The current list from the buildfarm includes quite a few typedef
names that it used to miss. The reason is a bit obscure, but it
seems likely to have something to do with our recent increased
use of palloc_object and palloc_array. In any case, this makes
the relevant struct declarations be much more nicely formatted,
so I'll take it. Install the current list and re-run pgindent
to update affected code.
Syncing with the current list also removes some obsolete
typedef names and fixes some alphabetization errors.
Discussion: https://postgr.es/m/1681301.1765742268@sss.pgh.pa.us
Eager aggregation is a query optimization technique that partially
pushes aggregation past a join, and finalizes it once all the
relations are joined. Eager aggregation may reduce the number of
input rows to the join and thus could result in a better overall plan.
In the current planner architecture, the separation between the
scan/join planning phase and the post-scan/join phase means that
aggregation steps are not visible when constructing the join tree,
limiting the planner's ability to exploit aggregation-aware
optimizations. To implement eager aggregation, we collect information
about aggregate functions in the targetlist and HAVING clause, along
with grouping expressions from the GROUP BY clause, and store it in
the PlannerInfo node. During the scan/join planning phase, this
information is used to evaluate each base or join relation to
determine whether eager aggregation can be applied. If applicable, we
create a separate RelOptInfo, referred to as a grouped relation, to
represent the partially-aggregated version of the relation and
generate grouped paths for it.
Grouped relation paths can be generated in two ways. The first method
involves adding sorted and hashed partial aggregation paths on top of
the non-grouped paths. To limit planning time, we only consider the
cheapest or suitably-sorted non-grouped paths in this step.
Alternatively, grouped paths can be generated by joining a grouped
relation with a non-grouped relation. Joining two grouped relations
is currently not supported.
To further limit planning time, we currently adopt a strategy where
partial aggregation is pushed only to the lowest feasible level in the
join tree where it provides a significant reduction in row count.
This strategy also helps ensure that all grouped paths for the same
grouped relation produce the same set of rows, which is important to
support a fundamental assumption of the planner.
For the partial aggregation that is pushed down to a non-aggregated
relation, we need to consider all expressions from this relation that
are involved in upper join clauses and include them in the grouping
keys, using compatible operators. This is essential to ensure that an
aggregated row from the partial aggregation matches the other side of
the join if and only if each row in the partial group does. This
ensures that all rows within the same partial group share the same
"destiny", which is crucial for maintaining correctness.
One restriction is that we cannot push partial aggregation down to a
relation that is in the nullable side of an outer join, because the
NULL-extended rows produced by the outer join would not be available
when we perform the partial aggregation, while with a
non-eager-aggregation plan these rows are available for the top-level
aggregation. Pushing partial aggregation in this case may result in
the rows being grouped differently than expected, or produce incorrect
values from the aggregate functions.
If we have generated a grouped relation for the topmost join relation,
we finalize its paths at the end. The final paths will compete in the
usual way with paths built from regular planning.
The patch was originally proposed by Antonin Houska in 2017. This
commit reworks various important aspects and rewrites most of the
current code. However, the original patch and reviews were very
useful.
Author: Richard Guo <guofenglinux@gmail.com>
Author: Antonin Houska <ah@cybertec.at> (in an older version)
Reviewed-by: Robert Haas <robertmhaas@gmail.com>
Reviewed-by: Jian He <jian.universality@gmail.com>
Reviewed-by: Tender Wang <tndrwang@gmail.com>
Reviewed-by: Matheus Alcantara <matheusssilv97@gmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: David Rowley <dgrowleyml@gmail.com>
Reviewed-by: Tomas Vondra <tomas@vondra.me> (in an older version)
Reviewed-by: Andy Fan <zhihuifan1213@163.com> (in an older version)
Reviewed-by: Ashutosh Bapat <ashutosh.bapat.oss@gmail.com> (in an older version)
Discussion: https://postgr.es/m/CAMbWs48jzLrPt1J_00ZcPZXWUQKawQOFE8ROc-ADiYqsqrpBNw@mail.gmail.com
Instead, use the new mechanism that allows planner extensions to store
private state inside a PlannerInfo, treating GEQO as an in-core planner
extension. This is a useful test of the new facility, and also buys
back a few bytes of storage.
To make this work, we must remove innerrel_is_unique_ext's hack of
testing whether join_search_private is set as a proxy for whether
the join search might be retried. Add a flag that extensions can
use to explicitly signal their intentions instead.
Reviewed-by: Andrei Lepikhov <lepihov@gmail.com>
Reviewed-by: Melanie Plageman <melanieplageman@gmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: http://postgr.es/m/CA+TgmoYWKHU2hKr62Toyzh-kTDEnMDeLw7gkOOnjL-TnOUq0kQ@mail.gmail.com
Extension that make extensive use of planner hooks may want to
coordinate their efforts, for example to avoid duplicate computation,
but that's currently difficult because there's no really good way to
pass data between different hooks.
To make that easier, allow for storage of extension-managed private
state in PlannerGlobal, PlannerInfo, and RelOptInfo, along very
similar lines to what we have permitted for ExplainState since commit
c65bc2e1d1.
Reviewed-by: Andrei Lepikhov <lepihov@gmail.com>
Reviewed-by: Melanie Plageman <melanieplageman@gmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: http://postgr.es/m/CA+TgmoYWKHU2hKr62Toyzh-kTDEnMDeLw7gkOOnjL-TnOUq0kQ@mail.gmail.com
Previously, subqueries were given names only after they were planned,
which makes it difficult to use information from a previous execution of
the query to guide future planning. If, for example, you knew something
about how you want "InitPlan 2" to be planned, you won't know whether
the subquery you're currently planning will end up being "InitPlan 2"
until after you've finished planning it, by which point it's too late to
use the information that you had.
To fix this, assign each subplan a unique name before we begin planning
it. To improve consistency, use textual names for all subplans, rather
than, as we did previously, a mix of numbers (such as "InitPlan 1") and
names (such as "CTE foo"), and make sure that the same name is never
assigned more than once.
We adopt the somewhat arbitrary convention of using the type of sublink
to set the plan name; for example, a query that previously had two
expression sublinks shown as InitPlan 2 and InitPlan 1 will now end up
named expr_1 and expr_2. Because names are assigned before rather than
after planning, some of the regression test outputs show the numerical
part of the name switching positions: what was previously SubPlan 2 was
actually the first one encountered, but we finished planning it later.
We assign names even to subqueries that aren't shown as such within the
EXPLAIN output. These include subqueries that are a FROM clause item or
a branch of a set operation, rather than something that will be turned
into an InitPlan or SubPlan. The purpose of this is to make sure that,
below the topmost query level, there's always a name for each subquery
that is stable from one planning cycle to the next (assuming no changes
to the query or the database schema).
Author: Robert Haas <rhaas@postgresql.org>
Co-authored-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Alexandra Wang <alexandra.wang.oss@gmail.com>
Reviewed-by: Richard Guo <guofenglinux@gmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Junwang Zhao <zhjwpku@gmail.com>
Discussion: http://postgr.es/m/3641043.1758751399@sss.pgh.pa.us
There are two implementation techniques for semijoins: one uses the
JOIN_SEMI jointype, where the executor emits at most one matching row
per left-hand side (LHS) row; the other unique-ifies the right-hand
side (RHS) and then performs a plain inner join.
The latter technique currently has some drawbacks related to the
unique-ification step.
* Only the cheapest-total path of the RHS is considered during
unique-ification. This may cause us to miss some optimization
opportunities; for example, a path with a better sort order might be
overlooked simply because it is not the cheapest in total cost. Such
a path could help avoid a sort at a higher level, potentially
resulting in a cheaper overall plan.
* We currently rely on heuristics to choose between hash-based and
sort-based unique-ification. A better approach would be to generate
paths for both methods and allow add_path() to decide which one is
preferable, consistent with how path selection is handled elsewhere in
the planner.
* In the sort-based implementation, we currently pay no attention to
the pathkeys of the input subpath or the resulting output. This can
result in redundant sort nodes being added to the final plan.
This patch improves semijoin planning by creating a new RelOptInfo for
the RHS rel to represent its unique-ified version. It then generates
multiple paths that represent elimination of distinct rows from the
RHS, considering both a hash-based implementation using the cheapest
total path of the original RHS rel, and sort-based implementations
that either exploit presorted input paths or explicitly sort the
cheapest total path. All resulting paths compete in add_path(), and
those deemed worthy of consideration are added to the new RelOptInfo.
Finally, the unique-ified rel is joined with the other side of the
semijoin using a plain inner join.
As a side effect, most of the code related to the JOIN_UNIQUE_OUTER
and JOIN_UNIQUE_INNER jointypes -- used to indicate that the LHS or
RHS path should be made unique -- has been removed. Besides, the
T_Unique path now has the same meaning for both semijoins and upper
DISTINCT clauses: it represents adjacent-duplicate removal on
presorted input. This patch unifies their handling by sharing the
same data structures and functions.
This patch also removes the UNIQUE_PATH_NOOP related code along the
way, as it is dead code -- if the RHS rel is provably unique, the
semijoin should have already been simplified to a plain inner join by
analyzejoins.c.
Author: Richard Guo <guofenglinux@gmail.com>
Reviewed-by: Alexandra Wang <alexandra.wang.oss@gmail.com>
Reviewed-by: wenhui qiu <qiuwenhuifx@gmail.com>
Discussion: https://postgr.es/m/CAMbWs4-EBnaRvEs7frTLbsXiweSTUXifsteF-d3rvv01FKO86w@mail.gmail.com
There've been a few complaints that it can be overly difficult to figure
out why the planner picked a Memoize plan. To help address that, here we
adjust the EXPLAIN output to display the following additional details:
1) The estimated number of cache entries that can be stored at once
2) The estimated number of unique lookup keys that we expect to see
3) The number of lookups we expect
4) The estimated hit ratio
Technically #4 can be calculated using #1, #2 and #3, but it's not a
particularly obvious calculation, so we opt to display it explicitly.
The original patch by Lukas Fittl only displayed the hit ratio, but
there was a fear that might lead to more questions about how that was
calculated. The idea with displaying all 4 is to be transparent which
may allow queries to be tuned more easily. For example, if #2 isn't
correct then maybe extended statistics or a manual n_distinct estimate can
be used to help fix poor plan choices.
Author: Ilia Evdokimov <ilya.evdokimov@tantorlabs.com>
Author: Lukas Fittl <lukas@fittl.com>
Reviewed-by: David Rowley <dgrowleyml@gmail.com>
Reviewed-by: Andrei Lepikhov <lepihov@gmail.com>
Reviewed-by: Robert Haas <robertmhaas@gmail.com>
Discussion: https://postgr.es/m/CAP53Pky29GWAVVk3oBgKBDqhND0BRBN6yTPeguV_qSivFL5N_g%40mail.gmail.com
In commit b262ad440, we introduced an optimization that reduces an IS
[NOT] NULL qual on a NOT NULL column to constant true or constant
false, provided we can prove that the input expression of the NullTest
is not nullable by any outer joins or grouping sets. This deduction
happens quite late in the planner, during the distribution of quals to
rels in query_planner. However, this approach has some drawbacks: we
can't perform any further folding with the constant, and it turns out
to be prone to bugs.
Ideally, this deduction should happen during constant folding.
However, the per-relation information about which columns are defined
as NOT NULL is not available at that point. This information is
currently collected from catalogs when building RelOptInfos for base
or "other" relations.
This patch moves the collection of NOT NULL attribute information for
relations before pull_up_sublinks, storing it in a hash table keyed by
relation OID. It then uses this information to perform the NullTest
deduction for Vars during constant folding. This also makes it
possible to leverage this information to pull up NOT IN subqueries.
Note that this patch does not get rid of restriction_is_always_true
and restriction_is_always_false. Removing them would prevent us from
reducing some IS [NOT] NULL quals that we were previously able to
reduce, because (a) the self-join elimination may introduce new IS NOT
NULL quals after constant folding, and (b) if some outer joins are
converted to inner joins, previously irreducible NullTest quals may
become reducible.
Author: Richard Guo <guofenglinux@gmail.com>
Reviewed-by: Robert Haas <robertmhaas@gmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://postgr.es/m/CAMbWs4-bFJ1At4btk5wqbezdu8PLtQ3zv-aiaY3ry9Ymm=jgFQ@mail.gmail.com
As pointed out by Tom Lane, the patch introduced fragile and invasive
design around plan invalidation handling when locking of prunable
partitions was deferred from plancache.c to the executor. In
particular, it violated assumptions about CachedPlan immutability and
altered executor APIs in ways that are difficult to justify given the
added complexity and overhead.
This also removes the firstResultRels field added to PlannedStmt in
commit 28317de72, which was intended to support deferred locking of
certain ModifyTable result relations.
Reported-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://postgr.es/m/605328.1747710381@sss.pgh.pa.us
When creating an explicit Sort node for the outer path of a mergejoin,
we need to determine the number of presorted keys of the outer path to
decide whether explicit incremental sort can be applied. Currently,
this is done by repeatedly calling pathkeys_count_contained_in.
This patch caches the number of presorted outer pathkeys in MergePath,
allowing us to save several calls to pathkeys_count_contained_in. It
can be considered a complement to the changes in commit 828e94c9d.
Reported-by: David Rowley <dgrowleyml@gmail.com>
Author: Richard Guo <guofenglinux@gmail.com>
Reviewed-by: Tender Wang <tndrwang@gmail.com>
Discussion: https://postgr.es/m/CAApHDvqvBireB_w6x8BN5txdvBEHxVgZBt=rUnpf5ww5P_E_ww@mail.gmail.com
When planning queries to partitioned tables, we clone all
EquivalenceMembers belonging to the partitioned table into em_is_child
EquivalenceMembers for each non-pruned partition. For partitioned tables
with large numbers of partitions, this meant the ec_members list could
become large and code searching that list would become slow. Effectively,
the more partitions which were present, the more searches needed to be
performed for operations such as find_ec_member_matching_expr() during
create_plan() and the more partitions present, the longer these searches
would take, i.e., a quadratic slowdown.
To fix this, here we adjust how we store EquivalenceMembers for
em_is_child members. Instead of storing these directly in ec_members,
these are now stored in a new array of Lists in the EquivalenceClass,
which is indexed by the relid. When we want to find EquivalenceMembers
belonging to a certain child relation, we can narrow the search to the
array element for that relation.
To make EquivalenceMember lookup easier and to reduce the amount of code
change, this commit provides a pair of functions to allow iteration over
the EquivalenceMembers of an EC which also handles finding the child
members, if required. Callers that never need to look at child members
can remain using the foreach loop over ec_members, which will now often
be faster due to only parent-level members being stored there.
The actual performance increases here are highly dependent on the number
of partitions and the query being planned. Performance increases can be
visible with as few as 8 partitions, but the speedup is marginal for
such low numbers of partitions. The speedups become much more visible
with a few dozen to hundreds of partitions. With some tested queries
using 56 partitions, the planner was around 3x faster than before. For
use cases with thousands of partitions, these are likely to become
significantly faster. Some testing has shown planner speedups of 60x or
more with 8192 partitions.
Author: Yuya Watari <watari.yuya@gmail.com>
Co-authored-by: David Rowley <dgrowleyml@gmail.com>
Reviewed-by: David Rowley <dgrowleyml@gmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Andrey Lepikhov <a.lepikhov@postgrespro.ru>
Reviewed-by: Alena Rybakina <lena.ribackina@yandex.ru>
Reviewed-by: Dmitry Dolgov <9erthalion6@gmail.com>
Reviewed-by: Amit Langote <amitlangote09@gmail.com>
Reviewed-by: Ashutosh Bapat <ashutosh.bapat.oss@gmail.com>
Tested-by: Thom Brown <thom@linux.com>
Tested-by: newtglobal postgresql_contributors <postgresql_contributors@newtglobalcorp.com>
Discussion: https://postgr.es/m/CAJ2pMkZNCgoUKSE%2B_5LthD%2BKbXKvq6h2hQN8Esxpxd%2Bcxmgomg%40mail.gmail.com
Change the PathKey struct to use CompareType to record the sort
direction instead of hardcoding btree strategy numbers. The
CompareType is then converted to the index-type-specific strategy when
the plan is created.
This reduces the number of places btree strategy numbers are
hardcoded, and it's a self-contained subset of a larger effort to
allow non-btree indexes to behave like btrees.
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
Derived clauses are stored in ec_derives, a List of RestrictInfos.
These clauses are later looked up by matching the left and right
EquivalenceMembers along with the clause's parent EC.
This linear search becomes expensive in queries with many joins or
partitions, where ec_derives may contain thousands of entries. In
particular, create_join_clause() can spend significant time scanning
this list.
To improve performance, introduce a hash table (ec_derives_hash) that
is built when the list reaches 32 entries -- the same threshold used
for join_rel_hash. The original list is retained alongside the hash
table to support EC merging and serialization
(_outEquivalenceClass()).
Each clause is stored in the hash table using a canonicalized key: the
EquivalenceMember with the lower memory address is placed in the key
before the one with the higher memory address. This avoids storing or
searching for both permutations of the same clause. For clauses
involving a constant EM, the key places NULL in the first slot and the
non-constant EM in the second.
The hash table is initialized using list_length(ec_derives_list) as
the size hint. simplehash internally adjusts this to the next power of
two after dividing by the fillfactor, so this typically results in at
least 64 buckets near the threshold -- avoiding immediate resizing
while adapting to the actual number of entries.
The lookup logic for derived clauses is now centralized in
ec_search_derived_clause_for_ems(), which consults the hash table when
available and falls back to the list otherwise.
The new ec_clear_derived_clauses() always frees ec_derives_list, even
though some of the original code paths that cleared the old
ec_derives field did not. This ensures consistent cleanup and avoids
leaking memory when large lists are discarded.
An assertion originally placed in find_derived_clause_for_ec_member()
is moved into ec_search_derived_clause_for_ems() so that it is
enforced consistently, regardless of whether the hash table or list is
used for lookup.
This design incorporates suggestions by David Rowley, who proposed
both the key canonicalization and the initial sizing approach to
balance memory usage and CPU efficiency.
Author: Ashutosh Bapat <ashutosh.bapat.oss@gmail.com>
Reviewed-by: Amit Langote <amitlangote09@gmail.com>
Reviewed-by: David Rowley <dgrowleyml@gmail.com>
Tested-by: Dmitry Dolgov <9erthalion6@gmail.com>
Tested-by: Alvaro Herrera <alvherre@alvh.no-ip.org>
Tested-by: Amit Langote <amitlangote09@gmail.com>
Tested-by: David Rowley <dgrowleyml@gmail.com>
Discussion: https://postgr.es/m/CAExHW5vZiQtWU6moszLP5iZ8gLX_ZAUbgEX0DxGLx9PGWCtqUg@mail.gmail.com
The changes made in commit d2b4b4c225 contained incorrect comments:
They said that certain forward declarations were necessary to "avoid
including pathnodes.h here", but the file is itself pathnodes.h! So
change the comment to just say it's a forward declaration in one case,
and in the other case we don't need the declaration at all because it
already appeared earlier in the file.
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
The Self-Join Elimination (SJE) feature removes an inner join of a plain
table to itself in the query tree if it is proven that the join can be
replaced with a scan without impacting the query result. Self-join and
inner relation get replaced with the outer in query, equivalence classes,
and planner info structures. Also, the inner restrictlist moves to the
outer one with the removal of duplicated clauses. Thus, this optimization
reduces the length of the range table list (this especially makes sense for
partitioned relations), reduces the number of restriction clauses and,
in turn, selectivity estimations, and potentially improves total planner
prediction for the query.
This feature is dedicated to avoiding redundancy, which can appear after
pull-up transformations or the creation of an EquivalenceClass-derived clause
like the below.
SELECT * FROM t1 WHERE x IN (SELECT t3.x FROM t1 t3);
SELECT * FROM t1 WHERE EXISTS (SELECT t3.x FROM t1 t3 WHERE t3.x = t1.x);
SELECT * FROM t1,t2, t1 t3 WHERE t1.x = t2.x AND t2.x = t3.x;
In the future, we could also reduce redundancy caused by subquery pull-up
after unnecessary outer join removal in cases like the one below.
SELECT * FROM t1 WHERE x IN
(SELECT t3.x FROM t1 t3 LEFT JOIN t2 ON t2.x = t1.x);
Also, it can drastically help to join partitioned tables, removing entries
even before their expansion.
The SJE proof is based on innerrel_is_unique() machinery.
We can remove a self-join when for each outer row:
1. At most, one inner row matches the join clause;
2. Each matched inner row must be (physically) the same as the outer one;
3. Inner and outer rows have the same row mark.
In this patch, we use the next approach to identify a self-join:
1. Collect all merge-joinable join quals which look like a.x = b.x;
2. Add to the list above the baseretrictinfo of the inner table;
3. Check innerrel_is_unique() for the qual list. If it returns false, skip
this pair of joining tables;
4. Check uniqueness, proved by the baserestrictinfo clauses. To prove the
possibility of self-join elimination, the inner and outer clauses must
match exactly.
The relation replacement procedure is not trivial and is partly combined
with the one used to remove useless left joins. Tests covering this feature
were added to join.sql. Some of the existing regression tests changed due
to self-join removal logic.
Discussion: https://postgr.es/m/flat/64486b0b-0404-e39e-322d-0801154901f3%40postgrespro.ru
Author: Andrey Lepikhov <a.lepikhov@postgrespro.ru>
Author: Alexander Kuzmenkov <a.kuzmenkov@postgrespro.ru>
Co-authored-by: Alexander Korotkov <aekorotkov@gmail.com>
Co-authored-by: Alena Rybakina <lena.ribackina@yandex.ru>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Robert Haas <robertmhaas@gmail.com>
Reviewed-by: Andres Freund <andres@anarazel.de>
Reviewed-by: Simon Riggs <simon@2ndquadrant.com>
Reviewed-by: Jonathan S. Katz <jkatz@postgresql.org>
Reviewed-by: David Rowley <david.rowley@2ndquadrant.com>
Reviewed-by: Thomas Munro <thomas.munro@enterprisedb.com>
Reviewed-by: Konstantin Knizhnik <k.knizhnik@postgrespro.ru>
Reviewed-by: Heikki Linnakangas <hlinnaka@iki.fi>
Reviewed-by: Hywel Carver <hywel@skillerwhale.com>
Reviewed-by: Laurenz Albe <laurenz.albe@cybertec.at>
Reviewed-by: Ronan Dunklau <ronan.dunklau@aiven.io>
Reviewed-by: vignesh C <vignesh21@gmail.com>
Reviewed-by: Zhihong Yu <zyu@yugabyte.com>
Reviewed-by: Greg Stark <stark@mit.edu>
Reviewed-by: Jaime Casanova <jcasanov@systemguards.com.ec>
Reviewed-by: Michał Kłeczek <michal@kleczek.org>
Reviewed-by: Alena Rybakina <lena.ribackina@yandex.ru>
Reviewed-by: Alexander Korotkov <aekorotkov@gmail.com>
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
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
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
d4c3a156c added support that when the GROUP BY contained all of the
columns belonging to a relation's PRIMARY KEY, all other columns
belonging to that relation would be removed from the GROUP BY clause.
That's possible because all other columns are functionally dependent on
the PRIMARY KEY and those columns alone ensure the groups are distinct.
Here we expand on that optimization and allow it to work for any unique
indexes on the table rather than just the PRIMARY KEY index. This
normally requires that all columns in the index are defined with NOT NULL,
however, we can relax that requirement when the index is defined with
NULLS NOT DISTINCT.
When there are multiple suitable indexes to allow columns to be removed,
we prefer the index with the least number of columns as this allows us
to remove the highest number of GROUP BY columns. One day, we may want to
revisit that decision as it may make more sense to use the narrower set of
columns in terms of the width of the data types and stored/queried data.
This also adjusts the code to make use of RelOptInfo.indexlist rather
than looking up the catalog tables.
In passing, add another short-circuit path to allow bailing out earlier
in cases where it's certainly not possible to remove redundant GROUP BY
columns. This early exit is now cheaper to do than when this code was
originally written as 00b41463c made it cheaper to check for empty
Bitmapsets.
Patch originally by Zhang Mingli and later worked on by jian he, but after
I (David) worked on it, there was very little of the original left.
Author: Zhang Mingli, jian he, David Rowley
Reviewed-by: jian he, Andrei Lepikhov
Discussion: https://postgr.es/m/327990c8-b9b2-4b0c-bffb-462249f82de0%40Spark
The approach of declaring a function pointer with an empty argument
list and hoping that the compiler will not complain about casting it
to another type no longer works with C23, because foo() is now
equivalent to foo(void).
We don't need to do this here. With a few struct forward declarations
we can supply a correct argument list without having to pull in
another header file.
(This is the only new warning with C23. Together with the previous
fix a67a49648d, this makes the whole code compile cleanly under C23.)
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://www.postgresql.org/message-id/flat/95c6a9bf-d306-43d8-b880-664ef08f2944%40eisentraut.org
If there are subqueries in the grouping expressions, each of these
subqueries in the targetlist and HAVING clause is expanded into
distinct SubPlan nodes. As a result, only one of these SubPlan nodes
would be converted to reference to the grouping key column output by
the Agg node; others would have to get evaluated afresh. This is not
efficient, and with grouping sets this can cause wrong results issues
in cases where they should go to NULL because they are from the wrong
grouping set. Furthermore, during re-evaluation, these SubPlan nodes
might use nulled column values from grouping sets, which is not
correct.
This issue is not limited to subqueries. For other types of
expressions that are part of grouping items, if they are transformed
into another form during preprocessing, they may fail to match lower
target items. This can also lead to wrong results with grouping sets.
To fix this issue, we introduce a new kind of RTE representing the
output of the grouping step, with columns that are the Vars or
expressions being grouped on. In the parser, we replace the grouping
expressions in the targetlist and HAVING clause with Vars referencing
this new RTE, so that the output of the parser directly expresses the
semantic requirement that the grouping expressions be gotten from the
grouping output rather than computed some other way. In the planner,
we first preprocess all the columns of this new RTE and then replace
any Vars in the targetlist and HAVING clause that reference this new
RTE with the underlying grouping expressions, so that we will have
only one instance of a SubPlan node for each subquery contained in the
grouping expressions.
Bump catversion because this changes the querytree produced by the
parser.
Thanks to Tom Lane for the idea to invent a new kind of RTE.
Per reports from Geoff Winkless, Tobias Wendorff, Richard Guo from
various threads.
Author: Richard Guo
Reviewed-by: Ashutosh Bapat, Sutou Kouhei
Discussion: https://postgr.es/m/CAMbWs4_dp7e7oTwaiZeBX8+P1rXw4ThkZxh1QG81rhu9Z47VsQ@mail.gmail.com
Previously, when a path type was disabled by e.g. enable_seqscan=false,
we either avoided generating that path type in the first place, or
more commonly, we added a large constant, called disable_cost, to the
estimated startup cost of that path. This latter approach can distort
planning. For instance, an extremely expensive non-disabled path
could seem to be worse than a disabled path, especially if the full
cost of that path node need not be paid (e.g. due to a Limit).
Or, as in the regression test whose expected output changes with this
commit, the addition of disable_cost can make two paths that would
normally be distinguishible in cost seem to have fuzzily the same cost.
To fix that, we now count the number of disabled path nodes and
consider that a high-order component of both the startup cost and the
total cost. Hence, the path list is now sorted by disabled_nodes and
then by total_cost, instead of just by the latter, and likewise for
the partial path list. It is important that this number is a count
and not simply a Boolean; else, as soon as we're unable to respect
disabled path types in all portions of the path, we stop trying to
avoid them where we can.
Because the path list is now sorted by the number of disabled nodes,
the join prechecks must compute the count of disabled nodes during
the initial cost phase instead of postponing it to final cost time.
Counts of disabled nodes do not cross subquery levels; at present,
there is no reason for them to do so, since the we do not postpone
path selection across subquery boundaries (see make_subplan).
Reviewed by Andres Freund, Heikki Linnakangas, and David Rowley.
Discussion: http://postgr.es/m/CA+TgmoZ_+MS+o6NeGK2xyBv-xM+w1AfFVuHE4f_aq6ekHv7YSQ@mail.gmail.com
Hash joins can support semijoin with the LHS input on the right, using
the existing logic for inner join, combined with the assurance that only
the first match for each inner tuple is considered, which can be
achieved by leveraging the HEAP_TUPLE_HAS_MATCH flag. This can be very
useful in some cases since we may now have the option to hash the
smaller table instead of the larger.
Merge join could likely support "Right Semi Join" too. However, the
benefit of swapping inputs tends to be small here, so we do not address
that in this patch.
Note that this patch also modifies a test query in join.sql to ensure it
continues testing as intended. With this patch the original query would
result in a right-semi-join rather than semi-join, compromising its
original purpose of testing the fix for neqjoinsel's behavior for
semi-joins.
Author: Richard Guo
Reviewed-by: wenhui qiu, Alena Rybakina, Japin Li
Discussion: https://postgr.es/m/CAMbWs4_X1mN=ic+SxcyymUqFx9bB8pqSLTGJ-F=MHy4PW3eRXw@mail.gmail.com
0452b461bc made optimizer explore alternative orderings of group-by pathkeys.
It eliminated preprocess_groupclause(), which was intended to match items
between GROUP BY and ORDER BY. Instead, get_useful_group_keys_orderings()
function generates orderings of GROUP BY elements at the time of grouping
paths generation. The get_useful_group_keys_orderings() function takes into
account 3 orderings of GROUP BY pathkeys and clauses: original order as written
in GROUP BY, matching ORDER BY clauses as much as possible, and matching the
input path as much as possible. Given that even before 0452b461b,
preprocess_groupclause() could change the original order of GROUP BY clauses
we don't need to consider it apart from ordering matching ORDER BY clauses.
This commit restores preprocess_groupclause() to provide an ordering of
GROUP BY elements matching ORDER BY before generation of paths. The new
version of preprocess_groupclause() takes into account an incremental sort.
The get_useful_group_keys_orderings() function now takes into 2 orderings of
GROUP BY elements: the order generated preprocess_groupclause() and the order
matching the input path as much as possible.
Discussion: https://postgr.es/m/CAPpHfdvyWLMGwvxaf%3D7KAp-z-4mxbSH8ti2f6mNOQv5metZFzg%40mail.gmail.com
Author: Alexander Korotkov
Reviewed-by: Andrei Lepikhov, Pavel Borisov
0452b461bc made optimizer explore alternative orderings of group-by pathkeys.
The PathKeyInfo data structure was used to store the particular ordering of
group-by pathkeys and corresponding clauses. It turns out that PathKeyInfo
is not the best name for that purpose. This commit renames this data structure
to GroupByOrdering, and revises its comment.
Discussion: https://postgr.es/m/db0fc3a4-966c-4cec-a136-94024d39212d%40postgrespro.ru
Reported-by: Tom Lane
Author: Andrei Lepikhov
Reviewed-by: Alexander Korotkov, Pavel Borisov
This reverts commit 7204f35919,
thus restoring 66c0185a3 (Allow planner to use Merge Append to
efficiently implement UNION) as well as the follow-on commits
d5d2205c8, 3b1a7eb28, 7487044d6.
Per further discussion on pgsql-release, we wish to ship beta1 with
this feature, and patch the bug that was found just before wrap,
rather than shipping beta1 with the feature reverted.
This reverts 66c0185a3 (Allow planner to use Merge Append to
efficiently implement UNION) as well as the follow-on commits
d5d2205c8, 3b1a7eb28, 7487044d6. In addition to those, 07746a8ef
had to be removed then re-applied in a different place, because
66c0185a3 moved the relevant code.
The reason for this last-minute thrashing is that depesz found a
case in which the patched code creates a completely wrong plan
that silently gives incorrect query results. It's unclear what
the cause is or how many cases are affected, but with beta1 wrap
staring us in the face, there's no time for closer investigation.
After we figure that out, we can decide whether to un-revert this
for beta2 or hold it for v18.
Discussion: https://postgr.es/m/Zktzf926vslR35Fv@depesz.com
(also some private discussion among pgsql-release)
94985c210 added code to detect when WindowFuncs were monotonic and
allowed additional quals to be "pushed down" into the subquery to be
used as WindowClause runConditions in order to short-circuit execution
in nodeWindowAgg.c.
The Node representation of runConditions wasn't well selected and
because we do qual pushdown before planning the subquery, the planning
of the subquery could perform subquery pull-up of nested subqueries.
For WindowFuncs with args, the arguments could be changed after pushing
the qual down to the subquery.
This was made more difficult by the fact that the code duplicated the
WindowFunc inside an OpExpr to include in the WindowClauses runCondition
field. This could result in duplication of subqueries and a pull-up of
such a subquery could result in another initplan parameter being issued
for the 2nd version of the subplan. This could result in errors such as:
ERROR: WindowFunc not found in subplan target lists
To fix this, we change the node representation of these run conditions
and instead of storing an OpExpr containing the WindowFunc in a list
inside WindowClause, we now store a new node type named
WindowFuncRunCondition within a new field in the WindowFunc. These get
transformed into OpExprs later in planning once subquery pull-up has been
performed.
This problem did exist in v15 and v16, but that was fixed by 9d36b883b
and e5d20bbd.
Cat version bump due to new node type and modifying WindowFunc struct.
Bug: #18305
Reported-by: Zuming Jiang
Discussion: https://postgr.es/m/18305-33c49b4c830b37b3%40postgresql.org
b262ad440 added code to have the planner remove redundant IS NOT NULL
quals and eliminate needless scans for IS NULL quals on tables where the
qual's column has a NOT NULL constraint.
That commit failed to consider that an inheritance parent table could
have differing NOT NULL constraints between the parent and the child.
This caused issues as if we eliminated a qual on the parent, when
applying the quals to child tables in apply_child_basequals(), the qual
might not have been added to the parent's baserestrictinfo.
Here we fix this by not applying the optimization to remove redundant
quals to RelOptInfos belonging to inheritance parents and applying the
optimization again in apply_child_basequals(). Effectively, this means
that the parent and child are considered independently as the parent has
both an inh=true and inh=false RTE and we still apply the optimization
to the RelOptInfo corresponding to the inh=false RTE.
We're able to still apply the optimization in add_base_clause_to_rel()
for partitioned tables as the NULLability of partitions must match that
of their parent. And, if we ever expand restriction_is_always_false()
and restriction_is_always_true() to handle partition constraints then we
can apply the same logic as, even in multi-level partitioned tables,
there's no way to route values to a partition when the qual does not
match the partition qual of the partitioned table's parent partition.
The same is true for CHECK constraints as those must also match between
arent partitioned tables and their partitions.
Author: Richard Guo, David Rowley
Discussion: https://postgr.es/m/CAMbWs4930gQSZmjR7aANzEapdy61gCg6z8dT-kAEYD0sYWKPdQ@mail.gmail.com
This allows MERGE commands to include WHEN NOT MATCHED BY SOURCE
actions, which operate on rows that exist in the target relation, but
not in the data source. These actions can execute UPDATE, DELETE, or
DO NOTHING sub-commands.
This is in contrast to already-supported WHEN NOT MATCHED actions,
which operate on rows that exist in the data source, but not in the
target relation. To make this distinction clearer, such actions may
now be written as WHEN NOT MATCHED BY TARGET.
Writing WHEN NOT MATCHED without specifying BY SOURCE or BY TARGET is
equivalent to writing WHEN NOT MATCHED BY TARGET.
Dean Rasheed, reviewed by Alvaro Herrera, Ted Yu and Vik Fearing.
Discussion: https://postgr.es/m/CAEZATCWqnKGc57Y_JanUBHQXNKcXd7r=0R4NEZUVwP+syRkWbA@mail.gmail.com
If we know the sort order of a CTE's output, and it is relevant
to the outer query, label the CTE's outer-query access path using
those pathkeys. This may enable optimizations such as avoiding
a sort in the outer query.
The code for hoisting pathkeys into the outer query already exists
for regular RTE_SUBQUERY subqueries, but it wasn't getting used for
CTEs, possibly out of concern for maintaining an optimization fence
between the CTE and the outer query. However, on the same arguments
used for commit f7816aec2, there seems no harm in letting the outer
query know what the inner query decided to do.
In support of this, we now remember the best Path as well as Plan
for each subquery for the rest of the planner run. There may be
future applications for having that at hand, and it surely costs
little to build one more List.
Richard Guo (minor mods by me)
Discussion: https://postgr.es/m/CAMbWs49xYd3f8CrE8-WW3--dV1zH_sDSDn-vs2DzHj81Wcnsew@mail.gmail.com
Specifically, this commit reduces the memory consumed by the
SpecialJoinInfos that are allocated for child joins in
try_partitionwise_join() by freeing them at the end of creating paths
for each child join.
A SpecialJoinInfo allocated for a given child join is a copy of the
parent join's SpecialJoinInfo, which contains the translated copies
of the various Relids bitmapsets and semi_rhs_exprs, which is a List
of Nodes. The newly added freeing step frees the struct itself and
the various bitmapsets, but not semi_rhs_exprs, because there's no
handy function to free the memory of Node trees.
Author: Ashutosh Bapat <ashutosh.bapat.oss@gmail.com>
Reviewed-by: Richard Guo <guofenglinux@gmail.com>
Reviewed-by: Amit Langote <amitlangote09@gmail.com>
Reviewed-by: Andrey Lepikhov <a.lepikhov@postgrespro.ru>
Reviewed-by: Tomas Vondra <tomas.vondra@enterprisedb.com>
Discussion: https://postgr.es/m/CAExHW5tHqEf3ASVqvFFcghYGPfpy7o3xnvhHwBGbJFMRH8KjNw@mail.gmail.com
Until now, UNION queries have often been suboptimal as the planner has
only ever considered using an Append node and making the results unique
by either using a Hash Aggregate, or by Sorting the entire Append result
and running it through the Unique operator. Both of these methods
always require reading all rows from the union subqueries.
Here we adjust the union planner so that it can request that each subquery
produce results in target list order so that these can be Merge Appended
together and made unique with a Unique node. This can improve performance
significantly as the union child can make use of the likes of btree
indexes and/or Merge Joins to provide the top-level UNION with presorted
input. This is especially good if the top-level UNION contains a LIMIT
node that limits the output rows to a small subset of the unioned rows as
cheap startup plans can be used.
Author: David Rowley
Reviewed-by: Richard Guo, Andy Fan
Discussion: https://postgr.es/m/CAApHDvpb_63XQodmxKUF8vb9M7CxyUyT4sWvEgqeQU-GB7QFoQ@mail.gmail.com
Until now PostgreSQL has not been very smart about optimizing away IS
NOT NULL base quals on columns defined as NOT NULL. The evaluation of
these needless quals adds overhead. Ordinarily, anyone who came
complaining about that would likely just have been told to not include
the qual in their query if it's not required. However, a recent bug
report indicates this might not always be possible.
Bug 17540 highlighted that when we optimize Min/Max aggregates the IS NOT
NULL qual that the planner adds to make the rewritten plan ignore NULLs
can cause issues with poor index choice. That particular case
demonstrated that other quals, especially ones where no statistics are
available to allow the planner a chance at estimating an approximate
selectivity for can result in poor index choice due to cheap startup paths
being prefered with LIMIT 1.
Here we take generic approach to fixing this by having the planner check
for NOT NULL columns and just have the planner remove these quals (when
they're not needed) for all queries, not just when optimizing Min/Max
aggregates.
Additionally, here we also detect IS NULL quals on a NOT NULL column and
transform that into a gating qual so that we don't have to perform the
scan at all. This also works for join relations when the Var is not
nullable by any outer join.
This also helps with the self-join removal work as it must replace
strict join quals with IS NOT NULL quals to ensure equivalence with the
original query.
Author: David Rowley, Richard Guo, Andy Fan
Reviewed-by: Richard Guo, David Rowley
Discussion: https://postgr.es/m/CAApHDvqg6XZDhYRPz0zgOcevSMo0d3vxA9DvHrZtKfqO30WTnw@mail.gmail.com
Discussion: https://postgr.es/m/17540-7aa1855ad5ec18b4%40postgresql.org
When evaluating a query with a multi-column GROUP BY clause, we can minimize
sort operations or avoid them if we synchronize the order of GROUP BY clauses
with the ORDER BY sort clause or sort order, which comes from the underlying
query tree. Grouping does not imply any ordering, so we can compare
the keys in arbitrary order, and a Hash Agg leverages this. But for Group Agg,
we simply compared keys in the order specified in the query. This commit
explores alternative ordering of the keys, trying to find a cheaper one.
The ordering of group keys may interact with other parts of the query, some of
which may not be known while planning the grouping. For example, there may be
an explicit ORDER BY clause or some other ordering-dependent operation higher up
in the query, and using the same ordering may allow using either incremental
sort or even eliminating the sort entirely.
The patch always keeps the ordering specified in the query, assuming the user
might have additional insights.
This introduces a new GUC enable_group_by_reordering so that the optimization
may be disabled if needed.
Discussion: https://postgr.es/m/7c79e6a5-8597-74e8-0671-1c39d124c9d6%40sigaev.ru
Author: Andrei Lepikhov, Teodor Sigaev
Reviewed-by: Tomas Vondra, Claudio Freire, Gavin Flower, Dmitry Dolgov
Reviewed-by: Robert Haas, Pavel Borisov, David Rowley, Zhihong Yu
Reviewed-by: Tom Lane, Alexander Korotkov, Richard Guo, Alena Rybakina
When SJE uses RelOptInfo.unique_for_rels cache, it passes filtered quals to
innerrel_is_unique_ext(). That might lead to an invalid match to cache entries
made by previous non self-join checking calls. Add UniqueRelInfo.self_join
flag to prevent such cases. Also, fix that SJE should require a strict match
of outerrelids to make sure UniqueRelInfo.extra_clauses are valid.
Reported-by: Alexander Lakhin
Discussion: https://postgr.es/m/4788f781-31bd-9796-d7d6-588a751c8787%40gmail.com
d3d55ce571 changed RelOptInfo.unique_for_rels from the list of Relid sets to
the list of UniqueRelInfo's. But it didn't make UniqueRelInfo a node.
This commit makes UniqueRelInfo a node. Also this commit revises some
comments related to RelOptInfo.unique_for_rels.
Reported-by: Tom Lane
Discussion: https://postgr.es/m/flat/1189851.1698340331%40sss.pgh.pa.us
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
When an UPDATE/DELETE/MERGE's target table is an old-style
inheritance tree, it's possible for the parent to get excluded
from the plan while some children are not. (I believe this is
only possible if we can prove that a CHECK ... NO INHERIT
constraint on the parent contradicts the query WHERE clause,
so it's a very unusual case.) In such a case, ExecInitModifyTable
mistakenly concluded that the first surviving child is the target
table, leading to at least two bugs:
1. The wrong table's statement-level triggers would get fired.
2. In v16 and up, it was possible to fail with "invalid perminfoindex
0 in RTE with relid nnnn" due to the child RTE not having permissions
data included in the query plan. This was hard to reproduce reliably
because it did not occur unless the update triggered some non-HOT
index updates.
In v14 and up, this is easy to fix by defining ModifyTable.rootRelation
to be the parent RTE in plain inheritance as well as partitioned cases.
While the wrong-triggers bug also appears in older branches, the
relevant code in both the planner and executor is quite a bit
different, so it would take a good deal of effort to develop and
test a suitable patch. Given the lack of field complaints about the
trigger issue, I'll desist for now. (Patching v11 for this seems
unwise anyway, given that it will have no more releases after next
month.)
Per bug #18147 from Hans Buschmann.
Amit Langote and Tom Lane
Discussion: https://postgr.es/m/18147-6fc796538913ee88@postgresql.org
