| Commit message (Collapse) | Author | Age |
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For an EXISTS subquery, the only thing that matters is whether it
returns zero or more than zero rows. Therefore, we remove certain SQL
features that won't affect that, among them the GROUP BY clauses.
After we drop the groupClause, we'd better remove the RTE_GROUP RTE
and clear the hasGroupRTE flag, as they depend on the groupClause.
Failing to do so could result in a bogus RTE_GROUP entry in the parent
query, leading to an assertion failure on the hasGroupRTE flag.
Reported-by: David Rowley
Author: Richard Guo
Discussion: https://postgr.es/m/CAApHDvp2_yht8uPLyWO-kVGWZhYvx5zjGfSrg4fBQ9fsC13V0g@mail.gmail.com
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Introduced by 9f1337639.
Author: James Coleman <jtc331@gmail.com>
Discussion: https://postgr.es/m/CAAaqYe9ZQ_1+QiF_Nv7b37opicBu+35ZQK1CetQ54r5UdrF1eg@mail.gmail.com
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This reverts commit 7204f35919b7e021e8d1bc9f2d76fd6bfcdd2070,
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.
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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)
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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
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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
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Historically we've printed SubPlan expression nodes as "(SubPlan N)",
which is pretty uninformative. Trying to reproduce the original SQL
for the subquery is still as impractical as before, and would be
mighty verbose as well. However, we can still do better than that.
Displaying the "testexpr" when present, and adding a keyword to
indicate the SubLinkType, goes a long way toward showing what's
really going on.
In addition, this patch gets rid of EXPLAIN's use of "$n" to represent
subplan and initplan output Params. Instead we now print "(SubPlan
N).colX" or "(InitPlan N).colX" to represent the X'th output column
of that subplan. This eliminates confusion with the use of "$n" to
represent PARAM_EXTERN Params, and it's useful for the first part of
this change because it eliminates needing some other indication of
which subplan is referenced by a SubPlan that has a testexpr.
In passing, this adds simple regression test coverage of the
ROWCOMPARE_SUBLINK code paths, which were entirely unburdened
by testing before.
Tom Lane and Dean Rasheed, reviewed by Aleksander Alekseev.
Thanks to Chantal Keller for raising the question of whether
this area couldn't be improved.
Discussion: https://postgr.es/m/2838538.1705692747@sss.pgh.pa.us
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This allows a RETURNING clause to be appended to a MERGE query, to
return values based on each row inserted, updated, or deleted. As with
plain INSERT, UPDATE, and DELETE commands, the returned values are
based on the new contents of the target table for INSERT and UPDATE
actions, and on its old contents for DELETE actions. Values from the
source relation may also be returned.
As with INSERT/UPDATE/DELETE, the output of MERGE ... RETURNING may be
used as the source relation for other operations such as WITH queries
and COPY commands.
Additionally, a special function merge_action() is provided, which
returns 'INSERT', 'UPDATE', or 'DELETE', depending on the action
executed for each row. The merge_action() function can be used
anywhere in the RETURNING list, including in arbitrary expressions and
subqueries, but it is an error to use it anywhere outside of a MERGE
query's RETURNING list.
Dean Rasheed, reviewed by Isaac Morland, Vik Fearing, Alvaro Herrera,
Gurjeet Singh, Jian He, Jeff Davis, Merlin Moncure, Peter Eisentraut,
and Wolfgang Walther.
Discussion: http://postgr.es/m/CAEZATCWePEGQR5LBn-vD6SfeLZafzEm2Qy_L_Oky2=qw2w3Pzg@mail.gmail.com
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For ANY-SUBLINK, we adopted a two-stage pull-up approach to handle
different types of scenarios. In the first stage, the sublink is pulled up
as a subquery. Because of this, when writing this code, we did not have
the ability to perform lateral joins, and therefore, we were unable to
pull up Var with varlevelsup=1. Now that we have the ability to use
lateral joins, we can eliminate this limitation.
Author: Andy Fan <zhihui.fan1213@gmail.com>
Author: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Richard Guo <guofenglinux@gmail.com>
Reviewed-by: Alena Rybakina <lena.ribackina@yandex.ru>
Reviewed-by: Andrey Lepikhov <a.lepikhov@postgrespro.ru>
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Reported-by: Michael Paquier
Discussion: https://postgr.es/m/ZZKTDPxBBMt3C0J9@paquier.xyz
Backpatch-through: 12
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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
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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
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If the inner-side expressions contain PARAM_EXEC Params, we must
re-hash whenever the values of those Params change. The executor
mechanism for that exists already, but we failed to invoke it because
finalize_plan() neglected to search the Hash.hashkeys field for
Params. This allowed a previous scan's hash table to be re-used
when it should not be, leading to rows missing from the join's output.
(I believe incorrectly-included join rows are impossible however,
since checking the real hashclauses would reject false matches.)
This bug is very ancient, dating probably to d24d75ff1 of 7.4.
Sadly, this simple fix depends on the plan representational changes
made by 2abd7ae9b, so it will only work back to v12. I thought
about trying to make some kind of hack for v11, but I'm leery
of putting code significantly different from what is used in the
newer branches into a nearly-EOL branch. Seeing that the bug
escaped detection for a full twenty years, problematic cases
must be rare; so I don't feel too awful about leaving v11 as-is.
Per bug #17985 from Zuming Jiang. Back-patch to v12.
Discussion: https://postgr.es/m/17985-748b66607acd432e@postgresql.org
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Our policy since commit ab77a5a45 has been that a plan node having
any initplans is automatically not parallel-safe. (This could be
relaxed, but not today.) clean_up_removed_plan_level neglected
this, and could attach initplans to a parallel-safe child plan
node without clearing the plan's parallel-safe flag. That could
lead to "subplan was not initialized" errors at runtime, in case
an initplan referenced another one and only the referencing one
got transmitted to parallel workers.
The fix in clean_up_removed_plan_level is trivial enough.
materialize_finished_plan also moves initplans from one node
to another, but it's okay because it already copies the source
node's parallel_safe flag. The other place that does this kind
of thing is standard_planner's hack to inject a top-level Gather
when debug_parallel_query is active. But that's actually dead
code given that we're correctly enforcing the "initplans aren't
parallel safe" rule, so just replace it with an Assert that
there are no initplans.
Also improve some related comments.
Normally we'd add a regression test case for this sort of bug.
The mistake itself is already reached by existing tests, but there
is accidentally no visible problem. The only known test case that
creates an actual failure seems too indirect and fragile to justify
keeping it as a regression test (not least because it fails to fail
in v11, though the bug is clearly present there too).
Per report from Justin Pryzby. Back-patch to all supported branches.
Discussion: https://postgr.es/m/ZDVt6MaNWkRDO1LQ@telsasoft.com
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These are all dead code now that it's done centrally.
Patch by me; thanks to Nathan Bossart and Richard Guo for review.
Discussion: https://postgr.es/m/1159933.1677621588@sss.pgh.pa.us
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This function has been semi-deprecated ever since we invented
bms_next_member(). Its habit of scribbling on the input bitmapset
isn't great, plus for sufficiently large bitmapsets it would take
O(N^2) time to complete a loop. Now we have the additional problem
that reducing the input to empty while leaving it still accessible
would violate a planned invariant. So let's just get rid of it,
after updating the few extant callers to use bms_next_member().
Patch by me; thanks to Nathan Bossart and Richard Guo for review.
Discussion: https://postgr.es/m/1159933.1677621588@sss.pgh.pa.us
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Backpatch-through: 11
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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
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In a similar effort to f01592f91, here we're targetting fixing the
warnings where we've deemed the shadowing variable to serve a close enough
purpose to the shadowed variable just to reuse the shadowed version and
not declare the shadowing variable at all.
By my count, this takes the warning count from 106 down to 71.
Author: Justin Pryzby
Discussion: https://postgr.es/m/20220825020839.GT2342@telsasoft.com
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inline_cte() expected to find exactly as many references to the
target CTE as its cterefcount indicates. While that should be
accurate for the tree as emitted by the parser, there are some
optimizations that occur upstream of here that could falsify it,
notably removal of unused subquery output expressions.
Trying to make the accounting 100% accurate seems expensive and
doomed to future breakage. It's not really worth it, because
all this code is protecting is downstream assumptions that every
referenced CTE has a plan. Let's convert those assertions to
regular test-and-elog just in case there's some actual problem,
and then drop the failing assertion.
Per report from Tomas Vondra (thanks also to Richard Guo for
analysis). Back-patch to v12 where the faulty code came in.
Discussion: https://postgr.es/m/29196a1e-ed47-c7ca-9be2-b1c636816183@enterprisedb.com
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The planner needs to treat GroupingFunc like Aggref for many purposes,
in particular with respect to processing of the argument expressions,
which are not to be evaluated at runtime. A few places hadn't gotten
that memo, notably including subselect.c's processing of outer-level
aggregates. This resulted in assertion failures or wrong plans for
cases in which a GROUPING() construct references an outer aggregation
level.
Also fix missing special cases for GroupingFunc in cost_qual_eval
(resulting in wrong cost estimates for GROUPING(), although it's
not clear that that would affect plan shapes in practice) and in
ruleutils.c (resulting in excess parentheses in pretty-print mode).
Per bug #17088 from Yaoguang Chen. Back-patch to all supported
branches.
Richard Guo, Tom Lane
Discussion: https://postgr.es/m/17088-e33882b387de7f5c@postgresql.org
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The need for this was foreseen long ago, but when record_eq
actually became hashable (in commit 01e658fa7), we missed updating
this spot.
Per bug #17363 from Elvis Pranskevichus. Back-patch to v14 where
the faulty commit came in.
Discussion: https://postgr.es/m/17363-f6d42fd0d726be02@postgresql.org
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Backpatch-through: 10
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Commit 4ace45677 failed to fix the problem fully, because the
same issue of attempting to fetch a non-returnable index column
can occur when rechecking the indexqual after using a lossy index
operator. Moreover, it broke EXPLAIN for such indexquals (which
indicates a gap in our test cases :-().
Revert the code changes of 4ace45677 in favor of adding a new field
to struct IndexOnlyScan, containing a version of the indexqual that
can be executed against the index-returned tuple without using any
non-returnable columns. (The restrictions imposed by check_index_only
guarantee this is possible, although we may have to recompute indexed
expressions.) Support construction of that during setrefs.c
processing by marking IndexOnlyScan.indextlist entries as resjunk
if they can't be returned, rather than removing them entirely.
(We could alternatively require setrefs.c to look up the IndexOptInfo
again, but abusing resjunk this way seems like a reasonably safe way
to avoid needing to do that.)
This solution isn't great from an API-stability standpoint: if there
are any extensions out there that build IndexOnlyScan structs directly,
they'll be broken in the next minor releases. However, only a very
invasive extension would be likely to do such a thing. There's no
change in the Path representation, so typical planner extensions
shouldn't have a problem.
As before, back-patch to all supported branches.
Discussion: https://postgr.es/m/3179992.1641150853@sss.pgh.pa.us
Discussion: https://postgr.es/m/17350-b5bdcf476e5badbb@postgresql.org
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The point of introducing the hash_mem_multiplier GUC was to let users
reproduce the old behavior of hash aggregation, i.e. that it could use
more than work_mem at need. However, the implementation failed to get
the job done on Win64, where work_mem is clamped to 2GB to protect
various places that calculate memory sizes using "long int". As
written, the same clamp was applied to hash_mem. This resulted in
severe performance regressions for queries requiring a bit more than
2GB for hash aggregation, as they now spill to disk and there's no
way to stop that.
Getting rid of the work_mem restriction seems like a good idea, but
it's a big job and could not conceivably be back-patched. However,
there's only a fairly small number of places that are concerned with
the hash_mem value, and it turns out to be possible to remove the
restriction there without too much code churn or any ABI breaks.
So, let's do that for now to fix the regression, and leave the
larger task for another day.
This patch does introduce a bit more infrastructure that should help
with the larger task, namely pg_bitutils.h support for working with
size_t values.
Per gripe from Laurent Hasson. Back-patch to v13 where the
behavior change came in.
Discussion: https://postgr.es/m/997817.1627074924@sss.pgh.pa.us
Discussion: https://postgr.es/m/MN2PR15MB25601E80A9B6D1BA6F592B1985E39@MN2PR15MB2560.namprd15.prod.outlook.com
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"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
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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
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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
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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
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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
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This allows something like
SELECT ... FROM t1 JOIN t2 USING (a, b, c) AS x
where x has the columns a, b, c and unlike a regular alias it does not
hide the range variables of the tables being joined t1 and t2.
Per SQL:2016 feature F404 "Range variable for common column names".
Reviewed-by: Vik Fearing <vik.fearing@2ndquadrant.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://www.postgresql.org/message-id/flat/454638cf-d563-ab76-a585-2564428062af@2ndquadrant.com
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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
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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
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Backpatch-through: 9.5
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When commit bd3daddaf introduced AlternativeSubPlans, I had some
ambitions towards allowing the choice of subplan to change during
execution. That has not happened, or even been thought about, in the
ensuing twelve years; so it seems like a failed experiment. So let's
rip that out and resolve the choice of subplan at the end of planning
(in setrefs.c) rather than during executor startup. This has a number
of positive benefits:
* Removal of a few hundred lines of executor code, since
AlternativeSubPlans need no longer be supported there.
* Removal of executor-startup overhead (particularly, initialization
of subplans that won't be used).
* Removal of incidental costs of having a larger plan tree, such as
tree-scanning and copying costs in the plancache; not to mention
setrefs.c's own costs of processing the discarded subplans.
* EXPLAIN no longer has to print a weird (and undocumented)
representation of an AlternativeSubPlan choice; it sees only the
subplan actually used. This should mean less confusion for users.
* Since setrefs.c knows which subexpression of a plan node it's
working on at any instant, it's possible to adjust the estimated
number of executions of the subplan based on that. For example,
we should usually estimate more executions of a qual expression
than a targetlist expression. The implementation used here is
pretty simplistic, because we don't want to expend a lot of cycles
on the issue; but it's better than ignoring the point entirely,
as the executor had to.
That last point might possibly result in shifting the choice
between hashed and non-hashed EXISTS subplans in a few cases,
but in general this patch isn't meant to change planner choices.
Since we're doing the resolution so late, it's really impossible
to change any plan choices outside the AlternativeSubPlan itself.
Patch by me; thanks to David Rowley for review.
Discussion: https://postgr.es/m/1992952.1592785225@sss.pgh.pa.us
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nodeSubplan.c expects that the testexpr for a hashable ANY SubPlan
has the form of one or more OpExprs whose LHS is an expression of the
outer query's, while the RHS is an expression over Params representing
output columns of the subquery. However, the planner only went as far
as verifying that the clauses were all binary OpExprs. This works
99.99% of the time, because the clauses have the right shape when
emitted by the parser --- but it's possible for function inlining to
break that, as reported by PegoraroF10. To fix, teach the planner
to check that the LHS and RHS contain the right things, or more
accurately don't contain the wrong things. Given that this has been
broken for years without anyone noticing, it seems sufficient to just
give up hashing when it happens, rather than go to the trouble of
commuting the clauses back again (which wouldn't necessarily work
anyway).
While poking at that, I also noticed that nodeSubplan.c had a baked-in
assumption that the number of hash clauses is identical to the number
of subquery output columns. Again, that's fine as far as parser output
goes, but it's not hard to break it via function inlining. There seems
little reason for that assumption though --- AFAICS, the only thing
it's buying us is not having to store the number of hash clauses
explicitly. Adding code to the planner to reject such cases would take
more code than getting nodeSubplan.c to cope, so I fixed it that way.
This has been broken for as long as we've had hashable SubPlans,
so back-patch to all supported branches.
Discussion: https://postgr.es/m/1549209182255-0.post@n3.nabble.com
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Add a GUC that acts as a multiplier on work_mem. It gets applied when
sizing executor node hash tables that were previously size constrained
using work_mem alone.
The new GUC can be used to preferentially give hash-based nodes more
memory than the generic work_mem limit. It is intended to enable admin
tuning of the executor's memory usage. Overall system throughput and
system responsiveness can be improved by giving hash-based executor
nodes more memory (especially over sort-based alternatives, which are
often much less sensitive to being memory constrained).
The default value for hash_mem_multiplier is 1.0, which is also the
minimum valid value. This means that hash-based nodes continue to apply
work_mem in the traditional way by default.
hash_mem_multiplier is generally useful. However, it is being added now
due to concerns about hash aggregate performance stability for users
that upgrade to Postgres 13 (which added disk-based hash aggregation in
commit 1f39bce0). While the old hash aggregate behavior risked
out-of-memory errors, it is nevertheless likely that many users actually
benefited. Hash agg's previous indifference to work_mem during query
execution was not just faster; it also accidentally made aggregation
resilient to grouping estimate problems (at least in cases where this
didn't create destabilizing memory pressure).
hash_mem_multiplier can provide a certain kind of continuity with the
behavior of Postgres 12 hash aggregates in cases where the planner
incorrectly estimates that all groups (plus related allocations) will
fit in work_mem/hash_mem. This seems necessary because hash-based
aggregation is usually much slower when only a small fraction of all
groups can fit. Even when it isn't possible to totally avoid hash
aggregates that spill, giving hash aggregation more memory will reliably
improve performance (the same cannot be said for external sort
operations, which appear to be almost unaffected by memory availability
provided it's at least possible to get a single merge pass).
The PostgreSQL 13 release notes should advise users that increasing
hash_mem_multiplier can help with performance regressions associated
with hash aggregation. That can be taken care of by a later commit.
Author: Peter Geoghegan
Reviewed-By: Álvaro Herrera, Jeff Davis
Discussion: https://postgr.es/m/20200625203629.7m6yvut7eqblgmfo@alap3.anarazel.de
Discussion: https://postgr.es/m/CAH2-WzmD%2Bi1pG6rc1%2BCjc4V6EaFJ_qSuKCCHVnH%3DoruqD-zqow%40mail.gmail.com
Backpatch: 13-, where disk-based hash aggregation was introduced.
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Incremental Sort is an optimized variant of multikey sort for cases when
the input is already sorted by a prefix of the requested sort keys. For
example when the relation is already sorted by (key1, key2) and we need
to sort it by (key1, key2, key3) we can simply split the input rows into
groups having equal values in (key1, key2), and only sort/compare the
remaining column key3.
This has a number of benefits:
- Reduced memory consumption, because only a single group (determined by
values in the sorted prefix) needs to be kept in memory. This may also
eliminate the need to spill to disk.
- Lower startup cost, because Incremental Sort produce results after each
prefix group, which is beneficial for plans where startup cost matters
(like for example queries with LIMIT clause).
We consider both Sort and Incremental Sort, and decide based on costing.
The implemented algorithm operates in two different modes:
- Fetching a minimum number of tuples without check of equality on the
prefix keys, and sorting on all columns when safe.
- Fetching all tuples for a single prefix group and then sorting by
comparing only the remaining (non-prefix) keys.
We always start in the first mode, and employ a heuristic to switch into
the second mode if we believe it's beneficial - the goal is to minimize
the number of unnecessary comparions while keeping memory consumption
below work_mem.
This is a very old patch series. The idea was originally proposed by
Alexander Korotkov back in 2013, and then revived in 2017. In 2018 the
patch was taken over by James Coleman, who wrote and rewrote most of the
current code.
There were many reviewers/contributors since 2013 - I've done my best to
pick the most active ones, and listed them in this commit message.
Author: James Coleman, Alexander Korotkov
Reviewed-by: Tomas Vondra, Andreas Karlsson, Marti Raudsepp, Peter Geoghegan, Robert Haas, Thomas Munro, Antonin Houska, Andres Freund, Alexander Kuzmenkov
Discussion: https://postgr.es/m/CAPpHfdscOX5an71nHd8WSUH6GNOCf=V7wgDaTXdDd9=goN-gfA@mail.gmail.com
Discussion: https://postgr.es/m/CAPpHfds1waRZ=NOmueYq0sx1ZSCnt+5QJvizT8ndT2=etZEeAQ@mail.gmail.com
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When I added the ParseNamespaceItem data structure (in commit 5ebaaa494),
it wasn't very tightly integrated into the parser's APIs. In the wake of
adding p_rtindex to that struct (commit b541e9acc), there is a good reason
to make more use of it: by passing around ParseNamespaceItem pointers
instead of bare RTE pointers, we can get rid of various messy methods for
passing back or deducing the rangetable index of an RTE during parsing.
Hence, refactor the addRangeTableEntryXXX functions to build and return
a ParseNamespaceItem struct, not just the RTE proper; and replace
addRTEtoQuery with addNSItemToQuery, which is passed a ParseNamespaceItem
rather than building one internally.
Also, add per-column data (a ParseNamespaceColumn array) to each
ParseNamespaceItem. These arrays are built during addRangeTableEntryXXX,
where we have column type data at hand so that it's nearly free to fill
the data structure. Later, when we need to build Vars referencing RTEs,
we can use the ParseNamespaceColumn info to avoid the rather expensive
operations done in get_rte_attribute_type() or expandRTE().
get_rte_attribute_type() is indeed dead code now, so I've removed it.
This makes for a useful improvement in parse analysis speed, around 20%
in one moderately-complex test query.
The ParseNamespaceColumn structs also include Var identity information
(varno/varattno). That info isn't actually being used in this patch,
except that p_varno == 0 is a handy test for a dropped column.
A follow-on patch will make more use of it.
Discussion: https://postgr.es/m/2461.1577764221@sss.pgh.pa.us
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Backpatch-through: update all files in master, backpatch legal files through 9.4
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Originally, Postgres Lists were a more or less exact reimplementation of
Lisp lists, which consist of chains of separately-allocated cons cells,
each having a value and a next-cell link. We'd hacked that once before
(commit d0b4399d8) to add a separate List header, but the data was still
in cons cells. That makes some operations -- notably list_nth() -- O(N),
and it's bulky because of the next-cell pointers and per-cell palloc
overhead, and it's very cache-unfriendly if the cons cells end up
scattered around rather than being adjacent.
In this rewrite, we still have List headers, but the data is in a
resizable array of values, with no next-cell links. Now we need at
most two palloc's per List, and often only one, since we can allocate
some values in the same palloc call as the List header. (Of course,
extending an existing List may require repalloc's to enlarge the array.
But this involves just O(log N) allocations not O(N).)
Of course this is not without downsides. The key difficulty is that
addition or deletion of a list entry may now cause other entries to
move, which it did not before.
For example, that breaks foreach() and sister macros, which historically
used a pointer to the current cons-cell as loop state. We can repair
those macros transparently by making their actual loop state be an
integer list index; the exposed "ListCell *" pointer is no longer state
carried across loop iterations, but is just a derived value. (In
practice, modern compilers can optimize things back to having just one
loop state value, at least for simple cases with inline loop bodies.)
In principle, this is a semantics change for cases where the loop body
inserts or deletes list entries ahead of the current loop index; but
I found no such cases in the Postgres code.
The change is not at all transparent for code that doesn't use foreach()
but chases lists "by hand" using lnext(). The largest share of such
code in the backend is in loops that were maintaining "prev" and "next"
variables in addition to the current-cell pointer, in order to delete
list cells efficiently using list_delete_cell(). However, we no longer
need a previous-cell pointer to delete a list cell efficiently. Keeping
a next-cell pointer doesn't work, as explained above, but we can improve
matters by changing such code to use a regular foreach() loop and then
using the new macro foreach_delete_current() to delete the current cell.
(This macro knows how to update the associated foreach loop's state so
that no cells will be missed in the traversal.)
There remains a nontrivial risk of code assuming that a ListCell *
pointer will remain good over an operation that could now move the list
contents. To help catch such errors, list.c can be compiled with a new
define symbol DEBUG_LIST_MEMORY_USAGE that forcibly moves list contents
whenever that could possibly happen. This makes list operations
significantly more expensive so it's not normally turned on (though it
is on by default if USE_VALGRIND is on).
There are two notable API differences from the previous code:
* lnext() now requires the List's header pointer in addition to the
current cell's address.
* list_delete_cell() no longer requires a previous-cell argument.
These changes are somewhat unfortunate, but on the other hand code using
either function needs inspection to see if it is assuming anything
it shouldn't, so it's not all bad.
Programmers should be aware of these significant performance changes:
* list_nth() and related functions are now O(1); so there's no
major access-speed difference between a list and an array.
* Inserting or deleting a list element now takes time proportional to
the distance to the end of the list, due to moving the array elements.
(However, it typically *doesn't* require palloc or pfree, so except in
long lists it's probably still faster than before.) Notably, lcons()
used to be about the same cost as lappend(), but that's no longer true
if the list is long. Code that uses lcons() and list_delete_first()
to maintain a stack might usefully be rewritten to push and pop at the
end of the list rather than the beginning.
* There are now list_insert_nth...() and list_delete_nth...() functions
that add or remove a list cell identified by index. These have the
data-movement penalty explained above, but there's no search penalty.
* list_concat() and variants now copy the second list's data into
storage belonging to the first list, so there is no longer any
sharing of cells between the input lists. The second argument is
now declared "const List *" to reflect that it isn't changed.
This patch just does the minimum needed to get the new implementation
in place and fix bugs exposed by the regression tests. As suggested
by the foregoing, there's a fair amount of followup work remaining to
do.
Also, the ENABLE_LIST_COMPAT macros are finally removed in this
commit. Code using those should have been gone a dozen years ago.
Patch by me; thanks to David Rowley, Jesper Pedersen, and others
for review.
Discussion: https://postgr.es/m/11587.1550975080@sss.pgh.pa.us
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Switch to 2.1 version of pg_bsd_indent. This formats
multiline function declarations "correctly", that is with
additional lines of parameter declarations indented to match
where the first line's left parenthesis is.
Discussion: https://postgr.es/m/CAEepm=0P3FeTXRcU5B2W3jv3PgRVZ-kGUXLGfd42FFhUROO3ug@mail.gmail.com
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This has to be prevented because inlining would result in multiple
self-references, which we don't support (and in fact that's disallowed
by the SQL spec, see statements about linearly vs. nonlinearly
recursive queries). Bug fix for commit 608b167f9.
Per report from Yaroslav Schekin (via Andrew Gierth)
Discussion: https://postgr.es/m/87wolmg60q.fsf@news-spur.riddles.org.uk
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We have forboth() and forthree() macros that simplify iterating
through several parallel lists, but not everyplace that could
reasonably use those was doing so. Also invent forfour() and
forfive() macros to do the same for four or five parallel lists,
and use those where applicable.
The immediate motivation for doing this is to reduce the number
of ad-hoc lnext() calls, to reduce the footprint of a WIP patch.
However, it seems like good cleanup and error-proofing anyway;
the places that were combining forthree() with a manually iterated
loop seem particularly illegible and bug-prone.
There was some speculation about restructuring related parsetree
representations to reduce the need for parallel list chasing of
this sort. Perhaps that's a win, or perhaps not, but in any case
it would be considerably more invasive than this patch; and it's
not particularly related to my immediate goal of improving the
List infrastructure. So I'll leave that question for another day.
Patch by me; thanks to David Rowley for review.
Discussion: https://postgr.es/m/11587.1550975080@sss.pgh.pa.us
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Historically we've always materialized the full output of a CTE query,
treating WITH as an optimization fence (so that, for example, restrictions
from the outer query cannot be pushed into it). This is appropriate when
the CTE query is INSERT/UPDATE/DELETE, or is recursive; but when the CTE
query is non-recursive and side-effect-free, there's no hazard of changing
the query results by pushing restrictions down.
Another argument for materialization is that it can avoid duplicate
computation of an expensive WITH query --- but that only applies if
the WITH query is called more than once in the outer query. Even then
it could still be a net loss, if each call has restrictions that
would allow just a small part of the WITH query to be computed.
Hence, let's change the behavior for WITH queries that are non-recursive
and side-effect-free. By default, we will inline them into the outer
query (removing the optimization fence) if they are called just once.
If they are called more than once, we will keep the old behavior by
default, but the user can override this and force inlining by specifying
NOT MATERIALIZED. Lastly, the user can force the old behavior by
specifying MATERIALIZED; this would mainly be useful when the query had
deliberately been employing WITH as an optimization fence to prevent a
poor choice of plan.
Andreas Karlsson, Andrew Gierth, David Fetter
Discussion: https://postgr.es/m/87sh48ffhb.fsf@news-spur.riddles.org.uk
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Create a new header optimizer/optimizer.h, which exposes just the
planner functions that can be used "at arm's length", without need
to access Paths or the other planner-internal data structures defined
in nodes/relation.h. This is intended to provide the whole planner
API seen by most of the rest of the system; although FDWs still need
to use additional stuff, and more thought is also needed about just
what selfuncs.c should rely on.
The main point of doing this now is to limit the amount of new
#include baggage that will be needed by "planner support functions",
which I expect to introduce later, and which will be in relevant
datatype modules rather than anywhere near the planner.
This commit just moves relevant declarations into optimizer.h from
other header files (a couple of which go away because everything
got moved), and adjusts #include lists to match. There's further
cleanup that could be done if we want to decide that some stuff
being exposed by optimizer.h doesn't belong in the planner at all,
but I'll leave that for another day.
Discussion: https://postgr.es/m/11460.1548706639@sss.pgh.pa.us
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Move a few very simple node-creation and node-type-testing functions
from the planner's clauses.c to nodes/makefuncs and nodes/nodeFuncs.
There's nothing planner-specific about them, as evidenced by the
number of other places that were using them.
While at it, rename and_clause() etc to is_andclause() etc, to clarify
that they are node-type-testing functions not node-creation functions.
And use "static inline" implementations for the shortest ones.
Also, modify flatten_join_alias_vars() and some subsidiary functions
to take a Query not a PlannerInfo to define the join structure that
Vars should be translated according to. They were only using the
"parse" field of the PlannerInfo anyway, so this just requires removing
one level of indirection. The advantage is that now parse_agg.c can
use flatten_join_alias_vars() without the horrid kluge of creating an
incomplete PlannerInfo, which will allow that file to be decoupled from
relation.h in a subsequent patch.
Discussion: https://postgr.es/m/11460.1548706639@sss.pgh.pa.us
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The fact that "SELECT expression" has no base relations has long been a
thorn in the side of the planner. It makes it hard to flatten a sub-query
that looks like that, or is a trivial VALUES() item, because the planner
generally uses relid sets to identify sub-relations, and such a sub-query
would have an empty relid set if we flattened it. prepjointree.c contains
some baroque logic that works around this in certain special cases --- but
there is a much better answer. We can replace an empty FROM clause with a
dummy RTE that acts like a table of one row and no columns, and then there
are no such corner cases to worry about. Instead we need some logic to
get rid of useless dummy RTEs, but that's simpler and covers more cases
than what was there before.
For really trivial cases, where the query is just "SELECT expression" and
nothing else, there's a hazard that adding the extra RTE makes for a
noticeable slowdown; even though it's not much processing, there's not
that much for the planner to do overall. However testing says that the
penalty is very small, close to the noise level. In more complex queries,
this is able to find optimizations that we could not find before.
The new RTE type is called RTE_RESULT, since the "scan" plan type it
gives rise to is a Result node (the same plan we produced for a "SELECT
expression" query before). To avoid confusion, rename the old ResultPath
path type to GroupResultPath, reflecting that it's only used in degenerate
grouping cases where we know the query produces just one grouped row.
(It wouldn't work to unify the two cases, because there are different
rules about where the associated quals live during query_planner.)
Note: although this touches readfuncs.c, I don't think a catversion
bump is required, because the added case can't occur in stored rules,
only plans.
Patch by me, reviewed by David Rowley and Mark Dilger
Discussion: https://postgr.es/m/15944.1521127664@sss.pgh.pa.us
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Up to now, createplan.c attempted to share PARAM_EXEC slots for
NestLoopParams across different plan levels, if the same underlying Var
was being fed down to different righthand-side subplan trees by different
NestLoops. This was, I think, more of an artifact of using subselect.c's
PlannerParamItem infrastructure than an explicit design goal, but anyway
that was the end result.
This works well enough as long as the plan tree is executing synchronously,
but the feature whereby Gather can execute the parallelized subplan locally
breaks it. An upper NestLoop node might execute for a row retrieved from
a parallel worker, and assign a value for a PARAM_EXEC slot from that row,
while the leader's copy of the parallelized subplan is suspended with a
different active value of the row the Var comes from. When control
eventually returns to the leader's subplan, it gets the wrong answers if
the same PARAM_EXEC slot is being used within the subplan, as reported
in bug #15577 from Bartosz Polnik.
This is pretty reminiscent of the problem fixed in commit 46c508fbc, and
the proper fix seems to be the same: don't try to share PARAM_EXEC slots
across different levels of controlling NestLoop nodes.
This requires decoupling NestLoopParam handling from PlannerParamItem
handling, although the logic remains somewhat similar. To avoid bizarre
division of labor between subselect.c and createplan.c, I decided to move
all the param-slot-assignment logic for both cases out of those files
and put it into a new file paramassign.c. Hopefully it's a bit better
documented now, too.
A regression test case for this might be nice, but we don't know a
test case that triggers the problem with a suitably small amount
of data.
Back-patch to 9.6 where we added Gather nodes. It's conceivable that
related problems exist in older branches; but without some evidence
for that, I'll leave the older branches alone.
Discussion: https://postgr.es/m/15577-ca61ab18904af852@postgresql.org
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Backpatch-through: certain files through 9.4
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