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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
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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
c65bc2e1d14a2d4daed7c1921ac518f2c5ac3d17.
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
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This is not at all needed; I suspect it was a simple mistake in commit
5408e233f066. It causes htup_details.h to bleed into a huge number of
places via execnodes.h. Remove it and fix fallout.
Discussion: https://postgr.es/m/202510021240.ptc2zl5cvwen@alvherre.pgsql
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Add IGNORE NULLS/RESPECT NULLS option (null treatment clause) to lead,
lag, first_value, last_value and nth_value window functions. If
unspecified, the default is RESPECT NULLS which includes NULL values
in any result calculation. IGNORE NULLS ignores NULL values.
Built-in window functions are modified to call new API
WinCheckAndInitializeNullTreatment() to indicate whether they accept
IGNORE NULLS/RESPECT NULLS option or not (the API can be called by
user defined window functions as well). If WinGetFuncArgInPartition's
allowNullTreatment argument is true and IGNORE NULLS option is given,
WinGetFuncArgInPartition() or WinGetFuncArgInFrame() will return
evaluated function's argument expression on specified non NULL row (if
it exists) in the partition or the frame.
When IGNORE NULLS option is given, window functions need to visit and
evaluate same rows over and over again to look for non null rows. To
mitigate the issue, 2-bit not null information array is created while
executing window functions to remember whether the row has been
already evaluated to NULL or NOT NULL. If already evaluated, we could
skip the evaluation work, thus we could get better performance.
Author: Oliver Ford <ojford@gmail.com>
Co-authored-by: Tatsuo Ishii <ishii@postgresql.org>
Reviewed-by: Krasiyan Andreev <krasiyan@gmail.com>
Reviewed-by: Andrew Gierth <andrew@tao11.riddles.org.uk>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: David Fetter <david@fetter.org>
Reviewed-by: Vik Fearing <vik@postgresfriends.org>
Reviewed-by: "David G. Johnston" <david.g.johnston@gmail.com>
Reviewed-by: Chao Li <lic@highgo.com>
Discussion: https://postgr.es/m/flat/CAGMVOdsbtRwE_4+v8zjH1d9xfovDeQAGLkP_B6k69_VoFEgX-A@mail.gmail.com
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Commit a391ff3c3, which added the ability for a function's support
function to provide a custom selectivity estimate for "WHERE f(...)",
unintentionally removed the possibility of applying expression
statistics after finding there's no applicable support function.
That happened because we no longer fell through to boolvarsel()
as before. Refactor to do so again, putting the 0.3333333 default
back into boolvarsel() where it had been (cf. commit 39df0f150).
I surely wouldn't have made this error if 39df0f150 had included
a test case, so add one now. At the time we did not have the
"extended statistics" infrastructure, but we do now, and it is
also unable to work in this scenario because of this error.
So make use of that for the test case.
This is very clearly a bug fix, but I'm afraid to put it into
released branches because of the likelihood of altering plan
choices, which we avoid doing in minor releases. So, master only.
Reported-by: Frédéric Yhuel <frederic.yhuel@dalibo.com>
Author: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://postgr.es/m/a8b99dce-1bfb-4d97-af73-54a32b85c916@dalibo.com
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JsonConstructorExpr can produce non-NULL output with a NULL input, so
it should be treated as a non-strict construct. Failing to do so can
lead to incorrect query behavior.
For example, in the reported case, when pulling up a subquery that is
under an outer join, if the subquery's target list contains a
JsonConstructorExpr that uses subquery variables and it is mistakenly
treated as strict, it will be pulled up without being wrapped in a
PlaceHolderVar. As a result, the expression will be evaluated at the
wrong place and will not be forced to null when the outer join should
do so.
Back-patch to v16 where JsonConstructorExpr was introduced.
Bug: #19046
Reported-by: Runyuan He <runyuan@berkeley.edu>
Author: Tender Wang <tndrwang@gmail.com>
Co-authored-by: Richard Guo <guofenglinux@gmail.com>
Discussion: https://postgr.es/m/19046-765b6602b0a8cfdf@postgresql.org
Backpatch-through: 16
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Virtual generated columns in constraint expressions need to be
expanded because the optimizer matches these expressions to qual
clauses. Failing to do so can cause us to miss opportunities for
constraint exclusion.
Author: Richard Guo <guofenglinux@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/204804c0-798f-4c72-bd1f-36116024fda3%40eisentraut.org
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The typedef Relids (Bitmapset *) is intended to represent set of
relation identifiers, but was incorrectly used in several places to
store sets of attribute numbers. This is my oversight in e2debb643.
Fix that by replacing such usages with Bitmapset * to reflect the
correct semantics.
Author: Junwang Zhao <zhjwpku@gmail.com>
Reviewed-by: Tender Wang <tndrwang@gmail.com>
Reviewed-by: Richard Guo <guofenglinux@gmail.com>
Discussion: https://postgr.es/m/CAEG8a3LJhp_xriXf39iCz0TsK+M-2biuhDhpLC6Baxw8+ZYT3A@mail.gmail.com
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Constraint expressions and statistics expressions loaded from the
system catalogs need to be run through const-simplification, because
the planner will be comparing them to similarly-processed qual
clauses. Without this step, the planner may fail to detect valid
matches.
Currently, NullTest clauses in these expressions may not be reduced
correctly during const-simplification. This happens because their Var
nodes do not yet have the correct varno when eval_const_expressions is
applied. Since eval_const_expressions relies on varno to reduce
NullTest quals, incorrect varno can cause problems.
Additionally, for statistics expressions, eval_const_expressions is
called with root set to NULL, which also inhibits NullTest reduction.
This patch fixes the issue by ensuring that Vars are updated to have
the correct varno before const-simplification, and that a valid root
is passed to eval_const_expressions when needed.
Author: Richard Guo <guofenglinux@gmail.com>
Discussion: https://postgr.es/m/19007-4cc6e252ed8aa54a@postgresql.org
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It's possible that if the only live partition is concurrently dropped
and try_table_open() fails, that the bms_del_member() will pfree the
live_parts Bitmapset. Since the bms_del_member() call does not assign
the result back to the live_parts local variable, the while loop could
segfault as that variable would still reference the pfree'd Bitmapset.
Backpatch to 15. 52f3de874 was backpatched to 14, but there's no
bms_del_member() there due to live_parts not yet existing in RelOptInfo in
that version. Technically there's no bug in version 15 as
bms_del_member() didn't pfree when the set became empty prior to
00b41463c (from v16). Applied to v15 anyway to keep the code similar and
to avoid the bad coding pattern.
Author: Bernd Reiß <bd_reiss@gmx.at>
Reviewed-by: David Rowley <dgrowleyml@gmail.com>
Discussion: https://postgr.es/m/6b88f27a-c45c-4826-8e37-d61a04d90182@gmx.at
Backpatch-through: 15
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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
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Commit 9e6104c66 disallowed transition tables on foreign tables, but
failed to account for cases where a foreign table is a child table of a
partitioned/inherited table on which transition tables exist, leading to
incorrect transition tuples collected from such foreign tables for
queries on the parent table triggering transition capture. This
occurred not only for inherited UPDATE/DELETE but for partitioned INSERT
later supported by commit 3d956d956, which should have handled it at
least for the INSERT case, but didn't.
To fix, modify ExecAR*Triggers to throw an error if the given relation
is a foreign table requesting transition capture. Also, this commit
fixes make_modifytable so that in case of an inherited UPDATE/DELETE
triggering transition capture, FDWs choose normal operations to modify
child foreign tables, not DirectModify; which is needed because they
would otherwise skip the calls to ExecAR*Triggers at execution, causing
unexpected behavior.
Author: Etsuro Fujita <etsuro.fujita@gmail.com>
Reviewed-by: Amit Langote <amitlangote09@gmail.com>
Discussion: https://postgr.es/m/CAPmGK14QJYikKzBDCe3jMbpGENnQ7popFmbEgm-XTNuk55oyHg%40mail.gmail.com
Backpatch-through: 13
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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
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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
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For an ordered Append or MergeAppend, we need to inject an explicit
sort into any subpath that is not already well enough ordered.
Currently, only explicit full sorts are considered; incremental sorts
are not yet taken into account.
In this patch, for subpaths of an ordered Append or MergeAppend, we
choose to use explicit incremental sort if it is enabled and there are
presorted keys.
The rationale is based on the assumption that incremental sort is
always faster than full sort when there are presorted keys, a premise
that has been applied in various parts of the code. In addition, the
current cost model tends to favor incremental sort as being cheaper
than full sort in the presence of presorted keys, making it reasonable
not to consider full sort in such cases.
No backpatch as this could result in plan changes.
Author: Richard Guo <guofenglinux@gmail.com>
Reviewed-by: Andrei Lepikhov <lepihov@gmail.com>
Reviewed-by: Robert Haas <robertmhaas@gmail.com>
Discussion: https://postgr.es/m/CAMbWs4_V7a2enTR+T3pOY_YZ-FU8ZsFYym2swOz4jNMqmSgyuw@mail.gmail.com
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If, after removal of useless null-constant arguments, a CoalesceExpr
has exactly one remaining argument, we can just take that argument as
the result, without bothering to wrap a new CoalesceExpr around it.
This isn't likely to produce any great improvement in runtime per se,
but it can lead to better plans since the planner no longer has to
treat the expression as non-strict.
However, there were a few regression test cases that intentionally
wrote COALESCE(x) as a shorthand way of creating a non-strict
subexpression. To avoid ruining the intent of those tests, write
COALESCE(x,x) instead. (If anyone ever proposes de-duplicating
COALESCE arguments, we'll need another iteration of this arms race.
But it seems pretty unlikely that such an optimization would be
worthwhile.)
Author: Maksim Milyutin <maksim.milyutin@tantorlabs.ru>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://postgr.es/m/8e8573c3-1411-448d-877e-53258b7b2be0@tantorlabs.ru
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In the wake of commit a16ef313f, we need to deal with more cases
involving PlaceHolderVars in NestLoopParams than we did before.
For one thing, a16ef313f was incorrect to suppose that we could
rely on the required-outer relids of the lefthand path to decide
placement of nestloop-parameter PHVs. As Richard Guo argued at
the time, we must look at the required-outer relids of the join
path itself.
For another, we have to apply replace_nestloop_params() to such
a PHV's expression, in case it contains references to values that
will be supplied from NestLoopParams of higher-level nestloops.
For another, we need to be more careful about the phnullingrels
of the PHV than we were being. identify_current_nestloop_params
only bothered to ensure that the phnullingrels didn't contain
"too many" relids, but now it has to be exact, because setrefs.c
will apply both NRM_SUBSET and NRM_SUPERSET checks in different
places. We can compute the correct relids by determining the
set of outer joins that should be able to null the PHV and then
subtracting whatever's been applied at or below this join.
Do the same for plain Vars, too. (This should make it possible
to use NRM_EQUAL to process nestloop params in setrefs.c, but
I won't risk making such a change in v18 now.)
Lastly, if a nestloop parameter PHV was pulled up out of a subquery
and it contains a subquery that was originally pushed down from this
query level, then that will still be represented as a SubLink, because
SS_process_sublinks won't recurse into outer PHVs, so it didn't get
transformed during expression preprocessing in the subquery. We can
substitute the version of the PHV's expression appearing in its
PlaceHolderInfo to ensure that that preprocessing has happened.
(Seems like this processing sequence could stand to be redesigned,
but again, late in v18 development is not the time for that.)
It's not very clear to me why the old have_dangerous_phv join-order
restriction prevented us from seeing the last three of these problems.
But given the lack of field complaints, it must have done so.
Reported-by: Alexander Lakhin <exclusion@gmail.com>
Author: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://postgr.es/m/18953-1c9883a9d4afeb30@postgresql.org
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Commit 85e5e222b, which added (a forerunner of) this logic,
argued that
Adding the necessary complexity to make this work doesn't seem like
it would be repaid in significantly better plans, because in cases
where such a PHV exists, there is probably a corresponding join order
constraint that would allow a good plan to be found without using the
star-schema exception.
The flaw in this claim is that there may be other join-order
restrictions that prevent us from finding a join order that doesn't
involve a "dangerous" PHV. In particular we now recognize that
small join_collapse_limit or from_collapse_limit could prevent it.
Therefore, let's bite the bullet and make the case work.
We don't have to extend the executor's support for nestloop parameters
as I thought at the time, because we can instead push the evaluation
of the placeholder's expression into the left-hand input of the
NestLoop node. So there's not really a lot of downside to this
solution, and giving the planner more join-order flexibility should
have value beyond just avoiding failure.
Having said that, there surely is a nonzero risk of introducing
new bugs. Since this failure mode escaped detection for ten years,
such cases don't seem common enough to justify a lot of risk.
Therefore, let's put this fix into master but leave the back branches
alone (for now anyway).
Bug: #18953
Reported-by: Alexander Lakhin <exclusion@gmail.com>
Diagnosed-by: Richard Guo <guofenglinux@gmail.com>
Author: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://postgr.es/m/18953-1c9883a9d4afeb30@postgresql.org
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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
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This allows them to be added without scanning the table, and validating
them afterwards without holding access exclusive lock on the table after
any violating rows have been deleted or fixed.
Doing ALTER TABLE ... SET NOT NULL for a column that has an invalid
not-null constraint validates that constraint. ALTER TABLE .. VALIDATE
CONSTRAINT is also supported. There are various checks on whether an
invalid constraint is allowed in a child table when the parent table has
a valid constraint; this should match what we do for enforced/not
enforced constraints.
pg_attribute.attnotnull is now only an indicator for whether a not-null
constraint exists for the column; whether it's valid or invalid must be
queried in pg_constraint. Applications can continue to query
pg_attribute.attnotnull as before, but now it's possible that NULL rows
are present in the column even when that's set to true.
For backend internal purposes, we cache the nullability status in
CompactAttribute->attnullability that each tuple descriptor carries
(replacing CompactAttribute.attnotnull, which was a mirror of
Form_pg_attribute.attnotnull). During the initial tuple descriptor
creation, based on the pg_attribute scan, we set this to UNRESTRICTED if
pg_attribute.attnotnull is false, or to UNKNOWN if it's true; then we
update the latter to VALID or INVALID depending on the pg_constraint
scan. This flag is also copied when tupledescs are copied.
Comparing tuple descs for equality must also compare the
CompactAttribute.attnullability flag and return false in case of a
mismatch.
pg_dump deals with these constraints by storing the OIDs of invalid
not-null constraints in a separate array, and running a query to obtain
their properties. The regular table creation SQL omits them entirely.
They are then dealt with in the same way as "separate" CHECK
constraints, and dumped after the data has been loaded. Because no
additional pg_dump infrastructure was required, we don't bump its
version number.
I decided not to bump catversion either, because the old catalog state
works perfectly in the new world. (Trying to run with new catalog state
and the old server version would likely run into issues, however.)
System catalogs do not support invalid not-null constraints (because
commit 14e87ffa5c54 didn't allow them to have pg_constraint rows
anyway.)
Author: Rushabh Lathia <rushabh.lathia@gmail.com>
Author: Jian He <jian.universality@gmail.com>
Reviewed-by: Álvaro Herrera <alvherre@alvh.no-ip.org>
Tested-by: Ashutosh Bapat <ashutosh.bapat.oss@gmail.com>
Discussion: https://postgr.es/m/CAGPqQf0KitkNack4F5CFkFi-9Dqvp29Ro=EpcWt=4_hs-Rt+bQ@mail.gmail.com
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There were several places in ordering-related planning where a
requirement for btree was hardcoded but an amcanorder index could
suffice. This fixes that. We just need to do the necessary mapping
between strategy numbers and compare types and adjust some related
APIs so that this works independent of btree strategy numbers. For
instance, non-btree amcanorder indexes can now be used to support
sorting and merge joins. Also, predtest.c works independent of btree
strategy numbers now.
To avoid performance regressions, some details on btree and other
built-in index types are still hardcoded as shortcuts, but other index
types now have access to the same features by providing the required
flags and callbacks.
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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This commit implements the automatic conversion of 'x IN (VALUES ...)' into
ScalarArrayOpExpr. That simplifies the query tree, eliminating the appearance
of an unnecessary join.
Since VALUES describes a relational table, and the value of such a list is
a table row, the optimizer will likely face an underestimation problem due to
the inability to estimate cardinality through MCV statistics. The cardinality
evaluation mechanism can work with the array inclusion check operation.
If the array is small enough (< 100 elements), it will perform a statistical
evaluation element by element.
We perform the transformation in the convert_ANY_sublink_to_join() if VALUES
RTE is proper and the transformation is convertible. The conversion is only
possible for operations on scalar values, not rows. Also, we currently
support the transformation only when it ends up with a constant array.
Otherwise, the evaluation of non-hashed SAOP might be slower than the
corresponding Hash Join with VALUES.
Discussion: https://postgr.es/m/0184212d-1248-4f1f-a42d-f5cb1c1976d2%40tantorlabs.com
Author: Alena Rybakina <a.rybakina@postgrespro.ru>
Author: Andrei Lepikhov <lepihov@gmail.com>
Reviewed-by: Ivan Kush <ivan.kush@tantorlabs.com>
Reviewed-by: Alexander Korotkov <aekorotkov@gmail.com>
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This commit extracts the code to generate ScalarArrayOpExpr on top of the list
of expressions from match_orclause_to_indexcol() into a separate function
make_SAOP_expr(). This function was extracted to be used in optimization for
conversion of 'x IN (VALUES ...)' to 'x = ANY ...'. make_SAOP_expr() is
placed in clauses.c file as only two additional headers were needed there
compared with other places.
Discussion: https://postgr.es/m/0184212d-1248-4f1f-a42d-f5cb1c1976d2%40tantorlabs.com
Author: Alena Rybakina <a.rybakina@postgrespro.ru>
Author: Andrei Lepikhov <lepihov@gmail.com>
Reviewed-by: Ivan Kush <ivan.kush@tantorlabs.com>
Reviewed-by: Alexander Korotkov <aekorotkov@gmail.com>
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The check for non-inheritable constraints is performed later, and the
same comment is included at that point.
While we're here, remove one extraneous blank line.
Author: jian he <jian.universality@gmail.com>
Reviewed-by: Kirill Reshke <reshkekirill@gmail.com>
Reviewed-by: Richard Guo <guofenglinux@gmail.com>
Discussion: https://postgr.es/m/CACJufxETi6x86S8EkH8mRfOcm2AenoE9t1pyCFVMpU34gVhF3w@mail.gmail.com
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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 expands the NOT ENFORCED constraint flag, previously only
supported for CHECK constraints (commit ca87c415e2f), to foreign key
constraints.
Normally, when a foreign key constraint is created on a table, action
and check triggers are added to maintain data integrity. With this
patch, if a constraint is marked as NOT ENFORCED, integrity checks are
no longer required, making these triggers unnecessary. Consequently,
when creating a NOT ENFORCED foreign key constraint, triggers will not
be created, and the constraint will be marked as NOT VALID.
Similarly, if an existing foreign key constraint is changed to NOT
ENFORCED, the associated triggers will be dropped, and the constraint
will also be marked as NOT VALID. Conversely, if a NOT ENFORCED
foreign key constraint is changed to ENFORCED, the necessary triggers
will be created, and the will be changed to VALID by performing
necessary validation.
Since not-enforced foreign key constraints have no triggers, the
shortcut used for example in psql and pg_dump to skip looking for
foreign keys if the relation is known not to have triggers no longer
applies. (It already didn't work for partitioned tables.)
Author: Amul Sul <sulamul@gmail.com>
Reviewed-by: Joel Jacobson <joel@compiler.org>
Reviewed-by: Andrew Dunstan <andrew@dunslane.net>
Reviewed-by: Peter Eisentraut <peter@eisentraut.org>
Reviewed-by: jian he <jian.universality@gmail.com>
Reviewed-by: Alvaro Herrera <alvherre@alvh.no-ip.org>
Reviewed-by: Ashutosh Bapat <ashutosh.bapat.oss@gmail.com>
Reviewed-by: Isaac Morland <isaac.morland@gmail.com>
Reviewed-by: Alexandra Wang <alexandra.wang.oss@gmail.com>
Tested-by: Triveni N <triveni.n@enterprisedb.com>
Discussion: https://www.postgresql.org/message-id/flat/CAAJ_b962c5AcYW9KUt_R_ER5qs3fUGbe4az-SP-vuwPS-w-AGA@mail.gmail.com
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50e17ad28 (v14) and 29f45e299 (v15) made it so the planner could identify
IN and NOT IN clauses which have Const lists as right-hand arguments and
when an appropriate hash function is available for the data types, mark
the ScalarArrayOpExpr as hashable so the executor could execute it more
optimally by building and probing a hash table during expression
evaluation.
These commits both worked correctly when there was only a single
ScalarArrayOpExpr in the given expression being processed by the
planner, but when there were multiple, only the first was checked and any
subsequent ones were not identified, which resulted in less optimal
expression evaluation during query execution for all but the first found
ScalarArrayOpExpr.
Backpatch to 14, where 50e17ad28 was introduced.
Author: David Geier <geidav.pg@gmail.com>
Discussion: https://postgr.es/m/29a76f51-97b0-4c07-87b7-ec8e3b5345c9@gmail.com
Backpatch-through: 14
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After pushing the bitmap iterator into table-AM specific code (as part
of making bitmap heap scan use the read stream API in 2b73a8cd33b7),
scan_bitmap_next_block() no longer returns the current block number.
Since scan_bitmap_next_block() isn't returning any relevant information
to bitmap table scan code, it makes more sense to get rid of it.
Now, bitmap table scan code only calls table_scan_bitmap_next_tuple(),
and the heap AM implementation of scan_bitmap_next_block() is a local
helper in heapam_handler.c.
Reviewed-by: Tomas Vondra <tomas@vondra.me>
Discussion: https://postgr.es/m/flat/CAAKRu_ZwCwWFeL_H3ia26bP2e7HiKLWt0ZmGXPVwPO6uXq0vaA%40mail.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 adds support for the NOT ENFORCED/ENFORCED flag for constraints,
with support for check constraints.
The plan is to eventually support this for foreign key constraints,
where it is typically more useful.
Note that CHECK constraints do not currently support ALTER operations,
so changing the enforceability of an existing constraint isn't
possible without dropping and recreating it. This could be added
later.
Author: Amul Sul <amul.sul@enterprisedb.com>
Reviewed-by: Peter Eisentraut <peter@eisentraut.org>
Reviewed-by: jian he <jian.universality@gmail.com>
Tested-by: Triveni N <triveni.n@enterprisedb.com>
Discussion: https://www.postgresql.org/message-id/flat/CAAJ_b962c5AcYW9KUt_R_ER5qs3fUGbe4az-SP-vuwPS-w-AGA@mail.gmail.com
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Backpatch-through: 13
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The new compact_attrs array stores a few select fields from
FormData_pg_attribute in a more compact way, using only 16 bytes per
column instead of the 104 bytes that FormData_pg_attribute uses. Using
CompactAttribute allows performance-critical operations such as tuple
deformation to be performed without looking at the FormData_pg_attribute
element in TupleDesc which means fewer cacheline accesses.
For some workloads, tuple deformation can be the most CPU intensive part
of processing the query. Some testing with 16 columns on a table
where the first column is variable length showed around a 10% increase in
transactions per second for an OLAP type query performing aggregation on
the 16th column. However, in certain cases, the increases were much
higher, up to ~25% on one AMD Zen4 machine.
This also makes pg_attribute.attcacheoff redundant. A follow-on commit
will remove it, thus shrinking the FormData_pg_attribute struct by 4
bytes.
Author: David Rowley
Reviewed-by: Andres Freund, Victor Yegorov
Discussion: https://postgr.es/m/CAApHDvrBztXP3yx=NKNmo3xwFAFhEdyPnvrDg3=M0RhDs+4vYw@mail.gmail.com
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Remove the code for inserting flag columns in the inputs of a SetOp.
That was the only reason why there would be resjunk columns in a
set-operations plan tree, so we can get rid of some code that
supported that, too.
Get rid of choose_hashed_setop() in favor of building Paths for
the hashed and sorted alternatives, and letting them fight it out
within add_path().
Remove set_operation_ordered_results_useful(), which was giving wrong
answers due to examining the wrong ancestor node: we need to examine
the immediate SetOperationStmt parent not the topmost node. Instead
make each caller of recurse_set_operations() pass down the relevant
parent node. (This thinko seems to have led only to wasted planning
cycles and possibly-inferior plans, not wrong query answers. Perhaps
we should back-patch it, but I'm not doing so right now.)
Teach generate_nonunion_paths() to consider pre-sorted inputs for
sorted SetOps, rather than always generating a Sort node.
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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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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Ryo Kanbayashi
Discussion: https://postgr.es/m/CANOn0ExEQiPVrzkjULkENVac_n4Lknm6dxsU69MSncQap0kJVA%40mail.gmail.com
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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
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Many of them just seem to have been copied around for no real reason.
Their presence causes (small) risks of hiding actual type mismatches
or silently discarding qualifiers
Discussion: https://www.postgresql.org/message-id/flat/461ea37c-8b58-43b4-9736-52884e862820@eisentraut.org
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The function get_param_path_clause_serials() is used to get the set of
pushed-down clauses enforced within a parameterized Path. Since we
don't currently support parameterized MergeAppend paths, and it
doesn't look like that is going to change anytime soon (as explained
in the comments for generate_orderedappend_paths), we don't need to
consider MergeAppendPath in this function.
This change won't make any measurable difference in performance; it's
just for clarity's sake.
Author: Richard Guo
Reviewed-by: Andrei Lepikhov
Discussion: https://postgr.es/m/CAMbWs4_Puie4DQ2ODvjQB_3CxYkUODnrJm8jn_ObMAcrjYNW7Q@mail.gmail.com
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When optimizer generates bitmap paths, it considers breaking OR-clause
arguments one-by-one. But now, a group of similar OR-clauses can be
transformed into SAOP during index matching. So, bitmap paths should
keep up.
This commit teaches bitmap paths generation machinery to group similar
OR-clauses into dedicated RestrictInfos. Those RestrictInfos are considered
both to match index as a whole (as SAOP), or to match as a set of individual
OR-clause argument one-by-one (the old way).
Therefore, bitmap path generation will takes advantage of OR-clauses to SAOP's
transformation. The old way of handling them is also considered. So, there
shouldn't be planning regression.
Discussion: https://postgr.es/m/CAPpHfdu5iQOjF93vGbjidsQkhHvY2NSm29duENYH_cbhC6x%2BMg%40mail.gmail.com
Author: Alexander Korotkov, Andrey Lepikhov
Reviewed-by: Alena Rybakina, Andrei Lepikhov, Jian he, Robert Haas
Reviewed-by: Peter Geoghegan
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We now create contype='n' pg_constraint rows for not-null constraints on
user tables. Only one such constraint is allowed for a column.
We propagate these constraints to other tables during operations such as
adding inheritance relationships, creating and attaching partitions and
creating tables LIKE other tables. These related constraints mostly
follow the well-known rules of conislocal and coninhcount that we have
for CHECK constraints, with some adaptations: for example, as opposed to
CHECK constraints, we don't match not-null ones by name when descending
a hierarchy to alter or remove it, instead matching by the name of the
column that they apply to. This means we don't require the constraint
names to be identical across a hierarchy.
The inheritance status of these constraints can be controlled: now we
can be sure that if a parent table has one, then all children will have
it as well. They can optionally be marked NO INHERIT, and then children
are free not to have one. (There's currently no support for altering a
NO INHERIT constraint into inheriting down the hierarchy, but that's a
desirable future feature.)
This also opens the door for having these constraints be marked NOT
VALID, as well as allowing UNIQUE+NOT NULL to be used for functional
dependency determination, as envisioned by commit e49ae8d3bc58. It's
likely possible to allow DEFERRABLE constraints as followup work, as
well.
psql shows these constraints in \d+, though we may want to reconsider if
this turns out to be too noisy. Earlier versions of this patch hid
constraints that were on the same columns of the primary key, but I'm
not sure that that's very useful. If clutter is a problem, we might be
better off inventing a new \d++ command and not showing the constraints
in \d+.
For now, we omit these constraints on system catalog columns, because
they're unlikely to achieve anything.
The main difference to the previous attempt at this (b0e96f311985) is
that we now require that such a constraint always exists when a primary
key is in the column; we didn't require this previously which had a
number of unpalatable consequences. With this requirement, the code is
easier to reason about. For example:
- We no longer have "throwaway constraints" during pg_dump. We needed
those for the case where a table had a PK without a not-null
underneath, to prevent a slow scan of the data during restore of the
PK creation, which was particularly problematic for pg_upgrade.
- We no longer have to cope with attnotnull being set spuriously in
case a primary key is dropped indirectly (e.g., via DROP COLUMN).
Some bits of code in this patch were authored by Jian He.
Author: Álvaro Herrera <alvherre@alvh.no-ip.org>
Author: Bernd Helmle <mailings@oopsware.de>
Reviewed-by: 何建 (jian he) <jian.universality@gmail.com>
Reviewed-by: 王刚 (Tender Wang) <tndrwang@gmail.com>
Reviewed-by: Justin Pryzby <pryzby@telsasoft.com>
Reviewed-by: Peter Eisentraut <peter.eisentraut@enterprisedb.com>
Reviewed-by: Dean Rasheed <dean.a.rasheed@gmail.com>
Discussion: https://postgr.es/m/202408310358.sdhumtyuy2ht@alvherre.pgsql
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If the collation of any join key column doesn’t match the collation of
the corresponding partition key, partitionwise joins can yield incorrect
results. For example, rows that would match under the join key collation
might be located in different partitions due to the partitioning
collation. In such cases, a partitionwise join would yield different
results from a non-partitionwise join, so disallow it in such cases.
Reported-by: Tender Wang <tndrwang@gmail.com>
Author: Jian He <jian.universality@gmail.com>
Reviewed-by: Tender Wang <tndrwang@gmail.com>
Reviewed-by: Junwang Zhao <zhjwpku@gmail.com>
Discussion: https://postgr.es/m/CAHewXNno_HKiQ6PqyLYfuqDtwp7KKHZiH1J7Pqyz0nr+PS2Dwg@mail.gmail.com
Backpatch-through: 12
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When we generate multiple clones of the same qual condition to cope
with outer join identity 3, we need to ensure that all the clones get
the same serial number. To achieve this, we reset the
root->last_rinfo_serial counter each time we produce RestrictInfo(s)
from the qual list (see deconstruct_distribute_oj_quals). This
approach works only if we ensure that we are not changing the qual
list in any way that'd affect the number of RestrictInfos built from
it.
However, with b262ad440, an IS NULL qual on a NOT NULL column might
result in an additional constant-FALSE RestrictInfo. And different
versions of the same qual clause can lead to different conclusions
about whether it can be reduced to constant-FALSE. This would affect
the number of RestrictInfos built from the qual list for different
versions, causing inconsistent RestrictInfo serial numbers across
multiple clones of the same qual. This inconsistency can confuse
users of these serial numbers, such as rebuild_joinclause_attr_needed,
and lead to planner errors such as "ERROR: variable not found in
subplan target lists".
To fix, reset the root->last_rinfo_serial counter after generating the
additional constant-FALSE RestrictInfo.
Back-patch to v17 where the issue crept in. In v17, I failed to make
a test case that would expose this bug, so no test case for v17.
Author: Richard Guo
Discussion: https://postgr.es/m/CAMbWs4-B6kafn+LmPuh-TYFwFyEm-vVj3Qqv7Yo-69CEv14rRg@mail.gmail.com
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The decision in b6e1157e7 to ignore raw_expr when evaluating a
JsonValueExpr was incorrect. While its value is not ultimately
used (since formatted_expr's value is), failing to initialize it
can lead to problems, for instance, when the expression tree in
raw_expr contains Aggref nodes, which must be initialized to
ensure the parent Agg node works correctly.
Also, optimize eval_const_expressions_mutator()'s handling of
JsonValueExpr a bit. Currently, when formatted_expr cannot be folded
into a constant, we end up processing it twice -- once directly in
eval_const_expressions_mutator() and again recursively via
ece_generic_processing(). This recursive processing is required to
handle raw_expr. To avoid the redundant processing of formatted_expr,
we now process raw_expr directly in eval_const_expressions_mutator().
Finally, update the comment of JsonValueExpr to describe the roles of
raw_expr and formatted_expr more clearly.
Bug: #18657
Reported-by: Alexander Lakhin <exclusion@gmail.com>
Diagnosed-by: Fabio R. Sluzala <fabio3rs@gmail.com>
Diagnosed-by: Tender Wang <tndrwang@gmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://postgr.es/m/18657-1b90ccce2b16bdb8@postgresql.org
Backpatch-through: 16
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Up to now, remove_rel_from_query() has done a pretty shoddy job
of updating our where-needed bitmaps (per-Var attr_needed and
per-PlaceHolderVar ph_needed relid sets). It removed direct mentions
of the to-be-removed baserel and outer join, which is the minimum
amount of effort needed to keep the data structures self-consistent.
But it didn't account for the fact that the removed join ON clause
probably mentioned Vars of other relations, and those Vars might now
not be needed as high up in the join tree as before. It's easy to
show cases where this results in failing to remove a lower outer join
that could also have been removed.
To fix, recalculate the where-needed bitmaps from scratch after
each successful join removal. This sounds expensive, but it seems
to add only negligible planner runtime. (We cheat a little bit
by preserving "relation 0" entries in the bitmaps, allowing us to
skip re-scanning the targetlist and HAVING qual.)
The submitted test case drew attention because we had successfully
optimized away the lower join prior to v16. I suspect that that's
somewhat accidental and there are related cases that were never
optimized before and now can be. I've not tried to come up with
one, though.
Perhaps we should back-patch this into v16 and v17 to repair the
performance regression. However, since it took a year for anyone
to notice the problem, it can't be affecting too many people. Let's
let the patch bake awhile in HEAD, and see if we get more complaints.
Per bug #18627 from Mikaël Gourlaouen. No back-patch for now.
Discussion: https://postgr.es/m/18627-44f950eb6a8416c2@postgresql.org
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Add WITHOUT OVERLAPS clause to PRIMARY KEY and UNIQUE constraints.
These are backed by GiST indexes instead of B-tree indexes, since they
are essentially exclusion constraints with = for the scalar parts of
the key and && for the temporal part.
(previously committed as 46a0cd4cefb, reverted by 46a0cd4cefb; the new
part is this:)
Because 'empty' && 'empty' is false, the temporal PK/UQ constraint
allowed duplicates, which is confusing to users and breaks internal
expectations. For instance, when GROUP BY checks functional
dependencies on the PK, it allows selecting other columns from the
table, but in the presence of duplicate keys you could get the value
from any of their rows. So we need to forbid empties.
This all means that at the moment we can only support ranges and
multiranges for temporal PK/UQs, unlike the original patch (above).
Documentation and tests for this are added. But this could
conceivably be extended by introducing some more general support for
the notion of "empty" for other types.
Author: Paul A. Jungwirth <pj@illuminatedcomputing.com>
Reviewed-by: Peter Eisentraut <peter@eisentraut.org>
Reviewed-by: jian he <jian.universality@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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The only current implementation is for btree where it calls
_bt_getrootheight(). Other index types can now also use this to pass
information to their amcostestimate routine. Previously, btree was
hardcoded and other index types could not hook into the optimizer at
this point.
Author: 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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When generating window_pathkeys, distinct_pathkeys, or sort_pathkeys,
we failed to realize that the grouping/ordering expressions might be
nullable by grouping sets. As a result, we may incorrectly deem that
the PathKeys are redundant by EquivalenceClass processing and thus
remove them from the pathkeys list. That would lead to wrong results
in some cases.
To fix this issue, we mark the grouping expressions nullable by
grouping sets if that is the case. If the grouping expression is a
Var or PlaceHolderVar or constructed from those, we can just add the
RT index of the RTE_GROUP RTE to the existing nullingrels field(s);
otherwise we have to add a PlaceHolderVar to carry on the nullingrel
bit.
However, we have to manually remove this nullingrel bit from
expressions in various cases where these expressions are logically
below the grouping step, such as when we generate groupClause pathkeys
for grouping sets, or when we generate PathTarget for initial input to
grouping nodes.
Furthermore, in set_upper_references, the targetlist and quals of an
Agg node should have nullingrels that include the effects of the
grouping step, ie they will have nullingrels equal to the input
Vars/PHVs' nullingrels plus the nullingrel bit that references the
grouping RTE. In order to perform exact nullingrels matches, we also
need to manually remove this nullingrel bit.
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
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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
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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
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