didn't
get it right, since it requires keeping state that not all of
them have handy; not to mention that the requirements for it were
undocumented. That led to assertion failures in some corner
cases. The only state we really need for this is the existing
QueryDesc.already_executed flag, so let's just put all the
responsibility in ExecutePlan. (It could have been done in
ExecutorRun too, leading to a slightly shorter patch -- but if
there's ever more than one caller of ExecutePlan, it seems better
to have this logic in the subroutine than the callers.)
This makes those ExecutorRun/PortalRun parameters unnecessary.
In master it seems okay to just remove them, returning the
API for those functions to what it was before parallelism.
Such an API break is clearly not okay in stable branches,
but for them we can just leave the parameters in place after
documenting that they do nothing.
Per report from Yugo Nagata, who also reviewed and tested
this patch. Back-patch to all supported branches.
Discussion: https://postgr.es/m/20241206062549.710dc01cf91224809dd6c0e1@sraoss.co.jp
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If passed a read-write expanded object pointer, the EEOP_NULLIF
code would hand that same pointer to the equality function
and then (unless equality was reported) also return the same
pointer as its value. This is no good, because a function that
receives a read-write expanded object pointer is fully entitled
to scribble on or even delete the object, thus corrupting the
NULLIF output. (This problem is likely unobservable with the
equality functions provided in core Postgres, but it's easy to
demonstrate with one coded in plpgsql.)
To fix, make sure the pointer passed to the equality function
is read-only. We can still return the original read-write
pointer as the NULLIF result, allowing optimization of later
operations.
Per bug #18722 from Alexander Lakhin. This has been wrong
since we invented expanded objects, so back-patch to all
supported branches.
Discussion: https://postgr.es/m/18722-fd9e645448cc78b4@postgresql.org
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adf97c156 made it so ExprStates could support hashing and changed Hash
Join to use that instead of manually extracting Datums from tuples and
hashing them one column at a time.
When hashing multiple columns or expressions, the code added in that
commit stored the intermediate hash value in the ExprState's resvalue
field. That was a mistake as steps may be injected into the ExprState
between each hashing step that look at or overwrite the stored
intermediate hash value. EEOP_PARAM_SET is an example of such a step.
Here we fix this by adding a new dedicated field for storing
intermediate hash values and adjust the code so that all apart from the
final hashing step store their result in the intermediate field.
In passing, rename a variable so that it's more aligned to the
surrounding code and also so a few lines stay within the 80 char margin.
Reported-by: Andres Freund
Reviewed-by: Alena Rybakina <a.rybakina@postgrespro.ru>
Discussion: https://postgr.es/m/CAApHDvqo9eenEFXND5zZ9JxO_k4eTA4jKMGxSyjdTrsmYvnmZw@mail.gmail.com
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This patch provides the additional logging information in the following
conflict scenarios while applying changes:
insert_exists: Inserting a row that violates a NOT DEFERRABLE unique constraint.
update_differ: Updating a row that was previously modified by another origin.
update_exists: The updated row value violates a NOT DEFERRABLE unique constraint.
update_missing: The tuple to be updated is missing.
delete_differ: Deleting a row that was previously modified by another origin.
delete_missing: The tuple to be deleted is missing.
For insert_exists and update_exists conflicts, the log can include the origin
and commit timestamp details of the conflicting key with track_commit_timestamp
enabled.
update_differ and delete_differ conflicts can only be detected when
track_commit_timestamp is enabled on the subscriber.
We do not offer additional logging for exclusion constraint violations because
these constraints can specify rules that are more complex than simple equality
checks. Resolving such conflicts won't be straightforward. This area can be
further enhanced if required.
Author: Hou Zhijie
Reviewed-by: Shveta Malik, Amit Kapila, Nisha Moond, Hayato Kuroda, Dilip Kumar
Discussion: https://postgr.es/m/OS0PR01MB5716352552DFADB8E9AD1D8994C92@OS0PR01MB5716.jpnprd01.prod.outlook.com
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Here we add ExprState support for obtaining a 32-bit hash value from a
list of expressions. This allows both faster hashing and also JIT
compilation of these expressions. This is especially useful when hash
joins have multiple join keys as the previous code called ExecEvalExpr on
each hash join key individually and that was inefficient as tuple
deformation would have only taken into account one key at a time, which
could lead to walking the tuple once for each join key. With the new
code, we'll determine the maximum attribute required and deform the tuple
to that point only once.
Some performance tests done with this change have shown up to a 20%
performance increase of a query containing a Hash Join without JIT
compilation and up to a 26% performance increase when JIT is enabled and
optimization and inlining were performed by the JIT compiler. The
performance increase with 1 join column was less with a 14% increase
with and without JIT. This test was done using a fairly small hash
table and a large number of hash probes. The increase will likely be
less with large tables, especially ones larger than L3 cache as memory
pressure is more likely to be the limiting factor there.
This commit only addresses Hash Joins, but lays expression evaluation
and JIT compilation infrastructure for other hashing needs such as Hash
Aggregate.
Author: David Rowley
Reviewed-by: Alexey Dvoichenkov <alexey@hyperplane.net>
Reviewed-by: Tels <nospam-pg-abuse@bloodgate.com>
Discussion: https://postgr.es/m/CAApHDvoexAxgQFNQD_GRkr2O_eJUD1-wUGm%3Dm0L%2BGc%3DT%3DkEa4g%40mail.gmail.com
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Until now we generated an ExprState for each parameter to a SubPlan and
evaluated them one-by-one ExecScanSubPlan. That's sub-optimal as creating lots
of small ExprStates
a) makes JIT compilation more expensive
b) wastes memory
c) is a bit slower to execute
This commit arranges to evaluate parameters to a SubPlan as part of the
ExprState referencing a SubPlan, using the new EEOP_PARAM_SET expression
step. We emit one EEOP_PARAM_SET for each argument to a subplan, just before
the EEOP_SUBPLAN step.
It likely is worth using EEOP_PARAM_SET in other places as well, e.g. for
SubPlan outputs, nestloop parameters and - more ambitiously - to get rid of
ExprContext->domainValue/caseValue/ecxt_agg*. But that's for later.
Author: Andres Freund <andres@anarazel.de>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Alena Rybakina <lena.ribackina@yandex.ru>
Discussion: https://postgr.es/m/20230225214401.346ancgjqc3zmvek@awork3.anarazel.de
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The current method of coercing the boolean result value of
JsonPathExists() to the target type specified for an EXISTS column,
which is to call the type's input function via json_populate_type(),
leads to an error when the target type is integer, because the
integer input function doesn't recognize boolean literal values as
valid.
Instead use the boolean-to-integer cast function for coercion in that
case so that using integer or domains thereof as type for EXISTS
columns works. Note that coercion for ON ERROR values TRUE and FALSE
already works like that because the parser creates a cast expression
including the cast function, but the coercion of the actual result
value is not handled by the parser.
Tests by Jian He.
Reported-by: Jian He <jian.universality@gmail.com>
Author: Jian He <jian.universality@gmail.com>
Author: Amit Langote <amitlangote09@gmail.com>
Discussion: https://postgr.es/m/CACJufxEo4sUjKCYtda0_qt9tazqqKPmF1cqhW9KBOUeJFqQd2g@mail.gmail.com
Backpatch-through: 17
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Nodes like Memoize report the cache stats for each parallel worker, so it
makes sense to show the exact and lossy pages in Parallel Bitmap Heap Scan
in a similar way. Likewise, Sort shows the method and memory used for
each worker.
There was some discussion on whether the leader stats should include the
totals for each parallel worker or not. I did some analysis on this to
see what other parallel node types do and it seems only Parallel Hash does
anything like this. All the rest, per what's supported by
ExecParallelRetrieveInstrumentation() are consistent with each other.
Author: David Geier <geidav.pg@gmail.com>
Author: Heikki Linnakangas <hlinnaka@iki.fi>
Author: Donghang Lin <donghanglin@gmail.com>
Author: Alena Rybakina <lena.ribackina@yandex.ru>
Author: David Rowley <dgrowleyml@gmail.com>
Reviewed-by: Dmitry Dolgov <9erthalion6@gmail.com>
Reviewed-by: Michael Christofides <michael@pgmustard.com>
Reviewed-by: Robert Haas <robertmhaas@gmail.com>
Reviewed-by: Dilip Kumar <dilipbalaut@gmail.com>
Reviewed-by: Tomas Vondra <tomas.vondra@enterprisedb.com>
Reviewed-by: Melanie Plageman <melanieplageman@gmail.com>
Reviewed-by: Donghang Lin <donghanglin@gmail.com>
Reviewed-by: Masahiro Ikeda <Masahiro.Ikeda@nttdata.com>
Discussion: https://postgr.es/m/b3d80961-c2e5-38cc-6a32-61886cdf766d%40gmail.com
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Instead of looking up casts at parse time for converting the result
of JsonPath* query functions to the specified or the default
RETURNING type, always perform the conversion at runtime using either
the target type's input function or the function
json_populate_type().
There are two motivations for this change:
1. json_populate_type() coerces to types with typmod such that any
string values that exceed length limit cause an error instead of
silent truncation, which is necessary to be standard-conforming.
2. It was possible to end up with a cast expression that doesn't
support soft handling of errors causing bugs in the of handling
ON ERROR clause.
JsonExpr.coercion_expr which would store the cast expression is no
longer necessary, so remove.
Bump catversion because stored rules change because of the above
removal.
Reported-by: Alvaro Herrera <alvherre@alvh.no-ip.org>
Reviewed-by: Jian He <jian.universality@gmail.com>
Discussion: Discussion: https://postgr.es/m/202405271326.5a5rprki64aw%40alvherre.pgsql
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This allows us to abstract how/whether table AM uses transaction identifiers.
A custom table AM can use a custom slot, which may not store xmin directly,
but determine the tuple belonging to the current transaction in the other way.
Discussion: https://postgr.es/m/CAPpHfdurb9ycV8udYqM%3Do0sPS66PJ4RCBM1g-bBpvzUfogY0EA%40mail.gmail.com
Reviewed-by: Matthias van de Meent, Mark Dilger, Pavel Borisov
Reviewed-by: Nikita Malakhov, Japin Li
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This introduces the following SQL/JSON functions for querying JSON
data using jsonpath expressions:
JSON_EXISTS(), which can be used to apply a jsonpath expression to a
JSON value to check if it yields any values.
JSON_QUERY(), which can be used to to apply a jsonpath expression to
a JSON value to get a JSON object, an array, or a string. There are
various options to control whether multi-value result uses array
wrappers and whether the singleton scalar strings are quoted or not.
JSON_VALUE(), which can be used to apply a jsonpath expression to a
JSON value to return a single scalar value, producing an error if it
multiple values are matched.
Both JSON_VALUE() and JSON_QUERY() functions have options for
handling EMPTY and ERROR conditions, which can be used to specify
the behavior when no values are matched and when an error occurs
during jsonpath evaluation, respectively.
Author: Nikita Glukhov <n.gluhov@postgrespro.ru>
Author: Teodor Sigaev <teodor@sigaev.ru>
Author: Oleg Bartunov <obartunov@gmail.com>
Author: Alexander Korotkov <aekorotkov@gmail.com>
Author: Andrew Dunstan <andrew@dunslane.net>
Author: Amit Langote <amitlangote09@gmail.com>
Author: Peter Eisentraut <peter@eisentraut.org>
Author: Jian He <jian.universality@gmail.com>
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, Álvaro Herrera, Jian He, Anton A. Melnikov,
Nikita Malakhov, Peter Eisentraut, Tomas Vondra
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
Discussion: https://postgr.es/m/20220616233130.rparivafipt6doj3@alap3.anarazel.de
Discussion: https://postgr.es/m/abd9b83b-aa66-f230-3d6d-734817f0995d%40postgresql.org
Discussion: https://postgr.es/m/CA+HiwqHROpf9e644D8BRqYvaAPmgBZVup-xKMDPk-nd4EpgzHw@mail.gmail.com
Discussion: https://postgr.es/m/CA+HiwqE4XTdfb1nW=Ojoy_tQSRhYt-q_kb6i5d4xcKyrLC1Nbg@mail.gmail.com
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This allows a RETURNING clause to be appended to a MERGE query, to
return values based on each row inserted, updated, or deleted. As with
plain INSERT, UPDATE, and DELETE commands, the returned values are
based on the new contents of the target table for INSERT and UPDATE
actions, and on its old contents for DELETE actions. Values from the
source relation may also be returned.
As with INSERT/UPDATE/DELETE, the output of MERGE ... RETURNING may be
used as the source relation for other operations such as WITH queries
and COPY commands.
Additionally, a special function merge_action() is provided, which
returns 'INSERT', 'UPDATE', or 'DELETE', depending on the action
executed for each row. The merge_action() function can be used
anywhere in the RETURNING list, including in arbitrary expressions and
subqueries, but it is an error to use it anywhere outside of a MERGE
query's RETURNING list.
Dean Rasheed, reviewed by Isaac Morland, Vik Fearing, Alvaro Herrera,
Gurjeet Singh, Jian He, Jeff Davis, Merlin Moncure, Peter Eisentraut,
and Wolfgang Walther.
Discussion: http://postgr.es/m/CAEZATCWePEGQR5LBn-vD6SfeLZafzEm2Qy_L_Oky2=qw2w3Pzg@mail.gmail.com
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There is a very ancient hack in check_sql_fn_retval that allows a
single SELECT targetlist entry of composite type to be taken as
supplying all the output columns of a function returning composite.
(This is grotty and fundamentally ambiguous, but it's really hard
to do nested composite-returning functions without it.)
As far as I know, that doesn't cause any problems in ordinary
functions. It's disastrous for procedures however. All procedures
that have any output parameters are labeled with prorettype RECORD,
and the CALL code expects it will get back a record with one column
per output parameter, regardless of whether any of those parameters
is composite. Doing something else leads to an assertion failure
or core dump.
This is simple enough to fix: we just need to not apply that rule
when considering procedures. However, that requires adding another
argument to check_sql_fn_retval, which at least in principle might be
getting called by external callers. Therefore, in the back branches
convert check_sql_fn_retval into an ABI-preserving wrapper around a
new function check_sql_fn_retval_ext.
Per report from Yahor Yuzefovich. This has been broken since we
implemented procedures, so back-patch to all supported branches.
Discussion: https://postgr.es/m/CABz5gWHSjj2df6uG0NRiDhZ_Uz=Y8t0FJP-_SVSsRsnrQT76Gg@mail.gmail.com
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This allows the target relation of MERGE to be an auto-updatable or
trigger-updatable view, and includes support for WITH CHECK OPTION,
security barrier views, and security invoker views.
A trigger-updatable view must have INSTEAD OF triggers for every type
of action (INSERT, UPDATE, and DELETE) mentioned in the MERGE command.
An auto-updatable view must not have any INSTEAD OF triggers. Mixing
auto-update and trigger-update actions (i.e., having a partial set of
INSTEAD OF triggers) is not supported.
Rule-updatable views are also not supported, since there is no
rewriter support for non-SELECT rules with MERGE operations.
Dean Rasheed, reviewed by Jian He and Alvaro Herrera.
Discussion: https://postgr.es/m/CAEZATCVcB1g0nmxuEc-A+gGB0HnfcGQNGYH7gS=7rq0u0zOBXA@mail.gmail.com
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This adjusts the code for CoerceViaIO and CoerceToDomain expression
nodes to handle errors softly.
For CoerceViaIo, this adds a new ExprEvalStep opcode
EEOP_IOCOERCE_SAFE, which is implemented in the new accompanying
function ExecEvalCoerceViaIOSafe(). The only difference from
EEOP_IOCOERCE's inline implementation is that the input function
receives an ErrorSaveContext via the function's
FunctionCallInfo.context, which it can use to handle errors softly.
For CoerceToDomain, this simply entails replacing the ereport() in
ExecEvalConstraintNotNull() and ExecEvalConstraintCheck() by
errsave() passing it the ErrorSaveContext passed in the expression's
ExprEvalStep.
In both cases, the ErrorSaveContext to be used is passed by setting
ExprState.escontext to point to it before calling ExecInitExprRec()
on the expression tree whose errors are to be handled softly.
Note that there's no functional change as of this commit as no call
site of ExecInitExprRec() has been changed. This is intended for
implementing new SQL/JSON expression nodes in future commits.
Extracted from a much larger patch to add SQL/JSON query functions.
Author: Nikita Glukhov <n.gluhov@postgrespro.ru>
Author: Teodor Sigaev <teodor@sigaev.ru>
Author: Oleg Bartunov <obartunov@gmail.com>
Author: Alexander Korotkov <aekorotkov@gmail.com>
Author: Andrew Dunstan <andrew@dunslane.net>
Author: Amit Langote <amitlangote09@gmail.com>
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,
Álvaro Herrera, Jian He, Peter Eisentraut
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
Discussion: https://postgr.es/m/20220616233130.rparivafipt6doj3@alap3.anarazel.de
Discussion: https://postgr.es/m/abd9b83b-aa66-f230-3d6d-734817f0995d%40postgresql.org
Discussion: https://postgr.es/m/CA+HiwqHROpf9e644D8BRqYvaAPmgBZVup-xKMDPk-nd4EpgzHw@mail.gmail.com
Discussion: https://postgr.es/m/CA+HiwqE4XTdfb1nW=Ojoy_tQSRhYt-q_kb6i5d4xcKyrLC1Nbg@mail.gmail.com
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Reported-by: Michael Paquier
Discussion: https://postgr.es/m/ZZKTDPxBBMt3C0J9@paquier.xyz
Backpatch-through: 12
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tts_virtual_copyslot() contained an Assert that checked that the srcslot
contained <= attributes than the dstslot. This seems to be backwards as
if the srcslot contained fewer attributes then the dstslot could be left
with stale Datum values from the previously stored tuple. It might make
more sense to allow the source to contain additional attributes and only
copy the leading ones that also exist in the destination, however, that's
not what we're doing here.
Here we just remove the Assert from tts_virtual_copyslot() and add an
Assert to ExecCopySlot() to verify the attribute counts match. There
does not seem to be any places where the destination contains fewer
attributes, so instead of going to the trouble of making the code
properly handle this, let's just ensure the attribute counts match. If
this Assert fails then that will indicate that we do have cases that
require us to handle the srcslot with more attributes than the dstslot.
It seems better to only write this code if there's a genuine requirement
for it rather than write it now only to leave it untested.
Thanks to Andres Freund for helping with the analysis of this.
Discussion: https://postgr.es/m/CAApHDvpMAvBL0T+TRORquyx1iqFQKMVTXtqNocOw0Pa2uh1heg@mail.gmail.com
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As of commits dd04e958c8 and 1833f1a1c3, tuplestore_donestoring(),
SPI_push(), SPI_pop(), SPI_push_conditional(),
SPI_pop_conditional(), and SPI_restore_connection() are no-op
macros provided for backwards compatibility. This commit removes
these macros, so any uses in third-party code will need to be
removed, too. Since these macros have been no-ops for a while,
such adjustments won't produce any behavior changes for all
currently-supported versions of PostgreSQL.
Author: Bharath Rupireddy
Discussion: https://postgr.es/m/CALj2ACVeO58JM5tK2Qa8QC-%3DkC8sdkJOTd4BFU%3DK8zs4gGYpjQ%40mail.gmail.com
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Since C99, there can be a trailing comma after the last value in an
enum definition. A lot of new code has been introducing this style on
the fly. Some new patches are now taking an inconsistent approach to
this. Some add the last comma on the fly if they add a new last
value, some are trying to preserve the existing style in each place,
some are even dropping the last comma if there was one. We could
nudge this all in a consistent direction if we just add the trailing
commas everywhere once.
I omitted a few places where there was a fixed "last" value that will
always stay last. I also skipped the header files of libpq and ecpg,
in case people want to use those with older compilers. There were
also a small number of cases where the enum type wasn't used anywhere
(but the enum values were), which ended up confusing pgindent a bit,
so I left those alone.
Discussion: https://www.postgresql.org/message-id/flat/386f8c45-c8ac-4681-8add-e3b0852c1620%40eisentraut.org
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