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
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
To determine if the two relations being joined can use partitionwise
join, we need to verify the existence of equi-join conditions
involving pairs of matching partition keys for all partition keys.
Currently we do that by looking through the join's restriction
clauses. However, it has been discovered that this approach is
insufficient, because there might be partition keys known equal by a
specific EC, but they do not form a join clause because it happens
that other members of the EC than the partition keys are constrained
to become a join clause.
To address this issue, in addition to examining the join's restriction
clauses, we also check if any partition keys are known equal by ECs,
by leveraging function exprs_known_equal(). To accomplish this, we
enhance exprs_known_equal() to check equality per the semantics of the
opfamily, if provided.
It could be argued that exprs_known_equal() could be called O(N^2)
times, where N is the number of partition key expressions, resulting
in noticeable performance costs if there are a lot of partition key
expressions. But I think this is not a problem. The number of a
joinrel's partition key expressions would only be equal to the join
degree, since each base relation within the join contributes only one
partition key expression. That is to say, it does not scale with the
number of partitions. A benchmark with a query involving 5-way joins
of partitioned tables, each with 3 partition keys and 1000 partitions,
shows that the planning time is not significantly affected by this
patch (within the margin of error), particularly when compared to the
impact caused by partitionwise join.
Thanks to Tom Lane for the idea of leveraging exprs_known_equal() to
check if partition keys are known equal by ECs.
Author: Richard Guo, Tom Lane
Reviewed-by: Tom Lane, Ashutosh Bapat, Robert Haas
Discussion: https://postgr.es/m/CAN_9JTzo_2F5dKLqXVtDX5V6dwqB0Xk+ihstpKEt3a1LT6X78A@mail.gmail.com
In try_partitionwise_join, we aim to break down the join between two
partitioned relations into joins between matching partitions. To
achieve this, we iterate through each pair of partitions from the two
joining relations and create child-join relations for them. With
potentially thousands of partitions, the local objects allocated in
each iteration can accumulate significant memory usage. Therefore, we
opt to eagerly free these local objects at the end of each iteration.
In line with this approach, this patch frees the bitmap set that
represents the relids of child-join relations at the end of each
iteration. Additionally, it modifies build_child_join_rel() to reuse
the AppendRelInfo structures generated within each iteration.
Author: Ashutosh Bapat
Reviewed-by: David Christensen, Richard Guo
Discussion: https://postgr.es/m/CAExHW5s4EqY43oB=ne6B2=-xLgrs9ZGeTr1NXwkGFt2j-OmaQQ@mail.gmail.com
In the case of a parallel plan, when computing the number of tuples
processed per worker, we divide the total number of tuples by the
parallel_divisor obtained from get_parallel_divisor(), which accounts
for the leader's contribution in addition to the number of workers.
Accordingly, when estimating the number of tuples for gather (merge)
nodes, we should multiply the number of tuples per worker by the same
parallel_divisor to reverse the division. However, currently we use
parallel_workers rather than parallel_divisor for the multiplication.
This could result in an underestimation of the number of tuples for
gather (merge) nodes, especially when there are fewer than four
workers.
This patch fixes this issue by using the same parallel_divisor for the
multiplication. There is one ensuing plan change in the regression
tests, but it looks reasonable and does not compromise its original
purpose of testing parallel-aware hash join.
In passing, this patch removes an unnecessary assignment for path.rows
in create_gather_merge_path, and fixes an uninitialized-variable issue
in generate_useful_gather_paths.
No backpatch as this could result in plan changes.
Author: Anthonin Bonnefoy
Reviewed-by: Rafia Sabih, Richard Guo
Discussion: https://postgr.es/m/CAO6_Xqr9+51NxgO=XospEkUeAg-p=EjAWmtpdcZwjRgGKJ53iA@mail.gmail.com
Previously, the code charged disable_cost for CurrentOfExpr, and then
subtracted disable_cost from the cost of a TID path that used
CurrentOfExpr as the TID qual, effectively disabling all paths except
that one. Now, we instead suppress generation of the disabled paths
entirely, and generate only the one that the executor will actually
understand.
With this approach, we do not need to rely on disable_cost being
large enough to prevent the wrong path from being chosen, and we
save some CPU cycle by avoiding generating paths that we can't
actually use. In my opinion, the code is also easier to understand
like this.
Patch by me. Review by Heikki Linnakangas.
Discussion: http://postgr.es/m/591b3596-2ea0-4b8e-99c6-fad0ef2801f5@iki.fi
0452b461bc made get_eclass_for_sort_expr() always set
EquivalenceClass.ec_sortref if it's not done yet. This leads to an asymmetric
situation when whoever first looks for the EquivalenceClass sets the
ec_sortref. It is also counterintuitive that get_eclass_for_sort_expr()
performs modification of data structures.
This commit makes make_pathkeys_for_sortclauses_extended() responsible for
setting EquivalenceClass.ec_sortref. Now we set the
EquivalenceClass.ec_sortref's needed to explore alternative GROUP BY ordering
specifically during building pathkeys by the list of grouping clauses.
Discussion: https://postgr.es/m/17037754-f187-4138-8285-0e2bfebd0dea%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
Replace (expr op C1) OR (expr op C2) ... with expr op ANY(ARRAY[C1, C2, ...])
on the preliminary stage of optimization when we are still working with the
expression tree.
Here Cn is a n-th constant expression, 'expr' is non-constant expression, 'op'
is an operator which returns boolean result and has a commuter (for the case
of reverse order of constant and non-constant parts of the expression,
like 'Cn op expr').
Sometimes it can lead to not optimal plan. This is why there is a
or_to_any_transform_limit GUC. It specifies a threshold value of length of
arguments in an OR expression that triggers the OR-to-ANY transformation.
Generally, more groupable OR arguments mean that transformation will be more
likely to win than to lose.
Discussion: https://postgr.es/m/567ED6CA.2040504%40sigaev.ru
Author: Alena Rybakina <lena.ribackina@yandex.ru>
Author: Andrey Lepikhov <a.lepikhov@postgrespro.ru>
Reviewed-by: Peter Geoghegan <pg@bowt.ie>
Reviewed-by: Ranier Vilela <ranier.vf@gmail.com>
Reviewed-by: Alexander Korotkov <aekorotkov@gmail.com>
Reviewed-by: Robert Haas <robertmhaas@gmail.com>
Reviewed-by: Jian He <jian.universality@gmail.com>
66c0185a3 adjusted the UNION planner to request that union child queries
produce Paths correctly ordered to implement the UNION by way of
MergeAppend followed by Unique. The code there made a bad assumption
that if the root->parent_root->parse had setOperations set that the
query must be the child subquery of a set operation. That's not true
when it comes to planning a non-inlined CTE which is parented by a set
operation. This causes issues as the CTE's targetlist has no
requirement to match up to the SetOperationStmt's groupClauses
Fix this by adding a new parameter to both subquery_planner() and
grouping_planner() to explicitly pass the SetOperationStmt only when
planning set operation child subqueries.
Thank you to Tom Lane for helping to rationalize the decision on the
best function signature for subquery_planner().
Reported-by: Alexander Lakhin
Discussion: https://postgr.es/m/242fc7c6-a8aa-2daf-ac4c-0a231e2619c1@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
This teaches build_child_join_sjinfo() to create the dummy
SpecialJoinInfos (those created for inner joins) directly for a given
child join, skipping the unnecessary overhead of translating the
parent joinrel's SpecialJoinInfo.
To that end, this commit moves the code to initialize the dummy
SpecialJoinInfos to a new function named init_dummy_sjinfo() and
changes the few existing sites that have this code and
build_child_join_sjinfo() to call this new function.
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
When considering nestloop paths for individual partitions within
a partitionwise join, if the inner path is parameterized, it is
parameterized by the topmost parent of the outer rel, not the
corresponding outer rel itself. Therefore, we need to translate the
parameterization so that the inner path is parameterized by the
corresponding outer rel.
Up to now, we did this while generating join paths. However, that's
problematic because we must also translate some expressions that are
shared across all paths for a relation, such as restriction clauses
(kept in the RelOptInfo and/or IndexOptInfo) and TableSampleClauses
(kept in the RangeTblEntry). The existing code fails to translate
these at all, leading to wrong answers, odd failures such as
"variable not found in subplan target list", or executor crashes.
But we can't modify them during path generation, because that would
break things if we end up choosing some non-partitioned-join path.
So this patch postpones reparameterization of the inner path until
createplan.c, where it is safe to modify the referenced RangeTblEntry,
RelOptInfo or IndexOptInfo, because we have made a final choice of which
Path to use. We do still have to check during path generation that
the reparameterization will be possible. So we introduce a new
function path_is_reparameterizable_by_child() to detect that.
The duplication between path_is_reparameterizable_by_child() and
reparameterize_path_by_child() is a bit annoying, but there seems
no other good answer. A small benefit is that we can avoid building
useless reparameterized trees in cases where a non-partitioned join
is ultimately chosen. Also, reparameterize_path_by_child() can now
be allowed to scribble on the input paths, saving a few cycles.
This fix repairs the same problems previously addressed in the
back branches by commits 62f120203 et al.
Richard Guo, reviewed at various times by Ashutosh Bapat, Andrei
Lepikhov, Alena Rybakina, Robert Haas, and myself
Discussion: https://postgr.es/m/CAMbWs496+N=UAjOc=rcD3P7B6oJe4rZw08e_TZRUsWbPxZW3Tw@mail.gmail.com
This allows a RETURNING clause to be appended to a MERGE query, to
return values based on each row inserted, updated, or deleted. As with
plain INSERT, UPDATE, and DELETE commands, the returned values are
based on the new contents of the target table for INSERT and UPDATE
actions, and on its old contents for DELETE actions. Values from the
source relation may also be returned.
As with INSERT/UPDATE/DELETE, the output of MERGE ... RETURNING may be
used as the source relation for other operations such as WITH queries
and COPY commands.
Additionally, a special function merge_action() is provided, which
returns 'INSERT', 'UPDATE', or 'DELETE', depending on the action
executed for each row. The merge_action() function can be used
anywhere in the RETURNING list, including in arbitrary expressions and
subqueries, but it is an error to use it anywhere outside of a MERGE
query's RETURNING list.
Dean Rasheed, reviewed by Isaac Morland, Vik Fearing, Alvaro Herrera,
Gurjeet Singh, Jian He, Jeff Davis, Merlin Moncure, Peter Eisentraut,
and Wolfgang Walther.
Discussion: http://postgr.es/m/CAEZATCWePEGQR5LBn-vD6SfeLZafzEm2Qy_L_Oky2=qw2w3Pzg@mail.gmail.com
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
Since commit 599b33b94, this function assumed that every RTE_RELATION
RangeTblEntry would have an associated RelOptInfo. But that's not so:
we only build RelOptInfos for relations that are scanned by the query.
In particular the target of an INSERT won't have one, so that Vars
appearing in an INSERT ... RETURNING list will not have an associated
RelOptInfo. This apparently wasn't a problem before commit f7816aec2
taught examine_simple_variable() to drill down into CTEs containing
INSERT RETURNING, but it is now.
To fix, add a fallback code path that gets the userid to use directly
from the RTEPermissionInfo associated with the RTE. (Sadly, we must
have two code paths, because not every RTE has a RTEPermissionInfo
either.)
Per report from Alexander Lakhin. No back-patch, since the case is
apparently unreachable before f7816aec2.
Discussion: https://postgr.es/m/608a4886-6c60-0f9e-97d5-591256bd4150@gmail.com
It's at least theoretically possible to overflow int32 when adding up
column width estimates to make a row width estimate. (The bug example
isn't terribly convincing as a real use-case, but perhaps wide joins
would provide a more plausible route to trouble.) This'd lead to
assertion failures or silly planner behavior. To forestall it, make
the relevant functions compute their running sums in int64 arithmetic
and then clamp to int32 range at the end. We can reasonably assume
that MaxAllocSize is a hard limit on actual tuple width, so clamping
to that is simply a correction for dubious input values, and there's
no need to go as far as widening width variables to int64 everywhere.
Per bug #18247 from RekGRpth. There've been no reports of this issue
arising in practical cases, so I feel no need to back-patch.
Richard Guo and Tom Lane
Discussion: https://postgr.es/m/18247-11ac477f02954422@postgresql.org
The value was double in the original implementation of this logic.
Commit da08a6598 pulled it out into a subroutine, but carelessly
declared the parameter as int when it should have been double.
On most platforms, the only ill effect would be to clamp the value
to be not more than INT_MAX, which would seldom be exceeded and
probably wouldn't change the estimates too much anyway. Nonetheless,
it's wrong and can cause complaints from ubsan.
While here, improve the comments and parameter names.
This is an ABI change in a globally exposed subroutine, so
back-patching would create some risk of breaking extensions.
The value of the fix doesn't seem high enough to warrant taking
that risk, so fix in HEAD only.
Per report from Alexander Lakhin.
Discussion: https://postgr.es/m/f5e15fe1-202d-1936-f47c-f0c69a936b72@gmail.com
contain_mutable_functions and contain_volatile_functions give
reliable answers only after expression preprocessing (specifically
eval_const_expressions). Some places understand this, but some did
not get the memo --- which is not entirely their fault, because the
problem is documented only in places far away from those functions.
Introduce wrapper functions that allow doing the right thing easily,
and add commentary in hopes of preventing future mistakes from
copy-and-paste of code that's only conditionally safe.
Two actual bugs of this ilk are fixed here. We failed to preprocess
column GENERATED expressions before checking mutability, so that the
code could fail to detect the use of a volatile function
default-argument expression, or it could reject a polymorphic function
that is actually immutable on the datatype of interest. Likewise,
column DEFAULT expressions weren't preprocessed before determining if
it's safe to apply the attmissingval mechanism. A false negative
would just result in an unnecessary table rewrite, but a false
positive could allow the attmissingval mechanism to be used in a case
where it should not be, resulting in unexpected initial values in a
new column.
In passing, re-order the steps in ComputePartitionAttrs so that its
checks for invalid column references are done before applying
expression_planner, rather than after. The previous coding would
not complain if a partition expression contains a disallowed column
reference that gets optimized away by constant folding, which seems
to me to be a behavior we do not want.
Per bug #18097 from Jim Keener. Back-patch to all supported versions.
Discussion: https://postgr.es/m/18097-ebb179674f22932f@postgresql.org
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
The Self Join Elimination (SJE) feature removes an inner join of a plain table
to itself in the query tree if is proved that the join can be replaced with
a scan without impacting the query result. Self join and inner relation are
replaced with the outer in query, equivalence classes, and planner info
structures. Also, inner restrictlist moves to the outer one with removing
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 === selectivity estimations, and potentially
can improve total planner prediction for the query.
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 row as the outer one.
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 inner and outer clauses must have
an exact match.
The relation replacement procedure is not trivial and it is partly combined
with the one, used to remove useless left joins. Tests, covering this feature,
were added to join.sql. Some 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, Alexander Kuzmenkov
Reviewed-by: Tom Lane, Robert Haas, Andres Freund, Simon Riggs, Jonathan S. Katz
Reviewed-by: David Rowley, Thomas Munro, Konstantin Knizhnik, Heikki Linnakangas
Reviewed-by: Hywel Carver, Laurenz Albe, Ronan Dunklau, vignesh C, Zhihong Yu
Reviewed-by: Greg Stark, Jaime Casanova, Michał Kłeczek, Alena Rybakina
Reviewed-by: Alexander Korotkov
Going by c4a1933b4, b33ef397a and 05893712c (to name just a few), it seems
that maintaining debug_print_rel() is often forgotten. In the case of
c4a1933b4, it was several years before anyone noticed that a path type
was not handled by debug_print_rel(). (debug_print_rel() is only
compiled when building with OPTIMIZER_DEBUG).
After a quick survey on the pgsql-hackers mailing list, nobody came
forward to admit that they use OPTIMIZER_DEBUG. So to prevent any future
maintenance neglect, let's just remove debug_print_rel() and have
OPTIMIZER_DEBUG make use of pprint() instead (as suggested by Tom Lane).
If anyone wants to come forward to claim they make use of
OPTIMIZER_DEBUG in a way that they need debug_print_rel() then they have
around 10 months remaining in the v17 cycle where we could revert this.
If nobody comes forward in that time, then we can likely safely declare
debug_print_rel() as not worth keeping.
Discussion: https://postgr.es/m/CAApHDvoCdjo8Cu2zEZF4-AxWG-90S+pYXAnoDDa9J3xH-OrczQ@mail.gmail.com
This was disabled in commit 6f80a8d9c due to the lack of support for
handling of pseudoconstant quals assigned to replaced joins in
createplan.c. To re-allow it, this patch adds the support by 1)
modifying the ForeignPath and CustomPath structs so that if they
represent foreign and custom scans replacing a join with a scan, they
store the list of RestrictInfo nodes to apply to the join, as in
JoinPaths, and by 2) modifying create_scan_plan() in createplan.c so
that it uses that list in that case, instead of the baserestrictinfo
list, to get pseudoconstant quals assigned to the join, as mentioned in
the commit message for that commit.
Important item for the release notes: this is non-backwards-compatible
since it modifies the ForeignPath and CustomPath structs, as mentioned
above, and changes the argument lists for FDW helper functions
create_foreignscan_path(), create_foreign_join_path(), and
create_foreign_upper_path().
Richard Guo, with some additional changes by me, reviewed by Nishant
Sharma, Suraj Kharage, and Richard Guo.
Discussion: https://postgr.es/m/CADrsxdbcN1vejBaf8a%2BQhrZY5PXL-04mCd4GDu6qm6FigDZd6Q%40mail.gmail.com
Here we adjust the costs for WindowAggs so that they properly take into
account how much of their subnode they must read before outputting the
first row. Without this, we always assumed that the startup cost for the
WindowAgg was not much more expensive than the startup cost of its
subnode, however, that's going to be completely wrong in many cases. The
WindowAgg may have to read *all* of its subnode to output a single row
with certain window bound options.
Here we estimate how many rows we'll need to read from the WindowAgg's
subnode and proportionally add more of the subnode's run costs onto the
WindowAgg's startup costs according to how much of it we expect to have to
read in order to produce the first WindowAgg row.
The reason this is more important than we might have initially thought is
that we may end up making use of a path from the lower planner that works
well as a cheap startup plan when the query has a LIMIT clause, however,
the WindowAgg might mean we need to read far more rows than what the LIMIT
specifies.
No backpatch on this so as not to cause plan changes in released
versions.
Bug: #17862
Reported-by: Tim Palmer
Author: David Rowley
Reviewed-by: Andy Fan
Discussion: https://postgr.es/m/17862-1ab8f74b0f7b0611@postgresql.org
Discussion: https://postgr.es/m/CAApHDvrB0S5BMv+0-wTTqWFE-BJ0noWqTnDu9QQfjZ2VSpLv_g@mail.gmail.com
Commit e7cb7ee14, which introduced the infrastructure for FDWs and
custom scan providers to replace joins with scans, failed to add support
handling of pseudoconstant quals assigned to replaced joins in
createplan.c, leading to an incorrect plan without a gating Result node
when postgres_fdw replaced a join with such a qual.
To fix, we could add the support by 1) modifying the ForeignPath and
CustomPath structs to store the list of RestrictInfo nodes to apply to
the join, as in JoinPaths, if they represent foreign and custom scans
replacing a join with a scan, and by 2) modifying create_scan_plan() in
createplan.c to use that list in that case, instead of the
baserestrictinfo list, to get pseudoconstant quals assigned to the join;
but #1 would cause an ABI break. So fix by modifying the infrastructure
to just disallow replacing joins with such quals.
Back-patch to all supported branches.
Reported by Nishant Sharma. Patch by me, reviewed by Nishant Sharma and
Richard Guo.
Discussion: https://postgr.es/m/CADrsxdbcN1vejBaf8a%2BQhrZY5PXL-04mCd4GDu6qm6FigDZd6Q%40mail.gmail.com
If the plan itself is parallel-safe, and the initPlans are too,
there's no reason anymore to prevent the plan from being marked
parallel-safe. That restriction (dating to commit ab77a5a45) was
really a special case of the fact that we couldn't transmit subplans
to parallel workers at all. We fixed that in commit 5e6d8d2bb and
follow-ons, but this case never got addressed.
We still forbid attaching initPlans to a Gather node that's
inserted pursuant to debug_parallel_query = regress. That's because,
when we hide the Gather from EXPLAIN output, we'd hide the initPlans
too, causing cosmetic regression diffs. It seems inadvisable to
kluge EXPLAIN to the extent required to make the output look the
same, so just don't do it in that case.
Along the way, this also takes care of some sloppiness about updating
path costs to match when we move initplans from one place to another
during createplan.c and setrefs.c. Since all the planning decisions
are already made by that point, this is just cosmetic; but it seems
good to keep EXPLAIN output consistent with where the initplans are.
The diff in query_planner() might be worth remarking on. I found that
one because after fixing things to allow parallel-safe initplans, one
partition_prune test case changed plans (as shown in the patch) ---
but only when debug_parallel_query was active. The reason proved to
be that we only bothered to mark Result nodes as potentially
parallel-safe when debug_parallel_query is on. This neglects the fact
that parallel-safety may be of interest for a sub-query even though
the Result itself doesn't parallelize.
Discussion: https://postgr.es/m/1129530.1681317832@sss.pgh.pa.us
We are capable of optimizing MIN() and MAX() aggregates on indexed
columns into subqueries that exploit the index, rather than the normal
thing of scanning the whole table. When we do this, we replace the
Aggref node(s) with Params referencing subquery outputs. Such Params
really ought to be included in the per-plan-node extParam/allParam
sets computed by SS_finalize_plan. However, we've never done so
up to now because of an ancient implementation choice to perform
that substitution during set_plan_references, which runs after
SS_finalize_plan, so that SS_finalize_plan never sees these Params.
This seems like clearly a bug, yet there have been no field reports
of problems that could trace to it. This may be because the types
of Plan nodes that could contain Aggrefs do not have any of the
rescan optimizations that are controlled by extParam/allParam.
Nonetheless it seems certain to bite us someday, so let's fix it
in a self-contained patch that can be back-patched if we find a
case in which there's a live bug pre-v17.
The cleanest fix would be to perform a separate tree walk to do
these substitutions before SS_finalize_plan runs. That seems
unattractive, first because a whole-tree mutation pass is expensive,
and second because we lack infrastructure for visiting expression
subtrees in a Plan tree, so that we'd need a new function knowing
as much as SS_finalize_plan knows about that. I also considered
swapping the order of SS_finalize_plan and set_plan_references,
but that fell foul of various assumptions that seem tricky to fix.
So the approach adopted here is to teach SS_finalize_plan itself
to check for such Aggrefs. I refactored things a bit in setrefs.c
to avoid having three copies of the code that does that.
Given the lack of any currently-known bug, no test case here.
Discussion: https://postgr.es/m/2391880.1689025003@sss.pgh.pa.us
We've had multiple issues with the clause_is_computable_at logic that
I introduced in 2489d76c4: it's been known to accept more than one
clone of the same qual at the same plan node, and also to accept no
clones at all. It's looking impractical to get it 100% right on the
basis of the currently-stored information, so fix it by introducing a
new RestrictInfo field "incompatible_relids" that explicitly shows
which outer joins a given clone mustn't be pushed above.
In principle we could populate this field in every RestrictInfo, but
that would cost space and there doesn't presently seem to be a need
for it in general. Also, while deconstruct_distribute_oj_quals can
easily fill the field with the remaining members of the commutative
join set that it's considering, computing it in the general case
seems again pretty complicated. So for now, just fill it for
clone quals.
Along the way, fix a bug that may or may not be only latent:
equivclass.c was generating replacement clauses with is_pushed_down
and has_clone/is_clone markings that didn't match their
required_relids. This led me to conclude that leaving the clone flags
out of make_restrictinfo's purview wasn't such a great idea after all,
so add them.
Per report from Richard Guo.
Discussion: https://postgr.es/m/CAMbWs48EYi_9-pSd0ORes1kTmTeAjT4Q3gu49hJtYCbSn2JyeA@mail.gmail.com
Pass it the RestrictInfo under consideration, not just the
clause_relids. This should save some trivial amount of
code at the call sites, and it gives us more flexibility
about what clause_is_computable_at() does. There's no
actual functional change here, though.
Discussion: https://postgr.es/m/3564467.1684352557@sss.pgh.pa.us
After applying outer-join identity 3 in the forward direction,
it was possible for the planner to mistakenly apply a qual clause
from above the two outer joins at the now-lower join level.
This can give the wrong answer, since a value that would get nulled
by the now-upper join might not yet be null.
To fix, when we perform such a transformation, consider that the
now-lower join hasn't really completed the outer join it's nominally
responsible for and thus its relid set should not include that OJ's
relid (nor should its output Vars have that nullingrel bit set).
Instead we add those bits when the now-upper join is performed.
The existing rules for qual placement then suffice to prevent
higher qual clauses from dropping below the now-upper join.
There are a few complications from needing to consider transitive
closures in case multiple pushdowns have happened, but all in all
it's not a very complex patch.
This is all new logic (from 2489d76c4) so no need to back-patch.
The added test cases all have the same results as in v15.
Tom Lane and Richard Guo
Discussion: https://postgr.es/m/0b819232-4b50-f245-1c7d-c8c61bf41827@postgrespro.ru
It's possible, in admittedly-rather-contrived cases, for an eclass
to generate a derived "join" qual that constrains the post-outer-join
value(s) of some RHS variable(s) without mentioning the LHS at all.
While the mechanisms were set up to work for this, we fell foul of
the "get_common_eclass_indexes" filter installed by commit 3373c7155:
it could decide that such an eclass wasn't relevant to the join, so
that the required qual clause wouldn't get emitted there or anywhere
else.
To fix, apply get_common_eclass_indexes only at inner joins, where
its rule is still valid. At an outer join, fall back to examining all
eclasses that mention either input (or the OJ relid, though it should
be impossible for an eclass to mention that without mentioning either
input). Perhaps we can improve on that later, but the cost/benefit of
adding more complexity to skip some irrelevant eclasses is dubious.
To allow cheaply distinguishing outer from inner joins, pass the
ojrelid to generate_join_implied_equalities as a separate argument.
This also allows cleaning up some sloppiness that had crept into
the definition of its join_relids argument, and it allows accurate
calculation of nominal_join_relids for a child outer join. (The
latter oversight seems not to have been a live bug, but it certainly
could have caused problems in future.)
Also fix what might be a live bug in check_index_predicates: it was
being sloppy about what it passed to generate_join_implied_equalities.
Per report from Richard Guo.
Discussion: https://postgr.es/m/CAMbWs4-DsTBfOvXuw64GdFss2=M5cwtEhY=0DCS7t2gT7P6hSA@mail.gmail.com
force_parallel_mode is meant to be used to allow us to exercise the
parallel query infrastructure to ensure that it's working as we expect.
It seems some users think this GUC is for forcing the query planner into
picking a parallel plan regardless of the costs. A quick look at the
documentation would have made them realize that they were wrong, but the
GUC is likely too conveniently named which, evidently, seems to often
result in users expecting that it forces the planner into usefully
parallelizing queries.
Here we rename the GUC to something which casual users are less likely to
mistakenly think is what they need to make their query run more quickly.
For now, the old name can still be used. We'll revisit if the old name
mapping can be removed once the buildfarm configs are all updated.
Reviewed-by: John Naylor
Discussion: https://postgr.es/m/CAApHDvrsOi92_uA7PEaHZMH-S4Xv+MGhQWA+GrP8b1kjpS1HjQ@mail.gmail.com
EquivalenceClasses are now understood as applying within a "join
domain", which is a set of inner-joined relations (possibly underneath
an outer join). We no longer need to treat an EC from below an outer
join as a second-class citizen.
I have hopes of eventually being able to treat outer-join clauses via
EquivalenceClasses, by means of only applying deductions within the
EC's join domain. There are still problems in the way of that, though,
so for now the reconsider_outer_join_clause logic is still here.
I haven't been able to get rid of RestrictInfo.is_pushed_down either,
but I wonder if that could be recast using JoinDomains.
I had to hack one test case in postgres_fdw.sql to make it still test
what it was meant to, because postgres_fdw is inconsistent about
how it deals with quals containing non-shippable expressions; see
https://postgr.es/m/1691374.1671659838@sss.pgh.pa.us. That should
be improved, but I don't think it's within the scope of this patch
series.
Patch by me; thanks to Richard Guo for review.
Discussion: https://postgr.es/m/830269.1656693747@sss.pgh.pa.us
Remove RestrictInfo.nullable_relids, along with a good deal of
infrastructure that calculated it. One use-case for it was in
join_clause_is_movable_to, but we can now replace that usage with
a check to see if the clause's relids include any outer join
that can null the target relation. The other use-case was in
join_clause_is_movable_into, but that test can just be dropped
entirely now that the clause's relids include outer joins.
Furthermore, join_clause_is_movable_into should now be
accurate enough that it will accept anything returned by
generate_join_implied_equalities, so we can restore the Assert
that was diked out in commit 95f4e59c3.
Remove the outerjoin_delayed mechanism. We needed this before to
prevent quals from getting evaluated below outer joins that should
null some of their vars. Now that we consider varnullingrels while
placing quals, that's taken care of automatically, so throw the
whole thing away.
Teach remove_useless_result_rtes to also remove useless FromExprs.
Having done that, the delay_upper_joins flag serves no purpose any
more and we can remove it, largely reverting 11086f2f2.
Use constant TRUE for "dummy" clauses when throwing back outer joins.
This improves on a hack I introduced in commit 6a6522529. If we
have a left-join clause l.x = r.y, and a WHERE clause l.x = constant,
we generate r.y = constant and then don't really have a need for the
join clause. But we must throw the join clause back anyway after
marking it redundant, so that the join search heuristics won't think
this is a clauseless join and avoid it. That was a kluge introduced
under time pressure, and after looking at it I thought of a better
way: let's just introduce constant-TRUE "join clauses" instead,
and get rid of them at the end. This improves the generated plans for
such cases by not having to test a redundant join clause. We can also
get rid of the ugly hack used to mark such clauses as redundant for
selectivity estimation.
Patch by me; thanks to Richard Guo for review.
Discussion: https://postgr.es/m/830269.1656693747@sss.pgh.pa.us
Traditionally we used the same Var struct to represent the value
of a table column everywhere in parse and plan trees. This choice
predates our support for SQL outer joins, and it's really a pretty
bad idea with outer joins, because the Var's value can depend on
where it is in the tree: it might go to NULL above an outer join.
So expression nodes that are equal() per equalfuncs.c might not
represent the same value, which is a huge correctness hazard for
the planner.
To improve this, decorate Var nodes with a bitmapset showing
which outer joins (identified by RTE indexes) may have nulled
them at the point in the parse tree where the Var appears.
This allows us to trust that equal() Vars represent the same value.
A certain amount of klugery is still needed to cope with cases
where we re-order two outer joins, but it's possible to make it
work without sacrificing that core principle. PlaceHolderVars
receive similar decoration for the same reason.
In the planner, we include these outer join bitmapsets into the relids
that an expression is considered to depend on, and in consequence also
add outer-join relids to the relids of join RelOptInfos. This allows
us to correctly perceive whether an expression can be calculated above
or below a particular outer join.
This change affects FDWs that want to plan foreign joins. They *must*
follow suit when labeling foreign joins in order to match with the
core planner, but for many purposes (if postgres_fdw is any guide)
they'd prefer to consider only base relations within the join.
To support both requirements, redefine ForeignScan.fs_relids as
base+OJ relids, and add a new field fs_base_relids that's set up by
the core planner.
Large though it is, this commit just does the minimum necessary to
install the new mechanisms and get check-world passing again.
Follow-up patches will perform some cleanup. (The README additions
and comments mention some stuff that will appear in the follow-up.)
Patch by me; thanks to Richard Guo for review.
Discussion: https://postgr.es/m/830269.1656693747@sss.pgh.pa.us
Avoid explicitly grouping by columns that we know are redundant
for sorting, for example we need group by only one of x and y in
SELECT ... WHERE x = y GROUP BY x, y
This comes up more often than you might think, as shown by the
changes in the regression tests. It's nearly free to detect too,
since we are just piggybacking on the existing logic that detects
redundant pathkeys. (In some of the existing plans that change,
it's visible that a sort step preceding the grouping step already
didn't bother to sort by the redundant column, making the old plan
a bit silly-looking.)
To do this, build processed_groupClause and processed_distinctClause
lists that omit any provably-redundant sort items, and consult those
not the originals where relevant. This means that within the
planner, one should usually consult root->processed_groupClause or
root->processed_distinctClause if one wants to know which columns
are to be grouped on; but to check whether grouping or distinct-ing
is happening at all, check non-NIL-ness of parse->groupClause or
parse->distinctClause. This is comparable to longstanding rules
about handling the HAVING clause, so I don't think it'll be a huge
maintenance problem.
nodeAgg.c also needs minor mods, because it's now possible to generate
AGG_PLAIN and AGG_SORTED Agg nodes with zero grouping columns.
Patch by me; thanks to Richard Guo and David Rowley for review.
Discussion: https://postgr.es/m/185315.1672179489@sss.pgh.pa.us
We were identifying the updatable generated columns of inheritance
children by transposing the calculation made for their parent.
However, there's nothing that says a traditional-inheritance child
can't have generated columns that aren't there in its parent, or that
have different dependencies than are in the parent's expression.
(At present it seems that we don't enforce that for partitioning
either, which is likely wrong to some degree or other; but the case
clearly needs to be handled with traditional inheritance.)
Hence, drop the very-klugy-anyway "extraUpdatedCols" RTE field
in favor of identifying which generated columns depend on updated
columns during executor startup. In HEAD we can remove
extraUpdatedCols altogether; in back branches, it's still there but
always empty. Another difference between the HEAD and back-branch
versions of this patch is that in HEAD we can add the new bitmap field
to ResultRelInfo, but that would cause an ABI break in back branches.
Like 4b3e37993, add a List field at the end of struct EState instead.
Back-patch to v13. The bogus calculation is also being made in v12,
but it doesn't have the same visible effect because we don't use it
to decide which generated columns to recalculate; as a consequence of
which the patch doesn't apply easily. I think that there might still
be a demonstrable bug associated with trigger firing conditions, but
that's such a weird corner-case usage that I'm content to leave it
unfixed in v12.
Amit Langote and Tom Lane
Discussion: https://postgr.es/m/CA+HiwqFshLKNvQUd1DgwJ-7tsTp=dwv7KZqXC4j2wYBV1aCDUA@mail.gmail.com
Discussion: https://postgr.es/m/2793383.1672944799@sss.pgh.pa.us
1349d279 added query planner support to allow more efficient execution of
aggregate functions which have an ORDER BY or a DISTINCT clause. Prior to
that commit, the planner would only request that the lower planner produce
a plan with the order required for the GROUP BY clause and it would be
left up to nodeAgg.c to perform the final sort of records within each
group so that the aggregate transition functions were called in the
correct order. Now that the planner requests the lower planner produce a
plan with the GROUP BY and the ORDER BY / DISTINCT aggregates in mind,
there is the possibility that the planner chooses a plan which could be
less efficient than what would have been produced before 1349d279.
While developing 1349d279, I had in mind that Incremental Sort would help
us in cases where an index exists only on the GROUP BY column(s).
Incremental Sort would just replace the implicit tuplesorts which are
being performed in nodeAgg.c. However, because the planner has the
flexibility to instead choose a plan which just performs a full sort on
both the GROUP BY and ORDER BY / DISTINCT aggregate columns, there is
potential for the planner to make a bad choice. The costing for
Incremental Sort is not perfect as it assumes an even distribution of rows
to sort within each sort group.
Here we add an escape hatch in the form of the enable_presorted_aggregate
GUC. This will allow users to get the pre-PG16 behavior in cases where
they have no other means to convince the query planner to produce a plan
which only sorts on the GROUP BY column(s).
Discussion: https://postgr.es/m/CAApHDvr1Sm+g9hbv4REOVuvQKeDWXcKUAhmbK5K+dfun0s9CvA@mail.gmail.com
Currently, information about the permissions to be checked on relations
mentioned in a query is stored in their range table entries. So the
executor must scan the entire range table looking for relations that
need to have permissions checked. This can make the permission checking
part of the executor initialization needlessly expensive when many
inheritance children are present in the range range. While the
permissions need not be checked on the individual child relations, the
executor still must visit every range table entry to filter them out.
This commit moves the permission checking information out of the range
table entries into a new plan node called RTEPermissionInfo. Every
top-level (inheritance "root") RTE_RELATION entry in the range table
gets one and a list of those is maintained alongside the range table.
This new list is initialized by the parser when initializing the range
table. The rewriter can add more entries to it as rules/views are
expanded. Finally, the planner combines the lists of the individual
subqueries into one flat list that is passed to the executor for
checking.
To make it quick to find the RTEPermissionInfo entry belonging to a
given relation, RangeTblEntry gets a new Index field 'perminfoindex'
that stores the corresponding RTEPermissionInfo's index in the query's
list of the latter.
ExecutorCheckPerms_hook has gained another List * argument; the
signature is now:
typedef bool (*ExecutorCheckPerms_hook_type) (List *rangeTable,
List *rtePermInfos,
bool ereport_on_violation);
The first argument is no longer used by any in-core uses of the hook,
but we leave it in place because there may be other implementations that
do. Implementations should likely scan the rtePermInfos list to
determine which operations to allow or deny.
Author: Amit Langote <amitlangote09@gmail.com>
Discussion: https://postgr.es/m/CA+HiwqGjJDmUhDSfv-U2qhKJjt9ST7Xh9JXC_irsAQ1TAUsJYg@mail.gmail.com
This reverts commit db0d67db24 and
several follow-on fixes. The idea of making a cost-based choice
of the order of the sorting columns is not fundamentally unsound,
but it requires cost information and data statistics that we don't
really have. For example, relying on procost to distinguish the
relative costs of different sort comparators is pretty pointless
so long as most such comparator functions are labeled with cost 1.0.
Moreover, estimating the number of comparisons done by Quicksort
requires more than just an estimate of the number of distinct values
in the input: you also need some idea of the sizes of the larger
groups, if you want an estimate that's good to better than a factor of
three or so. That's data that's often unknown or not very reliable.
Worse, to arrive at estimates of the number of calls made to the
lower-order-column comparison functions, the code needs to make
estimates of the numbers of distinct values of multiple columns,
which are necessarily even less trustworthy than per-column stats.
Even if all the inputs are perfectly reliable, the cost algorithm
as-implemented cannot offer useful information about how to order
sorting columns beyond the point at which the average group size
is estimated to drop to 1.
Close inspection of the code added by db0d67db2 shows that there
are also multiple small bugs. These could have been fixed, but
there's not much point if we don't trust the estimates to be
accurate in-principle.
Finally, the changes in cost_sort's behavior made for very large
changes (often a factor of 2 or so) in the cost estimates for all
sorting operations, not only those for multi-column GROUP BY.
That naturally changes plan choices in many situations, and there's
precious little evidence to show that the changes are for the better.
Given the above doubts about whether the new estimates are really
trustworthy, it's hard to summon much confidence that these changes
are better on the average.
Since we're hard up against the release deadline for v15, let's
revert these changes for now. We can always try again later.
Note: in v15, I left T_PathKeyInfo in place in nodes.h even though
it's unreferenced. Removing it would be an ABI break, and it seems
a bit late in the release cycle for that.
Discussion: https://postgr.es/m/TYAPR01MB586665EB5FB2C3807E893941F5579@TYAPR01MB5866.jpnprd01.prod.outlook.com
Make sure that function declarations use names that exactly match the
corresponding names from function definitions in optimizer, parser,
utility, libpq, and "commands" code, as well as in remaining library
code. Do the same for all code related to frontend programs (with the
exception of pg_dump/pg_dumpall related code).
Like other recent commits that cleaned up function parameter names, this
commit was written with help from clang-tidy. Later commits will handle
ecpg and pg_dump/pg_dumpall.
Author: Peter Geoghegan <pg@bowt.ie>
Reviewed-By: David Rowley <dgrowleyml@gmail.com>
Discussion: https://postgr.es/m/CAH2-WznJt9CMM9KJTMjJh_zbL5hD9oX44qdJ4aqZtjFi-zA3Tg@mail.gmail.com
The present implementations of adjust_appendrel_attrs_multilevel and
its sibling adjust_child_relids_multilevel are very messy, because
they work by reconstructing the relids of the child's immediate
parent and then seeing if that's bms_equal to the relids of the
target parent. Aside from being quite inefficient, this will not
work with planned future changes to make joinrels' relid sets
contain outer-join relids in addition to baserels.
The whole thing can be solved at a stroke by adding explicit parent
and top_parent links to child RelOptInfos, and making these functions
work with RelOptInfo pointers instead of relids. Doing that is
simpler for most callers, too.
In my original version of this patch, I got rid of
RelOptInfo.top_parent_relids on the grounds that it was now redundant.
However, that adds a lot of code churn in places that otherwise would
not need changing, and arguably the extra indirection needed to fetch
top_parent->relids in those places costs something. So this version
leaves that field in place.
Discussion: https://postgr.es/m/553080.1657481916@sss.pgh.pa.us
Up to now, callers of find_placeholder_info() were required to pass
a flag indicating if it's OK to make a new PlaceHolderInfo. That'd
be fine if the callers had free choice, but they do not. Once we
begin deconstruct_jointree() it's no longer OK to make more PHIs;
while callers before that always want to create a PHI if it's not
there already. So there's no freedom of action, only the opportunity
to cause bugs by creating PHIs too late. Let's get rid of that in
favor of adding a state flag PlannerInfo.placeholdersFrozen, which
we can set at the point where it's no longer OK to make more PHIs.
This patch also simplifies a couple of call sites that were using
complicated logic to avoid calling find_placeholder_info() as much
as possible. Now that that lookup is O(1) thanks to the previous
commit, the extra bitmap manipulations are probably a net negative.
Discussion: https://postgr.es/m/1405792.1660677844@sss.pgh.pa.us
Commit fac1b470a thought we could check for set-returning functions
by testing only the top-level node in an expression tree. This is
wrong in itself, and to make matters worse it encouraged others
to make the same mistake, by exporting tlist.c's special-purpose
IS_SRF_CALL() as a widely-visible macro. I can't find any evidence
that anyone's taken the bait, but it was only a matter of time.
Use expression_returns_set() instead, and stuff the IS_SRF_CALL()
genie back in its bottle, this time with a warning label. I also
added a couple of cross-reference comments.
After a fair amount of fooling around, I've despaired of making
a robust test case that exposes the bug reliably, so no test case
here. (Note that the test case added by fac1b470a is itself
broken, in that it doesn't notice if you remove the code change.
The repro given by the bug submitter currently doesn't fail either
in v15 or HEAD, though I suspect that may indicate an unrelated bug.)
Per bug #17564 from Martijn van Oosterhout. Back-patch to v13,
as the faulty patch was.
Discussion: https://postgr.es/m/17564-c7472c2f90ef2da3@postgresql.org
ORDER BY / DISTINCT aggreagtes have, since implemented in Postgres, been
executed by always performing a sort in nodeAgg.c to sort the tuples in
the current group into the correct order before calling the transition
function on the sorted tuples. This was not great as often there might be
an index that could have provided pre-sorted input and allowed the
transition functions to be called as the rows come in, rather than having
to store them in a tuplestore in order to sort them once all the tuples
for the group have arrived.
Here we change the planner so it requests a path with a sort order which
supports the most amount of ORDER BY / DISTINCT aggregate functions and
add new code to the executor to allow it to support the processing of
ORDER BY / DISTINCT aggregates where the tuples are already sorted in the
correct order.
Since there can be many ORDER BY / DISTINCT aggregates in any given query
level, it's very possible that we can't find an order that suits all of
these aggregates. The sort order that the planner chooses is simply the
one that suits the most aggregate functions. We take the most strictly
sorted variation of each order and see how many aggregate functions can
use that, then we try again with the order of the remaining aggregates to
see if another order would suit more aggregate functions. For example:
SELECT agg(a ORDER BY a),agg2(a ORDER BY a,b) ...
would request the sort order to be {a, b} because {a} is a subset of the
sort order of {a,b}, but;
SELECT agg(a ORDER BY a),agg2(a ORDER BY c) ...
would just pick a plan ordered by {a} (we give precedence to aggregates
which are earlier in the targetlist).
SELECT agg(a ORDER BY a),agg2(a ORDER BY b),agg3(a ORDER BY b) ...
would choose to order by {b} since two aggregates suit that vs just one
that requires input ordered by {a}.
Author: David Rowley
Reviewed-by: Ronan Dunklau, James Coleman, Ranier Vilela, Richard Guo, Tom Lane
Discussion: https://postgr.es/m/CAApHDvpHzfo92%3DR4W0%2BxVua3BUYCKMckWAmo-2t_KiXN-wYH%3Dw%40mail.gmail.com
setrefs.c contains logic to discard no-op SubqueryScan nodes, that is,
ones that have no qual to check and copy the input targetlist unchanged.
(Formally it's not very nice to be applying such optimizations so late
in the planner, but there are practical reasons for it; mostly that we
can't unify relids between the subquery and the parent query until we
flatten the rangetable during setrefs.c.) This behavior falsifies our
previous cost estimates, since we would've charged cpu_tuple_cost per
row just to pass data through the node. Most of the time that's little
enough to not matter, but there are cases where this effect visibly
changes the plan compared to what you would've gotten with no
sub-select.
To improve the situation, make the callers of cost_subqueryscan tell
it whether they think the targetlist is trivial. cost_subqueryscan
already has the qual list, so it can check the other half of the
condition easily. It could make its own determination of tlist
triviality too, but doing so would be repetitive (for callers that
may call it several times) or unnecessarily expensive (for callers
that can determine this more cheaply than a general test would do).
This isn't a 100% solution, because createplan.c also does things
that can falsify any earlier estimate of whether the tlist is
trivial. However, it fixes nearly all cases in practice, if results
for the regression tests are anything to go by.
setrefs.c also contains logic to discard no-op Append and MergeAppend
nodes. We did have knowledge of that behavior at costing time, but
somebody failed to update it when a check on parallel-awareness was
added to the setrefs.c logic. Fix that while we're here.
These changes result in two minor changes in query plans shown in
our regression tests. Neither is relevant to the purposes of its
test case AFAICT.
Patch by me; thanks to Richard Guo for review.
Discussion: https://postgr.es/m/2581077.1651703520@sss.pgh.pa.us
Noticed while working in this area. This code was introduced in PG15,
which is still in beta, so backpatch to there for consistency.
Backpatch-through: 15
Several places in the planner tried to clamp a double value to fit
in a "long" by doing
(long) Min(x, (double) LONG_MAX);
This is subtly incorrect, because it casts LONG_MAX to double and
potentially back again. If long is 64 bits then the double value
is inexact, and the platform might round it up to LONG_MAX+1
resulting in an overflow and an undesirably negative output.
While it's not hard to rewrite the expression into a safe form,
let's put it into a common function to reduce the risk of someone
doing it wrong in future.
In principle this is a bug fix, but since the problem could only
manifest with group count estimates exceeding 2^63, it seems unlikely
that anyone has actually hit this or will do so anytime soon. We're
fixing it mainly to satisfy fuzzer-type tools. That being the case,
a HEAD-only fix seems sufficient.
Andrey Lepikhov
Discussion: https://postgr.es/m/ebbc2efb-7ef9-bf2f-1ada-d6ec48f70e58@postgrespro.ru
Up until now, we've had a policy of only marking certain variables
in the PostgreSQL header files with PGDLLIMPORT, but now we've
decided to mark them all. This means that extensions running on
Windows should no longer operate at a disadvantage as compared to
extensions running on Linux: if the variable is present in a header
file, it should be accessible.
Discussion: http://postgr.es/m/CA+TgmoYanc1_FSfimhgiWSqVyP5KKmh5NP2BWNwDhO8Pg2vGYQ@mail.gmail.com
Window functions such as row_number() always return a value higher than
the previously returned value for tuples in any given window partition.
Traditionally queries such as;
SELECT * FROM (
SELECT *, row_number() over (order by c) rn
FROM t
) t WHERE rn <= 10;
were executed fairly inefficiently. Neither the query planner nor the
executor knew that once rn made it to 11 that nothing further would match
the outer query's WHERE clause. It would blindly continue until all
tuples were exhausted from the subquery.
Here we implement means to make the above execute more efficiently.
This is done by way of adding a pg_proc.prosupport function to various of
the built-in window functions and adding supporting code to allow the
support function to inform the planner if the window function is
monotonically increasing, monotonically decreasing, both or neither. The
planner is then able to make use of that information and possibly allow
the executor to short-circuit execution by way of adding a "run condition"
to the WindowAgg to allow it to determine if some of its execution work
can be skipped.
This "run condition" is not like a normal filter. These run conditions
are only built using quals comparing values to monotonic window functions.
For monotonic increasing functions, quals making use of the btree
operators for <, <= and = can be used (assuming the window function column
is on the left). You can see here that once such a condition becomes false
that a monotonic increasing function could never make it subsequently true
again. For monotonically decreasing functions the >, >= and = btree
operators for the given type can be used for run conditions.
The best-case situation for this is when there is a single WindowAgg node
without a PARTITION BY clause. Here when the run condition becomes false
the WindowAgg node can simply return NULL. No more tuples will ever match
the run condition. It's a little more complex when there is a PARTITION
BY clause. In this case, we cannot return NULL as we must still process
other partitions. To speed this case up we pull tuples from the outer
plan to check if they're from the same partition and simply discard them
if they are. When we find a tuple belonging to another partition we start
processing as normal again until the run condition becomes false or we run
out of tuples to process.
When there are multiple WindowAgg nodes to evaluate then this complicates
the situation. For intermediate WindowAggs we must ensure we always
return all tuples to the calling node. Any filtering done could lead to
incorrect results in WindowAgg nodes above. For all intermediate nodes,
we can still save some work when the run condition becomes false. We've
no need to evaluate the WindowFuncs anymore. Other WindowAgg nodes cannot
reference the value of these and these tuples will not appear in the final
result anyway. The savings here are small in comparison to what can be
saved in the top-level WingowAgg, but still worthwhile.
Intermediate WindowAgg nodes never filter out tuples, but here we change
WindowAgg so that the top-level WindowAgg filters out tuples that don't
match the intermediate WindowAgg node's run condition. Such filters
appear in the "Filter" clause in EXPLAIN for the top-level WindowAgg node.
Here we add prosupport functions to allow the above to work for;
row_number(), rank(), dense_rank(), count(*) and count(expr). It appears
technically possible to do the same for min() and max(), however, it seems
unlikely to be useful enough, so that's not done here.
Bump catversion
Author: David Rowley
Reviewed-by: Andy Fan, Zhihong Yu
Discussion: https://postgr.es/m/CAApHDvqvp3At8++yF8ij06sdcoo1S_b2YoaT9D4Nf+MObzsrLQ@mail.gmail.com
In commit 27e1f1456, create_append_plan() only allowed the subplan
created from a given subpath to be executed asynchronously when it was
an async-capable ForeignPath. To extend coverage, this patch handles
cases when the given subpath includes some other Path types as well that
can be omitted in the plan processing, such as a ProjectionPath directly
atop an async-capable ForeignPath, allowing asynchronous execution in
partitioned-scan/partitioned-join queries with non-Var tlist expressions
and more UNION queries.
Andrey Lepikhov and Etsuro Fujita, reviewed by Alexander Pyhalov and
Zhihong Yu.
Discussion: https://postgr.es/m/659c37a8-3e71-0ff2-394c-f04428c76f08%40postgrespro.ru
postgres_fdw would push ORDER BY clauses to the remote side without
verifying that the sort operator is safe to ship. Moreover, it failed
to print a suitable USING clause if the sort operator isn't default
for the sort expression's type. The net result of this is that the
remote sort might not have anywhere near the semantics we expect,
which'd be disastrous for locally-performed merge joins in particular.
We addressed similar issues in the context of ORDER BY within an
aggregate function call in commit 7012b132d, but failed to notice
that query-level ORDER BY was broken. Thus, much of the necessary
logic already existed, but it requires refactoring to be usable
in both cases.
Back-patch to all supported branches. In HEAD only, remove the
core code's copy of find_em_expr_for_rel, which is no longer used
and really should never have been pushed into equivclass.c in the
first place.
Ronan Dunklau, per report from David Rowley;
reviews by David Rowley, Ranier Vilela, and myself
Discussion: https://postgr.es/m/CAApHDvr4OeC2DBVY--zVP83-K=bYrTD7F8SZDhN4g+pj2f2S-A@mail.gmail.com
When evaluating a query with a multi-column GROUP BY clause using sort,
the cost may be heavily dependent on the order in which the keys are
compared when building the groups. Grouping does not imply any ordering,
so we're allowed to compare the keys in arbitrary order, and a Hash Agg
leverages this. But for Group Agg, we simply compared keys in the order
as specified in the query. This commit explores alternative ordering of
the keys, trying to find a cheaper one.
In principle, we might generate grouping paths for all permutations of
the keys, and leave the rest to the optimizer. But that might get very
expensive, so we try to pick only a couple interesting orderings based
on both local and global information.
When planning the grouping path, we explore statistics (number of
distinct values, cost of the comparison function) for the keys and
reorder them to minimize comparison costs. Intuitively, it may be better
to perform more expensive comparisons (for complex data types etc.)
last, because maybe the cheaper comparisons will be enough. Similarly,
the higher the cardinality of a key, the lower the probability we’ll
need to compare more keys. The patch generates and costs various
orderings, picking the cheapest ones.
The ordering of group keys may interact with other parts of the query,
some of which may not be known while planning the grouping. E.g. 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 eliminate the sort entirely.
The patch generates orderings and picks those minimizing the comparison
cost (for various pathkeys), and then adds orderings that might be
useful for operations higher up in the plan (ORDER BY, etc.). Finally,
it always keeps the ordering specified in the query, on the assumption
the user might have additional insights.
This introduces a new GUC enable_group_by_reordering, so that the
optimization may be disabled if needed.
The original patch was proposed by Teodor Sigaev, and later improved and
reworked by Dmitry Dolgov. Reviews by a number of people, including me,
Andrey Lepikhov, Claudio Freire, Ibrar Ahmed and Zhihong Yu.
Author: Dmitry Dolgov, Teodor Sigaev, Tomas Vondra
Reviewed-by: Tomas Vondra, Andrey Lepikhov, Claudio Freire, Ibrar Ahmed, Zhihong Yu
Discussion: https://postgr.es/m/7c79e6a5-8597-74e8-0671-1c39d124c9d6%40sigaev.ru
Discussion: https://postgr.es/m/CA%2Bq6zcW_4o2NC0zutLkOJPsFt80megSpX_dVRo6GK9PC-Jx_Ag%40mail.gmail.com
MERGE performs actions that modify rows in the target table using a
source table or query. MERGE provides a single SQL statement that can
conditionally INSERT/UPDATE/DELETE rows -- a task that would otherwise
require multiple PL statements. For example,
MERGE INTO target AS t
USING source AS s
ON t.tid = s.sid
WHEN MATCHED AND t.balance > s.delta THEN
UPDATE SET balance = t.balance - s.delta
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED AND s.delta > 0 THEN
INSERT VALUES (s.sid, s.delta)
WHEN NOT MATCHED THEN
DO NOTHING;
MERGE works with regular tables, partitioned tables and inheritance
hierarchies, including column and row security enforcement, as well as
support for row and statement triggers and transition tables therein.
MERGE is optimized for OLTP and is parameterizable, though also useful
for large scale ETL/ELT. MERGE is not intended to be used in preference
to existing single SQL commands for INSERT, UPDATE or DELETE since there
is some overhead. MERGE can be used from PL/pgSQL.
MERGE does not support targetting updatable views or foreign tables, and
RETURNING clauses are not allowed either. These limitations are likely
fixable with sufficient effort. Rewrite rules are also not supported,
but it's not clear that we'd want to support them.
Author: Pavan Deolasee <pavan.deolasee@gmail.com>
Author: Álvaro Herrera <alvherre@alvh.no-ip.org>
Author: Amit Langote <amitlangote09@gmail.com>
Author: Simon Riggs <simon.riggs@enterprisedb.com>
Reviewed-by: Peter Eisentraut <peter.eisentraut@enterprisedb.com>
Reviewed-by: Andres Freund <andres@anarazel.de> (earlier versions)
Reviewed-by: Peter Geoghegan <pg@bowt.ie> (earlier versions)
Reviewed-by: Robert Haas <robertmhaas@gmail.com> (earlier versions)
Reviewed-by: Japin Li <japinli@hotmail.com>
Reviewed-by: Justin Pryzby <pryzby@telsasoft.com>
Reviewed-by: Tomas Vondra <tomas.vondra@enterprisedb.com>
Reviewed-by: Zhihong Yu <zyu@yugabyte.com>
Discussion: https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.com
Discussion: https://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
Discussion: https://postgr.es/m/20201231134736.GA25392@alvherre.pgsql
Up to now, the planner estimated the size of a recursive query's
worktable as 10 times the size of the non-recursive term. It's hard
to see how to do significantly better than that automatically, but
we can give users control over the multiplier to allow tuning for
specific use-cases. The default behavior remains the same.
Simon Riggs
Discussion: https://postgr.es/m/CANbhV-EuaLm4H3g0+BSTYHEGxJj3Kht0R+rJ8vT57Dejnh=_nA@mail.gmail.com
Standardize on xoroshiro128** as our basic PRNG algorithm, eliminating
a bunch of platform dependencies as well as fundamentally-obsolete PRNG
code. In addition, this API replacement will ease replacing the
algorithm again in future, should that become necessary.
xoroshiro128** is a few percent slower than the drand48 family,
but it can produce full-width 64-bit random values not only 48-bit,
and it should be much more trustworthy. It's likely to be noticeably
faster than the platform's random(), depending on which platform you
are thinking about; and we can have non-global state vectors easily,
unlike with random(). It is not cryptographically strong, but neither
are the functions it replaces.
Fabien Coelho, reviewed by Dean Rasheed, Aleksander Alekseev, and myself
Discussion: https://postgr.es/m/alpine.DEB.2.22.394.2105241211230.165418@pseudo
It's possible that a subplan below a Memoize node contains a parameter
from above the Memoize node. If this parameter changes then cache entries
may become out-dated due to the new parameter value.
Previously Memoize was mistakenly not aware of this. We fix this here by
flushing the cache whenever a parameter that's not part of the cache
key changes.
Bug: #17213
Reported by: Elvis Pranskevichus
Author: David Rowley
Discussion: https://postgr.es/m/17213-988ed34b225a2862@postgresql.org
Backpatch-through: 14, where Memoize was added
It's possible that a subplan below a Memoize node contains a parameter
from above the Memoize node. If this parameter changes then cache entries
may become out-dated due to the new parameter value.
Previously Memoize was mistakenly not aware of this. We fix this here by
flushing the cache whenever a parameter that's not part of the cache
key changes.
Bug: #17213
Reported by: Elvis Pranskevichus
Author: David Rowley
Discussion: https://postgr.es/m/17213-988ed34b225a2862@postgresql.org
Backpatch-through: 14, where Memoize was added
Memoize would always use the hash equality operator for the cache key
types to determine if the current set of parameters were the same as some
previously cached set. Certain types such as floating points where -0.0
and +0.0 differ in their binary representation but are classed as equal by
the hash equality operator may cause problems as unless the join uses the
same operator it's possible that whichever join operator is being used
would be able to distinguish the two values. In which case we may
accidentally return in the incorrect rows out of the cache.
To fix this here we add a binary mode to Memoize to allow it to the
current set of parameters to previously cached values by comparing
bit-by-bit rather than logically using the hash equality operator. This
binary mode is always used for LATERAL joins and it's used for normal
joins when any of the join operators are not hashable.
Reported-by: Tom Lane
Author: David Rowley
Discussion: https://postgr.es/m/3004308.1632952496@sss.pgh.pa.us
Backpatch-through: 14, where Memoize was added
"Result Cache" was never a great name for this node, but nobody managed
to come up with another name that anyone liked enough. That was until
David Johnston mentioned "Node Memoization", which Tom Lane revised to
just "Memoize". People seem to like "Memoize", so let's do the rename.
Reviewed-by: Justin Pryzby
Discussion: https://postgr.es/m/20210708165145.GG1176@momjian.us
Backpatch-through: 14, where Result Cache was introduced
Commit 2453ea142 redefined pg_proc.proargtypes to include the types of
OUT parameters, for procedures only. While that had some advantages
for implementing the SQL-spec behavior of DROP PROCEDURE, it was pretty
disastrous from a number of other perspectives. Notably, since the
primary key of pg_proc is name + proargtypes, this made it possible to
have multiple procedures with identical names + input arguments and
differing output argument types. That would make it impossible to call
any one of the procedures by writing just NULL (or "?", or any other
data-type-free notation) for the output argument(s). The change also
seems likely to cause grave confusion for client applications that
examine pg_proc and expect the traditional definition of proargtypes.
Hence, revert the definition of proargtypes to what it was, and
undo a number of complications that had been added to support that.
To support the SQL-spec behavior of DROP PROCEDURE, when there are
no argmode markers in the command's parameter list, we perform the
lookup both ways (that is, matching against both proargtypes and
proallargtypes), succeeding if we get just one unique match.
In principle this could result in ambiguous-function failures
that would not happen when using only one of the two rules.
However, overloading of procedure names is thought to be a pretty
rare usage, so this shouldn't cause many problems in practice.
Postgres-specific code such as pg_dump can defend against any
possibility of such failures by being careful to specify argmodes
for all procedure arguments.
This also fixes a few other bugs in the area of CALL statements
with named parameters, and improves the documentation a little.
catversion bump forced because the representation of procedures
with OUT arguments changes.
Discussion: https://postgr.es/m/3742981.1621533210@sss.pgh.pa.us
It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE
list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present.
If it happens, the ON CONFLICT UPDATE code path would end up storing
tuples that include the values of the extra resjunk columns. That's
fairly harmless in the short run, but if new columns are added to
the table then the values would become accessible, possibly leading
to malfunctions if they don't match the datatypes of the new columns.
This had escaped notice through a confluence of missing sanity checks,
including
* There's no cross-check that a tuple presented to heap_insert or
heap_update matches the table rowtype. While it's difficult to
check that fully at reasonable cost, we can easily add assertions
that there aren't too many columns.
* The output-column-assignment cases in execExprInterp.c lacked
any sanity checks on the output column numbers, which seems like
an oversight considering there are plenty of assertion checks on
input column numbers. Add assertions there too.
* We failed to apply nodeModifyTable's ExecCheckPlanOutput() to
the ON CONFLICT UPDATE tlist. That wouldn't have caught this
specific error, since that function is chartered to ignore resjunk
columns; but it sure seems like a bad omission now that we've seen
this bug.
In HEAD, the right way to fix this is to make the processing of
ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists
now do, that is don't add "SET x = x" entries, and use
ExecBuildUpdateProjection to evaluate the tlist and combine it with
old values of the not-set columns. This adds a little complication
to ExecBuildUpdateProjection, but allows removal of a comparable
amount of now-dead code from the planner.
In the back branches, the most expedient solution seems to be to
(a) use an output slot for the ON CONFLICT UPDATE projection that
actually matches the target table, and then (b) invent a variant of
ExecBuildProjectionInfo that can be told to not store values resulting
from resjunk columns, so it doesn't try to store into nonexistent
columns of the output slot. (We can't simply ignore the resjunk columns
altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.)
This works back to v10. In 9.6, projections work much differently and
we can't cheaply give them such an option. The 9.6 version of this
patch works by inserting a JunkFilter when it's necessary to get rid
of resjunk columns.
In addition, v11 and up have the reverse problem when trying to
perform ON CONFLICT UPDATE on a partitioned table. Through a
further oversight, adjust_partition_tlist() discarded resjunk columns
when re-ordering the ON CONFLICT UPDATE tlist to match a partition.
This accidentally prevented the storing-bogus-tuples problem, but
at the cost that MULTIEXPR_SUBLINK cases didn't work, typically
crashing if more than one row has to be updated. Fix by preserving
resjunk columns in that routine. (I failed to resist the temptation
to add more assertions there too, and to do some minor code
beautification.)
Per report from Andres Freund. Back-patch to all supported branches.
Security: CVE-2021-32028
I didn't particularly like this function name, as it fails to
express what's going on. Also, returning the sort expression
alone isn't too helpful --- typically, a caller would also
need some other fields of the EquivalenceMember. But the
sole caller really only needs a bool result, so let's make
it "bool relation_can_be_sorted_early()".
Discussion: https://postgr.es/m/91f3ec99-85a4-fa55-ea74-33f85a5c651f@swarm64.com
An oversight introduced by the incremental-sort patches caused
"could not find pathkey item to sort" errors in some situations
where a sort key involves an aggregate or window function.
The basic problem here is that find_em_expr_usable_for_sorting_rel
isn't properly modeling what prepare_sort_from_pathkeys will do
later. Rather than hoping we can keep those functions in sync,
let's refactor so that they actually share the code for
identifying a suitable sort expression.
With this refactoring, tlist.c's tlist_member_ignore_relabel
is unused. I removed it in HEAD but left it in place in v13,
in case any extensions are using it.
Per report from Luc Vlaming. Back-patch to v13 where the
problem arose.
James Coleman and Tom Lane
Discussion: https://postgr.es/m/91f3ec99-85a4-fa55-ea74-33f85a5c651f@swarm64.com
ScalarArrayOpExprs with "useOr=true" and a set of Consts on the righthand
side have traditionally been evaluated by using a linear search over the
array. When these arrays contain large numbers of elements then this
linear search could become a significant part of execution time.
Here we add a new method of evaluating ScalarArrayOpExpr expressions to
allow them to be evaluated by first building a hash table containing each
element, then on subsequent evaluations, we just probe that hash table to
determine if there is a match.
The planner is in charge of determining when this optimization is possible
and it enables it by setting hashfuncid in the ScalarArrayOpExpr. The
executor will only perform the hash table evaluation when the hashfuncid
is set.
This means that not all cases are optimized. For example CHECK constraints
containing an IN clause won't go through the planner, so won't get the
hashfuncid set. We could maybe do something about that at some later
date. The reason we're not doing it now is from fear that we may slow
down cases where the expression is evaluated only once. Those cases can
be common, for example, a single row INSERT to a table with a CHECK
constraint containing an IN clause.
In the planner, we enable this when there are suitable hash functions for
the ScalarArrayOpExpr's operator and only when there is at least
MIN_ARRAY_SIZE_FOR_HASHED_SAOP elements in the array. The threshold is
currently set to 9.
Author: James Coleman, David Rowley
Reviewed-by: David Rowley, Tomas Vondra, Heikki Linnakangas
Discussion: https://postgr.es/m/CAAaqYe8x62+=wn0zvNKCj55tPpg-JBHzhZFFc6ANovdqFw7-dA@mail.gmail.com
Here we add a new executor node type named "Result Cache". The planner
can include this node type in the plan to have the executor cache the
results from the inner side of parameterized nested loop joins. This
allows caching of tuples for sets of parameters so that in the event that
the node sees the same parameter values again, it can just return the
cached tuples instead of rescanning the inner side of the join all over
again. Internally, result cache uses a hash table in order to quickly
find tuples that have been previously cached.
For certain data sets, this can significantly improve the performance of
joins. The best cases for using this new node type are for join problems
where a large portion of the tuples from the inner side of the join have
no join partner on the outer side of the join. In such cases, hash join
would have to hash values that are never looked up, thus bloating the hash
table and possibly causing it to multi-batch. Merge joins would have to
skip over all of the unmatched rows. If we use a nested loop join with a
result cache, then we only cache tuples that have at least one join
partner on the outer side of the join. The benefits of using a
parameterized nested loop with a result cache increase when there are
fewer distinct values being looked up and the number of lookups of each
value is large. Also, hash probes to lookup the cache can be much faster
than the hash probe in a hash join as it's common that the result cache's
hash table is much smaller than the hash join's due to result cache only
caching useful tuples rather than all tuples from the inner side of the
join. This variation in hash probe performance is more significant when
the hash join's hash table no longer fits into the CPU's L3 cache, but the
result cache's hash table does. The apparent "random" access of hash
buckets with each hash probe can cause a poor L3 cache hit ratio for large
hash tables. Smaller hash tables generally perform better.
The hash table used for the cache limits itself to not exceeding work_mem
* hash_mem_multiplier in size. We maintain a dlist of keys for this cache
and when we're adding new tuples and realize we've exceeded the memory
budget, we evict cache entries starting with the least recently used ones
until we have enough memory to add the new tuples to the cache.
For parameterized nested loop joins, we now consider using one of these
result cache nodes in between the nested loop node and its inner node. We
determine when this might be useful based on cost, which is primarily
driven off of what the expected cache hit ratio will be. Estimating the
cache hit ratio relies on having good distinct estimates on the nested
loop's parameters.
For now, the planner will only consider using a result cache for
parameterized nested loop joins. This works for both normal joins and
also for LATERAL type joins to subqueries. It is possible to use this new
node for other uses in the future. For example, to cache results from
correlated subqueries. However, that's not done here due to some
difficulties obtaining a distinct estimation on the outer plan to
calculate the estimated cache hit ratio. Currently we plan the inner plan
before planning the outer plan so there is no good way to know if a result
cache would be useful or not since we can't estimate the number of times
the subplan will be called until the outer plan is generated.
The functionality being added here is newly introducing a dependency on
the return value of estimate_num_groups() during the join search.
Previously, during the join search, we only ever needed to perform
selectivity estimations. With this commit, we need to use
estimate_num_groups() in order to estimate what the hit ratio on the
result cache will be. In simple terms, if we expect 10 distinct values
and we expect 1000 outer rows, then we'll estimate the hit ratio to be
99%. Since cache hits are very cheap compared to scanning the underlying
nodes on the inner side of the nested loop join, then this will
significantly reduce the planner's cost for the join. However, it's
fairly easy to see here that things will go bad when estimate_num_groups()
incorrectly returns a value that's significantly lower than the actual
number of distinct values. If this happens then that may cause us to make
use of a nested loop join with a result cache instead of some other join
type, such as a merge or hash join. Our distinct estimations have been
known to be a source of trouble in the past, so the extra reliance on them
here could cause the planner to choose slower plans than it did previous
to having this feature. Distinct estimations are also fairly hard to
estimate accurately when several tables have been joined already or when a
WHERE clause filters out a set of values that are correlated to the
expressions we're estimating the number of distinct value for.
For now, the costing we perform during query planning for result caches
does put quite a bit of faith in the distinct estimations being accurate.
When these are accurate then we should generally see faster execution
times for plans containing a result cache. However, in the real world, we
may find that we need to either change the costings to put less trust in
the distinct estimations being accurate or perhaps even disable this
feature by default. There's always an element of risk when we teach the
query planner to do new tricks that it decides to use that new trick at
the wrong time and causes a regression. Users may opt to get the old
behavior by turning the feature off using the enable_resultcache GUC.
Currently, this is enabled by default. It remains to be seen if we'll
maintain that setting for the release.
Additionally, the name "Result Cache" is the best name I could think of
for this new node at the time I started writing the patch. Nobody seems
to strongly dislike the name. A few people did suggest other names but no
other name seemed to dominate in the brief discussion that there was about
names. Let's allow the beta period to see if the current name pleases
enough people. If there's some consensus on a better name, then we can
change it before the release. Please see the 2nd discussion link below
for the discussion on the "Result Cache" name.
Author: David Rowley
Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu, Hou Zhijie
Tested-By: Konstantin Knizhnik
Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com
This removes "Add Result Cache executor node". It seems that something
weird is going on with the tracking of cache hits and misses as
highlighted by many buildfarm animals. It's not yet clear what the
problem is as other parts of the plan indicate that the cache did work
correctly, it's just the hits and misses that were being reported as 0.
This is especially a bad time to have the buildfarm so broken, so
reverting before too many more animals go red.
Discussion: https://postgr.es/m/CAApHDvq_hydhfovm4=izgWs+C5HqEeRScjMbOgbpC-jRAeK3Yw@mail.gmail.com
Here we add a new executor node type named "Result Cache". The planner
can include this node type in the plan to have the executor cache the
results from the inner side of parameterized nested loop joins. This
allows caching of tuples for sets of parameters so that in the event that
the node sees the same parameter values again, it can just return the
cached tuples instead of rescanning the inner side of the join all over
again. Internally, result cache uses a hash table in order to quickly
find tuples that have been previously cached.
For certain data sets, this can significantly improve the performance of
joins. The best cases for using this new node type are for join problems
where a large portion of the tuples from the inner side of the join have
no join partner on the outer side of the join. In such cases, hash join
would have to hash values that are never looked up, thus bloating the hash
table and possibly causing it to multi-batch. Merge joins would have to
skip over all of the unmatched rows. If we use a nested loop join with a
result cache, then we only cache tuples that have at least one join
partner on the outer side of the join. The benefits of using a
parameterized nested loop with a result cache increase when there are
fewer distinct values being looked up and the number of lookups of each
value is large. Also, hash probes to lookup the cache can be much faster
than the hash probe in a hash join as it's common that the result cache's
hash table is much smaller than the hash join's due to result cache only
caching useful tuples rather than all tuples from the inner side of the
join. This variation in hash probe performance is more significant when
the hash join's hash table no longer fits into the CPU's L3 cache, but the
result cache's hash table does. The apparent "random" access of hash
buckets with each hash probe can cause a poor L3 cache hit ratio for large
hash tables. Smaller hash tables generally perform better.
The hash table used for the cache limits itself to not exceeding work_mem
* hash_mem_multiplier in size. We maintain a dlist of keys for this cache
and when we're adding new tuples and realize we've exceeded the memory
budget, we evict cache entries starting with the least recently used ones
until we have enough memory to add the new tuples to the cache.
For parameterized nested loop joins, we now consider using one of these
result cache nodes in between the nested loop node and its inner node. We
determine when this might be useful based on cost, which is primarily
driven off of what the expected cache hit ratio will be. Estimating the
cache hit ratio relies on having good distinct estimates on the nested
loop's parameters.
For now, the planner will only consider using a result cache for
parameterized nested loop joins. This works for both normal joins and
also for LATERAL type joins to subqueries. It is possible to use this new
node for other uses in the future. For example, to cache results from
correlated subqueries. However, that's not done here due to some
difficulties obtaining a distinct estimation on the outer plan to
calculate the estimated cache hit ratio. Currently we plan the inner plan
before planning the outer plan so there is no good way to know if a result
cache would be useful or not since we can't estimate the number of times
the subplan will be called until the outer plan is generated.
The functionality being added here is newly introducing a dependency on
the return value of estimate_num_groups() during the join search.
Previously, during the join search, we only ever needed to perform
selectivity estimations. With this commit, we need to use
estimate_num_groups() in order to estimate what the hit ratio on the
result cache will be. In simple terms, if we expect 10 distinct values
and we expect 1000 outer rows, then we'll estimate the hit ratio to be
99%. Since cache hits are very cheap compared to scanning the underlying
nodes on the inner side of the nested loop join, then this will
significantly reduce the planner's cost for the join. However, it's
fairly easy to see here that things will go bad when estimate_num_groups()
incorrectly returns a value that's significantly lower than the actual
number of distinct values. If this happens then that may cause us to make
use of a nested loop join with a result cache instead of some other join
type, such as a merge or hash join. Our distinct estimations have been
known to be a source of trouble in the past, so the extra reliance on them
here could cause the planner to choose slower plans than it did previous
to having this feature. Distinct estimations are also fairly hard to
estimate accurately when several tables have been joined already or when a
WHERE clause filters out a set of values that are correlated to the
expressions we're estimating the number of distinct value for.
For now, the costing we perform during query planning for result caches
does put quite a bit of faith in the distinct estimations being accurate.
When these are accurate then we should generally see faster execution
times for plans containing a result cache. However, in the real world, we
may find that we need to either change the costings to put less trust in
the distinct estimations being accurate or perhaps even disable this
feature by default. There's always an element of risk when we teach the
query planner to do new tricks that it decides to use that new trick at
the wrong time and causes a regression. Users may opt to get the old
behavior by turning the feature off using the enable_resultcache GUC.
Currently, this is enabled by default. It remains to be seen if we'll
maintain that setting for the release.
Additionally, the name "Result Cache" is the best name I could think of
for this new node at the time I started writing the patch. Nobody seems
to strongly dislike the name. A few people did suggest other names but no
other name seemed to dominate in the brief discussion that there was about
names. Let's allow the beta period to see if the current name pleases
enough people. If there's some consensus on a better name, then we can
change it before the release. Please see the 2nd discussion link below
for the discussion on the "Result Cache" name.
Author: David Rowley
Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu
Tested-By: Konstantin Knizhnik
Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com
This patch makes two closely related sets of changes:
1. For UPDATE, the subplan of the ModifyTable node now only delivers
the new values of the changed columns (i.e., the expressions computed
in the query's SET clause) plus row identity information such as CTID.
ModifyTable must re-fetch the original tuple to merge in the old
values of any unchanged columns. The core advantage of this is that
the changed columns are uniform across all tables of an inherited or
partitioned target relation, whereas the other columns might not be.
A secondary advantage, when the UPDATE involves joins, is that less
data needs to pass through the plan tree. The disadvantage of course
is an extra fetch of each tuple to be updated. However, that seems to
be very nearly free in context; even worst-case tests don't show it to
add more than a couple percent to the total query cost. At some point
it might be interesting to combine the re-fetch with the tuple access
that ModifyTable must do anyway to mark the old tuple dead; but that
would require a good deal of refactoring and it seems it wouldn't buy
all that much, so this patch doesn't attempt it.
2. For inherited UPDATE/DELETE, instead of generating a separate
subplan for each target relation, we now generate a single subplan
that is just exactly like a SELECT's plan, then stick ModifyTable
on top of that. To let ModifyTable know which target relation a
given incoming row refers to, a tableoid junk column is added to
the row identity information. This gets rid of the horrid hack
that was inheritance_planner(), eliminating O(N^2) planning cost
and memory consumption in cases where there were many unprunable
target relations.
Point 2 of course requires point 1, so that there is a uniform
definition of the non-junk columns to be returned by the subplan.
We can't insist on uniform definition of the row identity junk
columns however, if we want to keep the ability to have both
plain and foreign tables in a partitioning hierarchy. Since
it wouldn't scale very far to have every child table have its
own row identity column, this patch includes provisions to merge
similar row identity columns into one column of the subplan result.
In particular, we can merge the whole-row Vars typically used as
row identity by FDWs into one column by pretending they are type
RECORD. (It's still okay for the actual composite Datums to be
labeled with the table's rowtype OID, though.)
There is more that can be done to file down residual inefficiencies
in this patch, but it seems to be committable now.
FDW authors should note several API changes:
* The argument list for AddForeignUpdateTargets() has changed, and so
has the method it must use for adding junk columns to the query. Call
add_row_identity_var() instead of manipulating the parse tree directly.
You might want to reconsider exactly what you're adding, too.
* PlanDirectModify() must now work a little harder to find the
ForeignScan plan node; if the foreign table is part of a partitioning
hierarchy then the ForeignScan might not be the direct child of
ModifyTable. See postgres_fdw for sample code.
* To check whether a relation is a target relation, it's no
longer sufficient to compare its relid to root->parse->resultRelation.
Instead, check it against all_result_relids or leaf_result_relids,
as appropriate.
Amit Langote and Tom Lane
Discussion: https://postgr.es/m/CA+HiwqHpHdqdDn48yCEhynnniahH78rwcrv1rEX65-fsZGBOLQ@mail.gmail.com
This implements asynchronous execution, which runs multiple parts of a
non-parallel-aware Append concurrently rather than serially to improve
performance when possible. Currently, the only node type that can be
run concurrently is a ForeignScan that is an immediate child of such an
Append. In the case where such ForeignScans access data on different
remote servers, this would run those ForeignScans concurrently, and
overlap the remote operations to be performed simultaneously, so it'll
improve the performance especially when the operations involve
time-consuming ones such as remote join and remote aggregation.
We may extend this to other node types such as joins or aggregates over
ForeignScans in the future.
This also adds the support for postgres_fdw, which is enabled by the
table-level/server-level option "async_capable". The default is false.
Robert Haas, Kyotaro Horiguchi, Thomas Munro, and myself. This commit
is mostly based on the patch proposed by Robert Haas, but also uses
stuff from the patch proposed by Kyotaro Horiguchi and from the patch
proposed by Thomas Munro. Reviewed by Kyotaro Horiguchi, Konstantin
Knizhnik, Andrey Lepikhov, Movead Li, Thomas Munro, Justin Pryzby, and
others.
Discussion: https://postgr.es/m/CA%2BTgmoaXQEt4tZ03FtQhnzeDEMzBck%2BLrni0UWHVVgOTnA6C1w%40mail.gmail.com
Discussion: https://postgr.es/m/CA%2BhUKGLBRyu0rHrDCMC4%3DRn3252gogyp1SjOgG8SEKKZv%3DFwfQ%40mail.gmail.com
Discussion: https://postgr.es/m/20200228.170650.667613673625155850.horikyota.ntt%40gmail.com
To allow inserts in parallel-mode this feature has to ensure that all the
constraints, triggers, etc. are parallel-safe for the partition hierarchy
which is costly and we need to find a better way to do that. Additionally,
we could have used existing cached information in some cases like indexes,
domains, etc. to determine the parallel-safety.
List of commits reverted, in reverse chronological order:
ed62d3737c Doc: Update description for parallel insert reloption.
c8f78b6161 Add a new GUC and a reloption to enable inserts in parallel-mode.
c5be48f092 Improve FK trigger parallel-safety check added by 05c8482f7f.
e2cda3c20a Fix use of relcache TriggerDesc field introduced by commit 05c8482f7f.
e4e87a32cc Fix valgrind issue in commit 05c8482f7f.
05c8482f7f Enable parallel SELECT for "INSERT INTO ... SELECT ...".
Discussion: https://postgr.es/m/E1lMiB9-0001c3-SY@gemulon.postgresql.org
Commit 05c8482f7f added the implementation of parallel SELECT for
"INSERT INTO ... SELECT ..." which may incur non-negligible overhead in
the additional parallel-safety checks that it performs, even when, in the
end, those checks determine that parallelism can't be used. This is
normally only ever a problem in the case of when the target table has a
large number of partitions.
A new GUC option "enable_parallel_insert" is added, to allow insert in
parallel-mode. The default is on.
In addition to the GUC option, the user may want a mechanism to allow
inserts in parallel-mode with finer granularity at table level. The new
table option "parallel_insert_enabled" allows this. The default is true.
Author: "Hou, Zhijie"
Reviewed-by: Greg Nancarrow, Amit Langote, Takayuki Tsunakawa, Amit Kapila
Discussion: https://postgr.es/m/CAA4eK1K-cW7svLC2D7DHoGHxdAdg3P37BLgebqBOC2ZLc9a6QQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAJcOf-cXnB5cnMKqWEp2E2z7Mvcd04iLVmV=qpFJrR3AcrTS3g@mail.gmail.com
Parallel SELECT can't be utilized for INSERT in the following cases:
- INSERT statement uses the ON CONFLICT DO UPDATE clause
- Target table has a parallel-unsafe: trigger, index expression or
predicate, column default expression or check constraint
- Target table has a parallel-unsafe domain constraint on any column
- Target table is a partitioned table with a parallel-unsafe partition key
expression or support function
The planner is updated to perform additional parallel-safety checks for
the cases listed above, for determining whether it is safe to run INSERT
in parallel-mode with an underlying parallel SELECT. The planner will
consider using parallel SELECT for "INSERT INTO ... SELECT ...", provided
nothing unsafe is found from the additional parallel-safety checks, or
from the existing parallel-safety checks for SELECT.
While checking parallel-safety, we need to check it for all the partitions
on the table which can be costly especially when we decide not to use a
parallel plan. So, in a separate patch, we will introduce a GUC and or a
reloption to enable/disable parallelism for Insert statements.
Prior to entering parallel-mode for the execution of INSERT with parallel
SELECT, a TransactionId is acquired and assigned to the current
transaction state. This is necessary to prevent the INSERT from attempting
to assign the TransactionId whilst in parallel-mode, which is not allowed.
This approach has a disadvantage in that if the underlying SELECT does not
return any rows, then the TransactionId is not used, however that
shouldn't happen in practice in many cases.
Author: Greg Nancarrow, Amit Langote, Amit Kapila
Reviewed-by: Amit Langote, Hou Zhijie, Takayuki Tsunakawa, Antonin Houska, Bharath Rupireddy, Dilip Kumar, Vignesh C, Zhihong Yu, Amit Kapila
Tested-by: Tang, Haiying
Discussion: https://postgr.es/m/CAJcOf-cXnB5cnMKqWEp2E2z7Mvcd04iLVmV=qpFJrR3AcrTS3g@mail.gmail.com
Discussion: https://postgr.es/m/CAJcOf-fAdj=nDKMsRhQzndm-O13NY4dL6xGcEvdX5Xvbbi0V7g@mail.gmail.com
This adds a new executor node named TID Range Scan. The query planner
will generate paths for TID Range scans when quals are discovered on base
relations which search for ranges on the table's ctid column. These
ranges may be open at either end. For example, WHERE ctid >= '(10,0)';
will return all tuples on page 10 and over.
To support this, two new optional callback functions have been added to
table AM. scan_set_tidrange is used to set the scan range to just the
given range of TIDs. scan_getnextslot_tidrange fetches the next tuple
in the given range.
For AMs were scanning ranges of TIDs would not make sense, these functions
can be set to NULL in the TableAmRoutine. The query planner won't
generate TID Range Scan Paths in that case.
Author: Edmund Horner, David Rowley
Reviewed-by: David Rowley, Tomas Vondra, Tom Lane, Andres Freund, Zhihong Yu
Discussion: https://postgr.es/m/CAMyN-kB-nFTkF=VA_JPwFNo08S0d-Yk0F741S2B7LDmYAi8eyA@mail.gmail.com
It turns out that the calculation of [Merge]AppendPath.partitioned_rels
in allpaths.c is faulty and sometimes omits relevant non-leaf partitions,
allowing an assertion added by commit a929e17e5a to trigger. Rather
than fix that, it seems better to get rid of those fields altogether.
We don't really need the info until create_plan time, and calculating
it once for the selected plan should be cheaper than calculating it
for each append path we consider.
The preceding two commits did away with all use of the partitioned_rels
values; this commit just mechanically removes the fields and the code
that calculated them.
Discussion: https://postgr.es/m/87sg8tqhsl.fsf@aurora.ydns.eu
Discussion: https://postgr.es/m/CAJKUy5gCXDSmFs2c=R+VGgn7FiYcLCsEFEuDNNLGfoha=pBE_g@mail.gmail.com
Previously, pull_varnos() took the relids of a PlaceHolderVar as being
equal to the relids in its contents, but that fails to account for the
possibility that we have to postpone evaluation of the PHV due to outer
joins. This could result in a malformed plan. The known cases end up
triggering the "failed to assign all NestLoopParams to plan nodes"
sanity check in createplan.c, but other symptoms may be possible.
The right value to use is the join level we actually intend to evaluate
the PHV at. We can get that from the ph_eval_at field of the associated
PlaceHolderInfo. However, there are some places that call pull_varnos()
before the PlaceHolderInfos have been created; in that case, fall back
to the conservative assumption that the PHV will be evaluated at its
syntactic level. (In principle this might result in missing some legal
optimization, but I'm not aware of any cases where it's an issue in
practice.) Things are also a bit ticklish for calls occurring during
deconstruct_jointree(), but AFAICS the ph_eval_at fields should have
reached their final values by the time we need them.
The main problem in making this work is that pull_varnos() has no
way to get at the PlaceHolderInfos. We can fix that easily, if a
bit tediously, in HEAD by passing it the planner "root" pointer.
In the back branches that'd cause an unacceptable API/ABI break for
extensions, so leave the existing entry points alone and add new ones
with the additional parameter. (If an old entry point is called and
encounters a PHV, it'll fall back to using the syntactic level,
again possibly missing some valid optimization.)
Back-patch to v12. The computation is surely also wrong before that,
but it appears that we cannot reach a bad plan thanks to join order
restrictions imposed on the subquery that the PlaceHolderVar came from.
The error only became reachable when commit 4be058fe9 allowed trivial
subqueries to be collapsed out completely, eliminating their join order
restrictions.
Per report from Stephan Springl.
Discussion: https://postgr.es/m/171041.1610849523@sss.pgh.pa.us
While we do allow SRFs in ORDER BY, scan/join processing should not
consider such cases - such sorts should only happen via final Sort atop
a ProjectSet. So make sure we don't try adding such sorts below Gather
Merge, just like we do for expressions that are volatile and/or not
parallel safe.
Backpatch to PostgreSQL 13, where this code was introduced as part of
the Incremental Sort patch.
Author: James Coleman
Reviewed-by: Tomas Vondra
Backpatch-through: 13
Discussion: https://postgr.es/m/CAAaqYe8cK3g5CfLC4w7bs=hC0mSksZC=H5M8LSchj5e5OxpTAg@mail.gmail.com
Discussion: https://postgr.es/m/295524.1606246314%40sss.pgh.pa.us
Commit ebb7ae839d ensured we ignore pathkeys with volatile expressions
when considering adding a sort below a Gather Merge. Turns out we need
to care about parallel safety of the pathkeys too, otherwise we might
try sorting e.g. on results of a correlated subquery (as demonstrated
by a report from Luis Roberto).
Initial investigation by Tom Lane, patch by James Coleman. Backpatch
to 13, where the code was instroduced (as part of Incremental Sort).
Reported-by: Luis Roberto
Author: James Coleman
Reviewed-by: Tomas Vondra
Backpatch-through: 13
Discussion: https://postgr.es/m/622580997.37108180.1604080457319.JavaMail.zimbra%40siscobra.com.br
Discussion: https://postgr.es/m/CAAaqYe8cK3g5CfLC4w7bs=hC0mSksZC=H5M8LSchj5e5OxpTAg@mail.gmail.com
Formerly we only applied extended statistics to an OR clause as part
of the clauselist_selectivity() code path for an OR clause appearing
in an implicitly-ANDed list of clauses. This meant that it could only
use extended statistics if all sub-clauses of the OR clause were
covered by a single extended statistics object.
Instead, teach clause_selectivity() how to apply extended statistics
to an OR clause by handling its ORed list of sub-clauses in a similar
manner to an implicitly-ANDed list of sub-clauses, but with different
combination rules. This allows one or more extended statistics objects
to be used to estimate all or part of the list of sub-clauses. Any
remaining sub-clauses are then treated as if they are independent.
Additionally, to avoid double-application of extended statistics, this
introduces "extended" versions of clause_selectivity() and
clauselist_selectivity(), which include an option to ignore extended
statistics. This replaces the old clauselist_selectivity_simple()
function which failed to completely ignore extended statistics when
called from the extended statistics code.
A known limitation of the current infrastructure is that an AND clause
under an OR clause is not treated as compatible with extended
statistics (because we don't build RestrictInfos for such sub-AND
clauses). Thus, for example, "(a=1 AND b=1) OR (a=2 AND b=2)" will
currently be treated as two independent AND clauses (each of which may
be estimated using extended statistics), but extended statistics will
not currently be used to account for any possible overlap between
those clauses. Improving that is left as a task for the future.
Original patch by Tomas Vondra, with additional improvements by me.
Discussion: https://postgr.es/m/20200113230008.g67iyk4cs3xbnjju@development
For debugging purposes, Path nodes are supposed to have outfuncs
support, but this was overlooked in the original incremental sort patch.
While at it, clean up a couple other minor oversights, as well as
bizarre choice of return type for create_incremental_sort_path().
(All the existing callers just cast it to "Path *" immediately, so
they don't care, but some future caller might care.)
outfuncs.c fix by Zhijie Hou, the rest by me
Discussion: https://postgr.es/m/324c4d81d8134117972a5b1f6cdf9560@G08CNEXMBPEKD05.g08.fujitsu.local
