Existing partition pruning is only able to work at plan time, for query
quals that appear in the parsed query. This is good but limiting, as
there can be parameters that appear later that can be usefully used to
further prune partitions.
This commit adds support for pruning subnodes of Append which cannot
possibly contain any matching tuples, during execution, by evaluating
Params to determine the minimum set of subnodes that can possibly match.
We support more than just simple Params in WHERE clauses. Support
additionally includes:
1. Parameterized Nested Loop Joins: The parameter from the outer side of the
join can be used to determine the minimum set of inner side partitions to
scan.
2. Initplans: Once an initplan has been executed we can then determine which
partitions match the value from the initplan.
Partition pruning is performed in two ways. When Params external to the plan
are found to match the partition key we attempt to prune away unneeded Append
subplans during the initialization of the executor. This allows us to bypass
the initialization of non-matching subplans meaning they won't appear in the
EXPLAIN or EXPLAIN ANALYZE output.
For parameters whose value is only known during the actual execution
then the pruning of these subplans must wait. Subplans which are
eliminated during this stage of pruning are still visible in the EXPLAIN
output. In order to determine if pruning has actually taken place, the
EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never
executed due to the elimination of the partition then the execution
timing area will state "(never executed)". Whereas, if, for example in
the case of parameterized nested loops, the number of loops stated in
the EXPLAIN ANALYZE output for certain subplans may appear lower than
others due to the subplan having been scanned fewer times. This is due
to the list of matching subnodes having to be evaluated whenever a
parameter which was found to match the partition key changes.
This commit required some additional infrastructure that permits the
building of a data structure which is able to perform the translation of
the matching partition IDs, as returned by get_matching_partitions, into
the list index of a subpaths list, as exist in node types such as
Append, MergeAppend and ModifyTable. This allows us to translate a list
of clauses into a Bitmapset of all the subpath indexes which must be
included to satisfy the clause list.
Author: David Rowley, based on an earlier effort by Beena Emerson
Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi,
Jesper Pedersen
Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
Add a new module backend/partitioning/partprune.c, implementing a more
sophisticated algorithm for partition pruning. The new module uses each
partition's "boundinfo" for pruning instead of constraint exclusion,
based on an idea proposed by Robert Haas of a "pruning program": a list
of steps generated from the query quals which are run iteratively to
obtain a list of partitions that must be scanned in order to satisfy
those quals.
At present, this targets planner-time partition pruning, but there exist
further patches to apply partition pruning at execution time as well.
This commit also moves some definitions from include/catalog/partition.h
to a new file include/partitioning/partbounds.h, in an attempt to
rationalize partitioning related code.
Authors: Amit Langote, David Rowley, Dilip Kumar
Reviewers: Robert Haas, Kyotaro Horiguchi, Ashutosh Bapat, Jesper Pedersen.
Discussion: https://postgr.es/m/098b9c71-1915-1a2a-8d52-1a7a50ce79e8@lab.ntt.co.jp
Review comments from Andres Freund
* Consolidate code into AfterTriggerGetTransitionTable()
* Rename nodeMerge.c to execMerge.c
* Rename nodeMerge.h to execMerge.h
* Move MERGE handling in ExecInitModifyTable()
into a execMerge.c ExecInitMerge()
* Move mt_merge_subcommands flags into execMerge.h
* Rename opt_and_condition to opt_merge_when_and_condition
* Wordsmith various comments
Author: Pavan Deolasee
Reviewer: Simon Riggs
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 other require multiple PL statements.
e.g.
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 and partitioned tables, including
column and row security enforcement, as well as support for
row, statement and transition triggers.
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 statically from PL/pgSQL.
MERGE does not yet support inheritance, write rules,
RETURNING clauses, updatable views or foreign tables.
MERGE follows SQL Standard per the most recent SQL:2016.
Includes full tests and documentation, including full
isolation tests to demonstrate the concurrent behavior.
This version written from scratch in 2017 by Simon Riggs,
using docs and tests originally written in 2009. Later work
from Pavan Deolasee has been both complex and deep, leaving
the lead author credit now in his hands.
Extensive discussion of concurrency from Peter Geoghegan,
with thanks for the time and effort contributed.
Various issues reported via sqlsmith by Andreas Seltenreich
Authors: Pavan Deolasee, Simon Riggs
Reviewer: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs
Discussion:
https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.comhttps://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
Since commit 7012b132d0, postgres_fdw
has been able to push down the toplevel aggregation operation to the
remote server. Commit e2f1eb0ee3 made
it possible to break down the toplevel aggregation into one
aggregate per partition. This commit lets postgres_fdw push down
aggregation in that case just as it does at the top level.
In order to make this work, this commit adds an additional argument
to the GetForeignUpperPaths FDW API. A matching argument is added
to the signature for create_upper_paths_hook. Third-party code using
either of these will need to be updated.
Also adjust create_foreignscan_plan() so that it picks up the correct
set of relids in this case.
Jeevan Chalke, reviewed by Ashutosh Bapat and by me and with some
adjustments by me. The larger patch series of which this patch is a
part was also reviewed and tested by Antonin Houska, Rajkumar
Raghuwanshi, David Rowley, Dilip Kumar, Konstantin Knizhnik, Pascal
Legrand, and Rafia Sabih.
Discussion: http://postgr.es/m/CAM2+6=V64_xhstVHie0Rz=KPEQnLJMZt_e314P0jaT_oJ9MR8A@mail.gmail.com
Discussion: http://postgr.es/m/CAM2+6=XPWujjmj5zUaBTGDoB38CemwcPmjkRy0qOcsQj_V+2sQ@mail.gmail.com
Unlike the previous coding, this might result in a Gather per Append
subplan when the target list is parallel-restricted, but such a plan
is probably worth considering in that case, since a single Gather
on top of the entire Append is impossible.
Per Andres Freund and the buildfarm.
Discussion: http://postgr.es/m/20180330050351.bmxx4cdtz67czjda@alap3.anarazel.de
If the toplevel scan/join target list is parallel-safe, postpone
generating Gather (or Gather Merge) paths until after the toplevel has
been adjusted to return it. This (correctly) makes queries with
expensive functions in the target list more likely to choose a
parallel plan, since the cost of the plan now reflects the fact that
the evaluation will happen in the workers rather than the leader.
The original complaint about this problem was from Jeff Janes.
If the toplevel scan/join relation is partitioned, recursively apply
the changes to all partitions. This sometimes allows us to get rid of
Result nodes, because Append is not projection-capable but its
children may be. It also cleans up what appears to be incorrect SRF
handling from commit e2f1eb0ee3: the old
code had no knowledge of SRFs for child scan/join rels.
Because we now use create_projection_path() in some cases where we
formerly used apply_projection_to_path(), this changes the ordering
of columns in some queries generated by postgres_fdw. Update
regression outputs accordingly.
Patch by me, reviewed by Amit Kapila and by Ashutosh Bapat. Other
fixes for this problem (substantially different from this version)
were reviewed by Dilip Kumar, Amit Khandekar, and Marina Polyakova.
Discussion: http://postgr.es/m/CAMkU=1ycXNipvhWuweUVpKuyu6SpNjF=yHWu4c4US5JgVGxtZQ@mail.gmail.com
Don't call generate_gather_paths for the topmost scan/join relation
when it is initially populated with paths. Instead, do the work in
grouping_planner. By itself, this gains nothing; in fact it loses
slightly because we end up calling set_cheapest() for the topmost
scan/join rel twice rather than once. However, it paves the way for
a future commit which will postpone generate_gather_paths for the
topmost scan/join relation even further, allowing more accurate
costing of parallel paths.
Amit Kapila and Robert Haas. Earlier versions of this patch (which
different substantially) were reviewed by Dilip Kumar, Amit
Khandekar, Marina Polyakova, and Ashutosh Bapat.
We sometimes insert a ProjectionPath into a plan tree when projection
is not strictly required. The existing code already arranges to avoid
emitting a Result node when the ProjectionPath's subpath can perform
the projection itself, but previously it didn't consider the
possibility that the parent node might not actually require the
projection to be performed at all.
Skipping projection when it's not required can not only avoid Result
nodes that aren't needed, but also avoid losing the "physical tlist"
optimization unneccessarily.
Patch by me, reviewed by Amit Kapila.
Discussion: http://postgr.es/m/CA+TgmoakT5gmahbPWGqrR2nAdFOMAOnOXYoWHRdVfGWs34t6_A@mail.gmail.com
This provides infrastructure to allow JITed code to inline code
implemented in C. This e.g. can be postgres internal functions or
extension code.
This already speeds up long running queries, by allowing the LLVM
optimizer to optimize across function boundaries. The optimization
potential currently doesn't reach its full potential because LLVM
cannot optimize the FunctionCallInfoData argument fully away, because
it's allocated on the heap rather than the stack. Fixing that is
beyond what's realistic for v11.
To be able to do that, use CLANG to convert C code to LLVM bitcode,
and have LLVM build a summary for it. That bitcode can then be used to
to inline functions at runtime. For that the bitcode needs to be
installed. Postgres bitcode goes into $pkglibdir/bitcode/postgres,
extensions go into equivalent directories. PGXS has been modified so
that happens automatically if postgres has been compiled with LLVM
support.
Currently this isn't the fastest inline implementation, modules are
reloaded from disk during inlining. That's to work around an apparent
LLVM bug, triggering an apparently spurious error in LLVM assertion
enabled builds. Once that is resolved we can remove the superfluous
read from disk.
Docs will follow in a later commit containing docs for the whole JIT
feature.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
Performing JIT compilation for deforming gains performance benefits
over unJITed deforming from compile-time knowledge of the tuple
descriptor. Fixed column widths, NOT NULLness, etc can be taken
advantage of.
Right now the JITed deforming is only used when deforming tuples as
part of expression evaluation (and obviously only if the descriptor is
known). It's likely to be beneficial in other cases, too.
By default tuple deforming is JITed whenever an expression is JIT
compiled. There's a separate boolean GUC controlling it, but that's
expected to be primarily useful for development and benchmarking.
Docs will follow in a later commit containing docs for the whole JIT
feature.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
In addition to the interpretation of expressions (which back
evaluation of WHERE clauses, target list projection, aggregates
transition values etc) support compiling expressions to native code,
using the infrastructure added in earlier commits.
To avoid duplicating a lot of code, only support emitting code for
cases that are likely to be performance critical. For expression steps
that aren't deemed that, use the existing interpreter.
The generated code isn't great - some architectural changes are
required to address that. But this already yields a significant
speedup for some analytics queries, particularly with WHERE clauses
filtering a lot, or computing multiple aggregates.
Author: Andres Freund
Tested-By: Thomas Munro
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
Disable JITing for VALUES() nodes.
VALUES() nodes are only ever executed once. This is primarily helpful
for debugging, when forcing JITing even for cheap queries.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
This adds simple cost based plan time decision about whether JIT
should be performed. jit_above_cost, jit_optimize_above_cost are
compared with the total cost of a plan, and if the cost is above them
JIT is performed / optimization is performed respectively.
For that PlannedStmt and EState have a jitFlags (es_jit_flags) field
that stores information about what JIT operations should be performed.
EState now also has a new es_jit field, which can store a
JitContext. When there are no errors the context is released in
standard_ExecutorEnd().
It is likely that the default values for jit_[optimize_]above_cost
will need to be adapted further, but in my test these values seem to
work reasonably.
Author: Andres Freund, with feedback by Peter Eisentraut
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
If the partition keys of input relation are part of the GROUP BY
clause, all the rows belonging to a given group come from a single
partition. This allows aggregation/grouping over a partitioned
relation to be broken down * into aggregation/grouping on each
partition. This should be no worse, and often better, than the normal
approach.
If the GROUP BY clause does not contain all the partition keys, we can
still perform partial aggregation for each partition and then finalize
aggregation after appending the partial results. This is less certain
to be a win, but it's still useful.
Jeevan Chalke, Ashutosh Bapat, Robert Haas. The larger patch series
of which this patch is a part was also reviewed and tested by Antonin
Houska, Rajkumar Raghuwanshi, David Rowley, Dilip Kumar, Konstantin
Knizhnik, Pascal Legrand, and Rafia Sabih.
Discussion: http://postgr.es/m/CAM2+6=V64_xhstVHie0Rz=KPEQnLJMZt_e314P0jaT_oJ9MR8A@mail.gmail.com
If there were multiple grouping sets, none of them empty, all of which
were unsortable, then an oversight in consider_groupingsets_paths led
to a null pointer dereference. Fix, and add a regression test for this
case.
Per report from Dang Minh Huong, though I didn't use their patch.
Backpatch to 10.x where hashed grouping sets were added.
This avoids unnecessarily creating a RelOptInfo for which we have no
actual need. This idea is from Ashutosh Bapat, who wrote a very
different patch to accomplish a similar goal. It will be more
important if and when we get partition-wise aggregate, since then
there could be many partially grouped relations all of which could
potentially be unnecessary. In passing, this sets the grouping
relation's reltarget, which wasn't done previously but makes things
simpler for this refactoring.
Along the way, adjust things so that add_paths_to_partial_grouping_rel,
now renamed create_partial_grouping_paths, does not perform the Gather
or Gather Merge steps to generate non-partial paths from partial
paths; have the caller do it instead. This is again for the
convenience of partition-wise aggregate, which wants to inject
additional partial paths are created and before we decide which ones
to Gather/Gather Merge. This might seem like a separate change, but
it's actually pretty closely entangled; I couldn't really see much
value in separating it and having to change some things twice.
Patch by me, reviewed by Ashutosh Bapat.
Discussion: http://postgr.es/m/CA+TgmoZ+ZJTVad-=vEq393N99KTooxv9k7M+z73qnTAqkb49BQ@mail.gmail.com
There's no functional change here, or at least I hope there isn't,
just code rearrangement. The rearrangement is motivated by
partition-wise aggregate, which doesn't need to consider the
degenerate case but wants to reuse the logic for the ordinary case.
Based loosely on a patch from Ashutosh Bapat and Jeevan Chalke, but I
whacked it around pretty heavily. The larger patch series of which
this patch is a part was also reviewed and tested by Antonin Houska,
Rajkumar Raghuwanshi, David Rowley, Dilip Kumar, Konstantin Knizhnik,
Pascal Legrand, Rafia Sabih, and me.
Discussion: http://postgr.es/m/CAFjFpRewpqCmVkwvq6qrRjmbMDpN0CZvRRzjd8UvncczA3Oz1Q@mail.gmail.com
get_number_of_groups() and make_partial_grouping_target() currently
fish information directly out of the PlannerInfo; in the former case,
the target list, and in the latter case, the HAVING qual. This works
fine if there's only one grouping relation, but if the pending patch
for partition-wise aggregate gets committed, we'll have multiple
grouping relations and must therefore use appropriately translated
versions of these values for each one. To make that simpler, pass the
values to be used as arguments.
Jeevan Chalke. The larger patch series of which this patch is a part
was also reviewed and tested by Antonin Houska, Rajkumar Raghuwanshi,
David Rowley, Dilip Kumar, Konstantin Knizhnik, Pascal Legrand, Rafia
Sabih, and me.
Discussion: http://postgr.es/m/CAM2+6=UqFnFUypOvLdm5TgC+2M=-E0Q7_LOh0VDFFzmk2BBPzQ@mail.gmail.com
Discussion: http://postgr.es/m/CAM2+6=W+L=C4yBqMrgrfTfNtbtmr4T53-hZhwbA2kvbZ9VMrrw@mail.gmail.com
In b5635948ab, a couple of function header comments weren't changed, or
weren't changed correctly, to reflect the arguments being passed into
the functions. Specifically, get_number_of_groups() had the wrong
argument name in the commit and create_grouping_paths() wasn't
updated even though the arguments had been changed.
The issue with create_grouping_paths() was noticed by Ashutosh Bapat,
while I discovered the issue with get_number_of_groups() by looking to
see if there were any similar issues from that commit.
Discussion: https://postgr.es/m/CAFjFpRcbp4702jcp387PExt3fNCt62QJN8++DQGwBhsW6wRHWA@mail.gmail.com
A simple UNION ALL gets flattened into an appendrel of subquery
RTEs, but up until now it's been impossible for the appendrel to use
the partial paths for the subqueries, so we can implement the
appendrel as a Parallel Append but only one with non-partial paths
as children.
There are three separate obstacles to removing that limitation.
First, when planning a subquery, propagate any partial paths to the
final_rel so that they are potentially visible to outer query levels
(but not if they have initPlans attached, because that wouldn't be
safe). Second, after planning a subquery, propagate any partial paths
for the final_rel to the subquery RTE in the outer query level in the
same way we do for non-partial paths. Third, teach finalize_plan() to
account for the possibility that the fake parameter we use for rescan
signalling when the plan contains a Gather (Merge) node may be
propagated from an outer query level.
Patch by me, reviewed and tested by Amit Khandekar, Rajkumar
Raghuwanshi, and Ashutosh Bapat. Test cases based on examples by
Rajkumar Raghuwanshi.
Discussion: http://postgr.es/m/CA+Tgmoa6L9A1nNCk3aTDVZLZ4KkHDn1+tm7mFyFvP+uQPS7bAg@mail.gmail.com
One of the things canonicalize_qual() does is to remove constant-NULL
subexpressions of top-level AND/OR clauses. It does that on the assumption
that what it's given is a top-level WHERE clause, so that NULL can be
treated like FALSE. Although this is documented down inside a subroutine
of canonicalize_qual(), it wasn't mentioned in the documentation of that
function itself, and some callers hadn't gotten that memo.
Notably, commit d007a9505 caused get_relation_constraints() to apply
canonicalize_qual() to CHECK constraints. That allowed constraint
exclusion to misoptimize situations in which a CHECK constraint had a
provably-NULL subclause, as seen in the regression test case added here,
in which a child table that should be scanned is not. (Although this
thinko is ancient, the test case doesn't fail before 9.2, for reasons
I've not bothered to track down in detail. There may be related cases
that do fail before that.)
More recently, commit f0e44751d added an independent bug by applying
canonicalize_qual() to index expressions, which is even sillier since
those might not even be boolean. If they are, though, I think this
could lead to making incorrect index entries for affected index
expressions in v10. I haven't attempted to prove that though.
To fix, add an "is_check" parameter to canonicalize_qual() to specify
whether it should assume WHERE or CHECK semantics, and make it perform
NULL-elimination accordingly. Adjust the callers to apply the right
semantics, or remove the call entirely in cases where it's not known
that the expression has one or the other semantics. I also removed
the call in some cases involving partition expressions, where it should
be a no-op because such expressions should be canonical already ...
and was a no-op, independently of whether it could in principle have
done something, because it was being handed the qual in implicit-AND
format which isn't what it expects. In HEAD, add an Assert to catch
that type of mistake in future.
This represents an API break for external callers of canonicalize_qual().
While that's intentional in HEAD to make such callers think about which
case applies to them, it seems like something we probably wouldn't be
thanked for in released branches. Hence, in released branches, the
extra parameter is added to a new function canonicalize_qual_ext(),
and canonicalize_qual() is a wrapper that retains its old behavior.
Patch by me with suggestions from Dean Rasheed. Back-patch to all
supported branches.
Discussion: https://postgr.es/m/24475.1520635069@sss.pgh.pa.us
Since commit 69f4b9c85f, the existing
code was no longer assessing the parallel-safety of the real tlist
for each upper rel, but rather the first of possibly several tlists
created by split_pathtarget_at_srfs(). Repair.
Even though this is clearly wrong, it's not clear that it has any
user-visible consequences at the moment, so no back-patch for now. If
we discover later that it does have user-visible consequences, we
might need to back-patch this to v10.
Patch by me, per a report from Rajkumar Raghuwanshi.
Discussion: http://postgr.es/m/CA+Tgmoaob_Strkg4Dcx=VyxnyXtrmkV=ofj=pX7gH9hSre-g0Q@mail.gmail.com
Commit 3bf05e096b sometimes uses the
cheapest_partial_path variable in this function to mean the cheapest
one from the input rel and at other times the cheapest one from the
partially grouped rel, but it never resets it, so we can end up with
bad plans, leading to "ERROR: Aggref found in non-Agg plan node".
Jeevan Chalke, per a report from Andreas Joseph Krogh and a separate
off-list report from Rajkumar Raghuwanshi
Discussion: http://postgr.es/m/CAM2+6=X9kxQoL2ZqZ00E6asBt9z+rfyWbOmhXJ0+8fPAyMZ9Jg@mail.gmail.com
Up until now, we've abused grouped_rel->partial_pathlist as a place to
store partial paths that have been partially aggregate, but that's
really not correct, because a partial path for a relation is supposed
to be one which produces the correct results with the addition of only
a Gather or Gather Merge node, and these paths also require a Finalize
Aggregate step. Instead, add a new partially_group_rel which can hold
either partial paths (which need to be gathered and then have
aggregation finalized) or non-partial paths (which only need to have
aggregation finalized). This allows us to reuse generate_gather_paths
for partially_grouped_rel instead of writing new code, so that this
patch actually basically no net new code while making things cleaner,
simplifying things for pending patches for partition-wise aggregate.
Robert Haas and Jeevan Chalke. The larger patch series of which this
patch is a part was also reviewed and tested by Antonin Houska,
Rajkumar Raghuwanshi, David Rowley, Dilip Kumar, Konstantin Knizhnik,
Pascal Legrand, Rafia Sabih, and me.
Discussion: http://postgr.es/m/CA+TgmobrzFYS3+U8a_BCy3-hOvh5UyJbC18rEcYehxhpw5=ETA@mail.gmail.com
Discussion: http://postgr.es/m/CA+TgmoZyQEjdBNuoG9-wC5GQ5GrO4544Myo13dVptvx+uLg9uQ@mail.gmail.com
Given overlapping or partially redundant join clauses, for example
t1 JOIN t2 ON t1.a = t2.x AND t1.b = t2.x
the planner's EquivalenceClass machinery will ordinarily refactor the
clauses as "t1.a = t1.b AND t1.a = t2.x", so that join processing doesn't
see multiple references to the same EquivalenceClass in a list of join
equality clauses. However, if the join is outer, it's incorrect to derive
a restriction clause on the outer side from the join conditions, so the
clause refactoring does not happen and we end up with overlapping join
conditions. The code that attempted to deal with such cases had several
subtle bugs, which could result in "left and right pathkeys do not match in
mergejoin" or "outer pathkeys do not match mergeclauses" planner errors,
if the selected join plan type was a mergejoin. (It does not appear that
any actually incorrect plan could have been emitted.)
The core of the problem really was failure to recognize that the outer and
inner relations' pathkeys have different relationships to the mergeclause
list. A join's mergeclause list is constructed by reference to the outer
pathkeys, so it will always be ordered the same as the outer pathkeys, but
this cannot be presumed true for the inner pathkeys. If the inner sides of
the mergeclauses contain multiple references to the same EquivalenceClass
({t2.x} in the above example) then a simplistic rendering of the required
inner sort order is like "ORDER BY t2.x, t2.x", but the pathkey machinery
recognizes that the second sort column is redundant and throws it away.
The mergejoin planning code failed to account for that behavior properly.
One error was to try to generate cut-down versions of the mergeclause list
from cut-down versions of the inner pathkeys in the same way as the initial
construction of the mergeclause list from the outer pathkeys was done; this
could lead to choosing a mergeclause list that fails to match the outer
pathkeys. The other problem was that the pathkey cross-checking code in
create_mergejoin_plan treated the inner and outer pathkey lists
identically, whereas actually the expectations for them must be different.
That led to false "pathkeys do not match" failures in some cases, and in
principle could have led to failure to detect bogus plans in other cases,
though there is no indication that such bogus plans could be generated.
Reported by Alexander Kuzmenkov, who also reviewed this patch. This has
been broken for years (back to around 8.3 according to my testing), so
back-patch to all supported branches.
Discussion: https://postgr.es/m/5dad9160-4632-0e47-e120-8e2082000c01@postgrespro.ru
The previous code failed to realize that this setting effectively
disables parallelism, and would crash if it decided to attempt
parallelism anyway. Instead, treat it as a disabling condition.
Kyotaro Horiguchi, who also reported the issue. Reviewed by Michael
Paquier and Peter Geoghegan.
Discussion: http://postgr.es/m/20180209.170635.256350357.horiguchi.kyotaro@lab.ntt.co.jp
This patch adds the ability to use "RANGE offset PRECEDING/FOLLOWING"
frame boundaries in window functions. We'd punted on that back in the
original patch to add window functions, because it was not clear how to
do it in a reasonably data-type-extensible fashion. That problem is
resolved here by adding the ability for btree operator classes to provide
an "in_range" support function that defines how to add or subtract the
RANGE offset value. Factoring it this way also allows the operator class
to avoid overflow problems near the ends of the datatype's range, if it
wishes to expend effort on that. (In the committed patch, the integer
opclasses handle that issue, but it did not seem worth the trouble to
avoid overflow failures for datetime types.)
The patch includes in_range support for the integer_ops opfamily
(int2/int4/int8) as well as the standard datetime types. Support for
other numeric types has been requested, but that seems like suitable
material for a follow-on patch.
In addition, the patch adds GROUPS mode which counts the offset in
ORDER-BY peer groups rather than rows, and it adds the frame_exclusion
options specified by SQL:2011. As far as I can see, we are now fully
up to spec on window framing options.
Existing behaviors remain unchanged, except that I changed the errcode
for a couple of existing error reports to meet the SQL spec's expectation
that negative "offset" values should be reported as SQLSTATE 22013.
Internally and in relevant parts of the documentation, we now consistently
use the terminology "offset PRECEDING/FOLLOWING" rather than "value
PRECEDING/FOLLOWING", since the term "value" is confusingly vague.
Oliver Ford, reviewed and whacked around some by me
Discussion: https://postgr.es/m/CAGMVOdu9sivPAxbNN0X+q19Sfv9edEPv=HibOJhB14TJv_RCQg@mail.gmail.com
To make this work, tuplesort.c and logtape.c must also support
parallelism, so this patch adds that infrastructure and then applies
it to the particular case of parallel btree index builds. Testing
to date shows that this can often be 2-3x faster than a serial
index build.
The model for deciding how many workers to use is fairly primitive
at present, but it's better than not having the feature. We can
refine it as we get more experience.
Peter Geoghegan with some help from Rushabh Lathia. While Heikki
Linnakangas is not an author of this patch, he wrote other patches
without which this feature would not have been possible, and
therefore the release notes should possibly credit him as an author
of this feature. Reviewed by Claudio Freire, Heikki Linnakangas,
Thomas Munro, Tels, Amit Kapila, me.
Discussion: http://postgr.es/m/CAM3SWZQKM=Pzc=CAHzRixKjp2eO5Q0Jg1SoFQqeXFQ647JiwqQ@mail.gmail.com
Discussion: http://postgr.es/m/CAH2-Wz=AxWqDoVvGU7dq856S4r6sJAj6DBn7VMtigkB33N5eyg@mail.gmail.com
create_plan_recurse lacked any stack depth check. This is not per
our normal coding rules, but I'd supposed it was safe because earlier
planner processing is more complex and presumably should eat more
stack. But bug #15033 from Andrew Grossman shows this isn't true,
at least not for queries having the form of a many-thousand-way
INTERSECT stack.
Further testing showed that recurse_set_operations is also capable
of being crashed in this way, since it likewise will recurse to the
bottom of a parsetree before calling any support functions that
might themselves contain any stack checks. However, its stack
consumption is only perhaps a third of create_plan_recurse's.
It's possible that this particular problem with create_plan_recurse can
only manifest in 9.6 and later, since before that we didn't build a Path
tree for set operations. But having seen this example, I now have no
faith in the proposition that create_plan_recurse doesn't need a stack
check, so back-patch to all supported branches.
Discussion: https://postgr.es/m/20180127050845.28812.58244@wrigleys.postgresql.org
This is preparatory refactoring to prepare the way for partition-wise
aggregate, which will reuse the new subroutines for child grouping
rels. It also does not seem like a bad idea on general principle,
as the function was getting pretty long.
Jeevan Chalke. The larger patch series of which this patch is a part
was reviewed and tested by Antonin Houska, Rajkumar Raghuwanshi,
Ashutosh Bapat, David Rowley, Dilip Kumar, Konstantin Knizhnik,
Pascal Legrand, and me. Some cosmetic changes by me.
Discussion: http://postgr.es/m/CAM2+6=V64_xhstVHie0Rz=KPEQnLJMZt_e314P0jaT_oJ9MR8A@mail.gmail.com
When an UPDATE causes a row to no longer match the partition
constraint, try to move it to a different partition where it does
match the partition constraint. In essence, the UPDATE is split into
a DELETE from the old partition and an INSERT into the new one. This
can lead to surprising behavior in concurrency scenarios because
EvalPlanQual rechecks won't work as they normally did; the known
problems are documented. (There is a pending patch to improve the
situation further, but it needs more review.)
Amit Khandekar, reviewed and tested by Amit Langote, David Rowley,
Rajkumar Raghuwanshi, Dilip Kumar, Amul Sul, Thomas Munro, Álvaro
Herrera, Amit Kapila, and me. A few final revisions by me.
Discussion: http://postgr.es/m/CAJ3gD9do9o2ccQ7j7+tSgiE1REY65XRiMb=yJO3u3QhyP8EEPQ@mail.gmail.com
Since 9.4, we've allowed the syntax "select union select" and variants
of that. However, the planner wasn't expecting a no-column set operation
and ended up treating the set operation as if it were UNION ALL.
Turns out it's trivial to fix in v10 and later; we just need to be careful
about not generating a Sort node with no sort keys. However, since a weird
corner case like this is never going to be exercised by developers, we'd
better have thorough regression tests if we want to consider it supported.
Per report from Victor Yegorov.
Discussion: https://postgr.es/m/CAGnEbojGJrRSOgJwNGM7JSJZpVAf8xXcVPbVrGdhbVEHZ-BUMw@mail.gmail.com
Introduce parallel-aware hash joins that appear in EXPLAIN plans as Parallel
Hash Join with Parallel Hash. While hash joins could already appear in
parallel queries, they were previously always parallel-oblivious and had a
partial subplan only on the outer side, meaning that the work of the inner
subplan was duplicated in every worker.
After this commit, the planner will consider using a partial subplan on the
inner side too, using the Parallel Hash node to divide the work over the
available CPU cores and combine its results in shared memory. If the join
needs to be split into multiple batches in order to respect work_mem, then
workers process different batches as much as possible and then work together
on the remaining batches.
The advantages of a parallel-aware hash join over a parallel-oblivious hash
join used in a parallel query are that it:
* avoids wasting memory on duplicated hash tables
* avoids wasting disk space on duplicated batch files
* divides the work of building the hash table over the CPUs
One disadvantage is that there is some communication between the participating
CPUs which might outweigh the benefits of parallelism in the case of small
hash tables. This is avoided by the planner's existing reluctance to supply
partial plans for small scans, but it may be necessary to estimate
synchronization costs in future if that situation changes. Another is that
outer batch 0 must be written to disk if multiple batches are required.
A potential future advantage of parallel-aware hash joins is that right and
full outer joins could be supported, since there is a single set of matched
bits for each hashtable, but that is not yet implemented.
A new GUC enable_parallel_hash is defined to control the feature, defaulting
to on.
Author: Thomas Munro
Reviewed-By: Andres Freund, Robert Haas
Tested-By: Rafia Sabih, Prabhat Sahu
Discussion:
https://postgr.es/m/CAEepm=2W=cOkiZxcg6qiFQP-dHUe09aqTrEMM7yJDrHMhDv_RA@mail.gmail.comhttps://postgr.es/m/CAEepm=37HKyJ4U6XOLi=JgfSHM3o6B-GaeO-6hkOmneTDkH+Uw@mail.gmail.com
Commit dc02c7bca4 changed this call
to create_sort_path() to take -1 rather than limit_tuples because,
at that time, there was no way for a Sort beneath a Gather Merge
to become a top-N sort.
Later, commit 3452dc5240 provided
a way for a Sort beneath a Gather Merge to become a top-N sort,
but failed to revert the previous commit in the process. Do that.
Report and analysis by Jeff Janes; patch by Thomas Munro; review by
Amit Kapila and by me.
Discussion: http://postgr.es/m/CAEepm=1BWtC34vUroA0Uqjw02MaqdUrW+d6WD85_k8SLyPiKHQ@mail.gmail.com
When we create an Append node, we can spread out the workers over the
subplans instead of piling on to each subplan one at a time, which
should typically be a bit more efficient, both because the startup
cost of any plan executed entirely by one worker is paid only once and
also because of reduced contention. We can also construct Append
plans using a mix of partial and non-partial subplans, which may allow
for parallelism in places that otherwise couldn't support it.
Unfortunately, this patch doesn't handle the important case of
parallelizing UNION ALL by running each branch in a separate worker;
the executor infrastructure is added here, but more planner work is
needed.
Amit Khandekar, Robert Haas, Amul Sul, reviewed and tested by
Ashutosh Bapat, Amit Langote, Rafia Sabih, Amit Kapila, and
Rajkumar Raghuwanshi.
Discussion: http://postgr.es/m/CAJ3gD9dy0K_E8r727heqXoBmWZ83HwLFwdcaSSmBQ1+S+vRuUQ@mail.gmail.com
rewriteTargetListUD's processing is dependent on the relkind of the query's
target table. That was fine at the time it was made to act that way, even
for queries on inheritance trees, because all tables in an inheritance tree
would necessarily be plain tables. However, the 9.5 feature addition
allowing some members of an inheritance tree to be foreign tables broke the
assumption that rewriteTargetListUD's output tlist could be applied to all
child tables with nothing more than column-number mapping. This led to
visible failures if foreign child tables had row-level triggers, and would
also break in cases where child tables belonged to FDWs that used methods
other than CTID for row identification.
To fix, delay running rewriteTargetListUD until after the planner has
expanded inheritance, so that it is applied separately to the (already
mapped) tlist for each child table. We can conveniently call it from
preprocess_targetlist. Refactor associated code slightly to avoid the
need to heap_open the target relation multiple times during
preprocess_targetlist. (The APIs remain a bit ugly, particularly around
the point of which steps scribble on parse->targetList and which don't.
But avoiding such scribbling would require a change in FDW callback APIs,
which is more pain than it's worth.)
Also fix ExecModifyTable to ensure that "tupleid" is reset to NULL when
we transition from rows providing a CTID to rows that don't. (That's
really an independent bug, but it manifests in much the same cases.)
Add a regression test checking one manifestation of this problem, which
was that row-level triggers on a foreign child table did not work right.
Back-patch to 9.5 where the problem was introduced.
Etsuro Fujita, reviewed by Ildus Kurbangaliev and Ashutosh Bapat
Discussion: https://postgr.es/m/20170514150525.0346ba72@postgrespro.ru
Improve query_is_distinct_for() to accept SRFs in the targetlist when
we can prove distinctness from a DISTINCT clause. In that case the
de-duplication will surely happen after SRF expansion, so the proof
still works. Continue to punt in the case where we'd try to prove
distinctness from GROUP BY (or, in the future, source relations).
To do that, we'd have to determine whether the SRFs were in the
grouping columns or elsewhere in the tlist, and it still doesn't
seem worth the trouble. But this trivial change allows us to
recognize that "SELECT DISTINCT unnest(foo) FROM ..." produces
unique-ified output, which seems worth having.
Also, fix estimate_num_groups() to consider the possibility of SRFs in
the grouping columns. Its failure to do so was masked before v10 because
grouping_planner() scaled up plan rowcount estimates by the estimated SRF
multiplier after performing grouping. That doesn't happen anymore, which
is more correct, but it means we need an adjustment in the estimate for
the number of groups. Failure to do this leads to an underestimate for
the number of output rows of subqueries like "SELECT DISTINCT unnest(foo)"
compared to what 9.6 and earlier estimated, thus breaking plan choices
in some cases.
Per report from Dmitry Shalashov. Back-patch to v10 to avoid degraded
plan choices compared to previous releases.
Discussion: https://postgr.es/m/CAKPeCUGAeHgoh5O=SvcQxREVkoX7UdeJUMj1F5=aBNvoTa+O8w@mail.gmail.com
If a PARAM_EXEC parameter is used below a Gather (Merge) but the InitPlan
that computes it is attached to or above the Gather (Merge), force the
value to be computed before starting parallelism and pass it down to all
workers. This allows us to use parallelism in cases where it previously
would have had to be rejected as unsafe. We do - in this case - lose the
optimization that the value is only computed if it's actually used. An
alternative strategy would be to have the first worker that needs the value
compute it, but one downside of that approach is that we'd then need to
select a parallel-safe path to compute the parameter value; it couldn't for
example contain a Gather (Merge) node. At some point in the future, we
might want to consider both approaches.
Independent of that consideration, there is a great deal more work that
could be done to make more kinds of PARAM_EXEC parameters parallel-safe.
This infrastructure could be used to allow a Gather (Merge) on the inner
side of a nested loop (although that's not a very appealing plan) and
cases where the InitPlan is attached below the Gather (Merge) could be
addressed as well using various techniques. But this is a good start.
Amit Kapila, reviewed and revised by me. Reviewing and testing from
Kuntal Ghosh, Haribabu Kommi, and Tushar Ahuja.
Discussion: http://postgr.es/m/CAA4eK1LV0Y1AUV4cUCdC+sYOx0Z0-8NAJ2Pd9=UKsbQ5Sr7+JQ@mail.gmail.com
