Create an array estate->es_relations[] paralleling the es_range_table,
and store references to Relations (relcache entries) there, so that any
given RT entry is opened and closed just once per executor run. Scan
nodes typically still call ExecOpenScanRelation, but ExecCloseScanRelation
is no more; relation closing is now done centrally in ExecEndPlan.
This is slightly more complex than one would expect because of the
interactions with relcache references held in ResultRelInfo nodes.
The general convention is now that ResultRelInfo->ri_RelationDesc does
not represent a separate relcache reference and so does not need to be
explicitly closed; but there is an exception for ResultRelInfos in the
es_trig_target_relations list, which are manufactured by
ExecGetTriggerResultRel and have to be cleaned up by
ExecCleanUpTriggerState. (That much was true all along, but these
ResultRelInfos are now more different from others than they used to be.)
To allow the partition pruning logic to make use of es_relations[] rather
than having its own relcache references, adjust PartitionedRelPruneInfo
to store an RT index rather than a relation OID.
Amit Langote, reviewed by David Rowley and Jesper Pedersen,
some mods by me
Discussion: https://postgr.es/m/468c85d9-540e-66a2-1dde-fec2b741e688@lab.ntt.co.jp
Add RangeTblEntry.rellockmode, which records the appropriate lock mode for
each RTE_RELATION rangetable entry (either AccessShareLock, RowShareLock,
or RowExclusiveLock depending on the RTE's role in the query).
This patch creates the field and makes all creators of RTE nodes fill it
in reasonably, but for the moment nothing much is done with it. The plan
is to replace assorted post-parser logic that re-determines the right
lockmode to use with simple uses of rte->rellockmode. For now, just add
Asserts in each of those places that the rellockmode matches what they are
computing today. (In some cases the match isn't perfect, so the Asserts
are weaker than you might expect; but this seems OK, as per discussion.)
This passes check-world for me, but it seems worth pushing in this state
to see if the buildfarm finds any problems in cases I failed to test.
catversion bump due to change of stored rules.
Amit Langote, reviewed by David Rowley and Jesper Pedersen,
and whacked around a bit more by me
Discussion: https://postgr.es/m/468c85d9-540e-66a2-1dde-fec2b741e688@lab.ntt.co.jp
A test patch to pass parse and plan trees through outfuncs + readfuncs
exposed several issues that need to be fixed to get clean matches:
Query.withCheckOptions failed to get copied; it's intentionally ignored
by outfuncs/readfuncs on the grounds that it'd always be NIL anyway in
stored rules. This seems less than future-proof, and it's not even
saving very much, so just undo the decision and treat the field like
all others.
Several places that convert a view RTE into a subquery RTE, or similar
manipulations, failed to clear out fields that were specific to the
original RTE type and should be zero in a subquery RTE. Since readfuncs.c
will leave such fields as zero, equalfuncs.c thinks the nodes are different
leading to a reported mismatch. It seems like a good idea to clear out the
no-longer-needed fields, even though in principle nothing should look at
them; the node ought to be indistinguishable from how it would look if
we'd built a new node instead of scribbling on the old one.
BuildOnConflictExcludedTargetlist randomly set the resname of some
TargetEntries to "" not NULL. outfuncs/readfuncs don't distinguish those
cases, and so the string will read back in as NULL ... but equalfuncs.c
does distinguish. Perhaps we ought to try to make things more consistent
in this area --- but it's just useless extra code space for
BuildOnConflictExcludedTargetlist to not use NULL here, so I fixed it for
now by making it do that.
catversion bumped because the change in handling of Query.withCheckOptions
affects stored rules.
Discussion: https://postgr.es/m/17114.1537138992@sss.pgh.pa.us
I noticed while poking at a report from Andrey Lepikhov that the
recent addition of RawStmt nodes at the top of raw parse trees
makes it impossible to print any raw parse trees whatsoever,
because outfuncs.c doesn't know RawStmt and hence fails to descend
into it.
While we generally lack outfuncs.c support for utility statements,
there is reasonably complete support for what you can find in a
raw SELECT statement. It was not my intention to make that all
dead code ... so let's add support for RawStmt.
Back-patch to v10 where RawStmt appeared.
Commit f49842d, which added support for partitionwise joins, built the
child's tlist by applying adjust_appendrel_attrs() to the parent's. So in
the case where the parent's included a whole-row Var for the parent, the
child's contained a ConvertRowtypeExpr. To cope with that, that commit
added code to the planner, such as setrefs.c, but some code paths still
assumed that the tlist for a scan (or join) rel would only include Vars
and PlaceHolderVars, which was true before that commit, causing errors:
* When creating an explicit sort node for an input path for a mergejoin
path for a child join, prepare_sort_from_pathkeys() threw the 'could not
find pathkey item to sort' error.
* When deparsing a relation participating in a pushed down child join as a
subquery in contrib/postgres_fdw, get_relation_column_alias_ids() threw
the 'unexpected expression in subquery output' error.
* When performing set_plan_references() on a local join plan generated by
contrib/postgres_fdw for EvalPlanQual support for a pushed down child
join, fix_join_expr() threw the 'variable not found in subplan target
lists' error.
To fix these, two approaches have been proposed: one by Ashutosh Bapat and
one by me. While the former keeps building the child's tlist with a
ConvertRowtypeExpr, the latter builds it with a whole-row Var for the
child not to violate the planner assumption, and tries to fix it up later,
But both approaches need more work, so refuse to generate partitionwise
join paths when whole-row Vars are involved, instead. We don't need to
handle ConvertRowtypeExprs in the child's tlists for now, so this commit
also removes the changes to the planner.
Previously, partitionwise join computed attr_needed data for each child
separately, and built the child join's tlist using that data, which also
required an extra step for adding PlaceHolderVars to that tlist, but it
would be more efficient to build it from the parent join's tlist through
the adjust_appendrel_attrs() transformation. So this commit builds that
list that way, and simplifies build_joinrel_tlist() and placeholder.c as
well as part of set_append_rel_size() to basically what they were before
partitionwise join went in.
Back-patch to PG11 where partitionwise join was introduced.
Report by Rajkumar Raghuwanshi. Analysis by Ashutosh Bapat, who also
provided some of regression tests. Patch by me, reviewed by Robert Haas.
Discussion: https://postgr.es/m/CAKcux6ktu-8tefLWtQuuZBYFaZA83vUzuRd7c1YHC-yEWyYFpg@mail.gmail.com
The previous coding here supposed that if run-time partitioning applied to
a particular Append/MergeAppend plan, then all child plans of that node
must be members of a single partitioning hierarchy. This is totally wrong,
since an Append could be formed from a UNION ALL: we could have multiple
hierarchies sharing the same Append, or child plans that aren't part of any
hierarchy.
To fix, restructure the related plan-time and execution-time data
structures so that we can have a separate list or array for each
partitioning hierarchy. Also track subplans that are not part of any
hierarchy, and make sure they don't get pruned.
Per reports from Phil Florent and others. Back-patch to v11, since
the bug originated there.
David Rowley, with a lot of cosmetic adjustments by me; thanks also
to Amit Langote for review.
Discussion: https://postgr.es/m/HE1PR03MB17068BB27404C90B5B788BCABA7B0@HE1PR03MB1706.eurprd03.prod.outlook.com
nodeWindowAgg.c failed to cope with the possibility that no ordering
columns are defined in the window frame for GROUPS mode or RANGE OFFSET
mode, leading to assertion failures or odd errors, as reported by Masahiko
Sawada and Lukas Eder. In RANGE OFFSET mode, an ordering column is really
required, so add an Assert about that. In GROUPS mode, the code would
work, except that the node initialization code wasn't in sync with the
execution code about when to set up tuplestore read pointers and spare
slots. Fix the latter for consistency's sake (even though I think the
changes described below make the out-of-sync cases unreachable for now).
Per SQL spec, a single ordering column is required for RANGE OFFSET mode,
and at least one ordering column is required for GROUPS mode. The parser
enforced the former but not the latter; add a check for that.
We were able to reach the no-ordering-column cases even with fully spec
compliant queries, though, because the planner would drop partitioning
and ordering columns from the generated plan if they were redundant with
earlier columns according to the redundant-pathkey logic, for instance
"PARTITION BY x ORDER BY y" in the presence of a "WHERE x=y" qual.
While in principle that's an optimization that could save some pointless
comparisons at runtime, it seems unlikely to be meaningful in the real
world. I think this behavior was not so much an intentional optimization
as a side-effect of an ancient decision to construct the plan node's
ordering-column info by reverse-engineering the PathKeys of the input
path. If we give up redundant-column removal then it takes very little
code to generate the plan node info directly from the WindowClause,
ensuring that we have the expected number of ordering columns in all
cases. (If anyone does complain about this, the planner could perhaps
be taught to remove redundant columns only when it's safe to do so,
ie *not* in RANGE OFFSET mode. But I doubt anyone ever will.)
With these changes, the WindowAggPath.winpathkeys field is not used for
anything anymore, so remove it.
The test cases added here are not actually very interesting given the
removal of the redundant-column-removal logic, but they would represent
important corner cases if anyone ever tries to put that back.
Tom Lane and Masahiko Sawada. Back-patch to v11 where RANGE OFFSET
and GROUPS modes were added.
Discussion: https://postgr.es/m/CAD21AoDrWqycq-w_+Bx1cjc+YUhZ11XTj9rfxNiNDojjBx8Fjw@mail.gmail.com
Discussion: https://postgr.es/m/153086788677.17476.8002640580496698831@wrigleys.postgresql.org
These struct definitions were originally dropped into primnodes.h,
which is a poor choice since that's mainly intended for primitive
expression node types; these are not in that category. What they
are is auxiliary info in Plan trees, so move them to plannodes.h.
For consistency, also relocate some related code that was apparently
placed with the aid of a dartboard.
There's no interesting code changes in this commit, just reshuffling.
David Rowley and Tom Lane
Discussion: https://postgr.es/m/CAFj8pRBjrufA3ocDm8o4LPGNye9Y+pm1b9kCwode4X04CULG3g@mail.gmail.com
The initial coding of the run-time-pruning feature only coped with cases
where the partition key(s) are compared to Params. That is a bit silly;
we can allow it to work with any non-Var-containing stable expression, as
long as we take special care with expressions containing PARAM_EXEC Params.
The code is hardly any longer this way, and it's considerably clearer
(IMO at least). Per gripe from Pavel Stehule.
David Rowley, whacked around a bit by me
Discussion: https://postgr.es/m/CAFj8pRBjrufA3ocDm8o4LPGNye9Y+pm1b9kCwode4X04CULG3g@mail.gmail.com
This controls both plan-time and execution-time new-style partition
pruning. While finer-grain control is possible (maybe using an enum GUC
instead of boolean), there doesn't seem to be much need for that.
This new parameter controls partition pruning for all queries:
trivially, SELECT queries that affect partitioned tables are naturally
under its control since they are using the new technology. However,
while UPDATE/DELETE queries do not use the new code, we make the new GUC
control their behavior also (stealing control from
constraint_exclusion), because it is more natural, and it leads to a
more natural transition to the future in which those queries will also
use the new pruning code.
Constraint exclusion still controls pruning for regular inheritance
situations (those not involving partitioned tables).
Author: David Rowley
Review: Amit Langote, Ashutosh Bapat, Justin Pryzby, David G. Johnston
Discussion: https://postgr.es/m/CAKJS1f_0HwsxJG9m+nzU+CizxSdGtfe6iF_ykPYBiYft302DCw@mail.gmail.com
This reverts commits d204ef63776b8a00ca220adec23979091564e465,
83454e3c2b28141c0db01c7d2027e01040df5249 and a few more commits thereafter
(complete list at the end) related to MERGE feature.
While the feature was fully functional, with sufficient test coverage and
necessary documentation, it was felt that some parts of the executor and
parse-analyzer can use a different design and it wasn't possible to do that in
the available time. So it was decided to revert the patch for PG11 and retry
again in the future.
Thanks again to all reviewers and bug reporters.
List of commits reverted, in reverse chronological order:
f1464c5380 Improve parse representation for MERGE
ddb4158579 MERGE syntax diagram correction
530e69e59b Allow cpluspluscheck to pass by renaming variable
01b88b4df5 MERGE minor errata
3af7b2b0d4 MERGE fix variable warning in non-assert builds
a5d86181ec MERGE INSERT allows only one VALUES clause
4b2d44031f MERGE post-commit review
4923550c20 Tab completion for MERGE
aa3faa3c7a WITH support in MERGE
83454e3c2b New files for MERGE
d204ef6377 MERGE SQL Command following SQL:2016
Author: Pavan Deolasee
Reviewed-by: Michael Paquier
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
This patch introduces INCLUDE clause to index definition. This clause
specifies a list of columns which will be included as a non-key part in
the index. The INCLUDE columns exist solely to allow more queries to
benefit from index-only scans. Also, such columns don't need to have
appropriate operator classes. Expressions are not supported as INCLUDE
columns since they cannot be used in index-only scans.
Index access methods supporting INCLUDE are indicated by amcaninclude flag
in IndexAmRoutine. For now, only B-tree indexes support INCLUDE clause.
In B-tree indexes INCLUDE columns are truncated from pivot index tuples
(tuples located in non-leaf pages and high keys). Therefore, B-tree indexes
now might have variable number of attributes. This patch also provides
generic facility to support that: pivot tuples contain number of their
attributes in t_tid.ip_posid. Free 13th bit of t_info is used for indicating
that. This facility will simplify further support of index suffix truncation.
The changes of above are backward-compatible, pg_upgrade doesn't need special
handling of B-tree indexes for that.
Bump catalog version
Author: Anastasia Lubennikova with contribition by Alexander Korotkov and me
Reviewed by: Peter Geoghegan, Tomas Vondra, Antonin Houska, Jeff Janes,
David Rowley, Alexander Korotkov
Discussion: https://www.postgresql.org/message-id/flat/56168952.4010101@postgrespro.ru
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
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
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
A Value node would store an integer as a long. This causes needless
portability risks, as long can be of varying sizes. Change it to use
int instead. All code using this was already careful to only store
32-bit values anyway.
Reviewed-by: Michael Paquier <michael@paquier.xyz>
The LIKE INCLUDING ALL clause to CREATE TABLE intuitively indicates
cloning of extended statistics on the source table, but it failed to do
so. Patch it up so that it does. Also include an INCLUDING STATISTICS
option to the LIKE clause, so that the behavior can be requested
individually, or excluded individually.
While at it, reorder the INCLUDING options, both in code and in docs, in
alphabetical order which makes more sense than feature-implementation
order that was previously used.
Backpatch this to Postgres 10, where extended statistics were
introduced, because this is seen as an oversight in a fresh feature
which is better to get consistent from the get-go instead of changing
only in pg11.
In pg11, comments on statistics objects are cloned too. In pg10 they
are not, because I (Álvaro) was too coward to change the parse node as
required to support it. Also, in pg10 I chose not to renumber the
parser symbols for the various INCLUDING options in LIKE, for the same
reason. Any corresponding user-visible changes (docs) are backpatched,
though.
Reported-by: Stephen Froehlich
Author: David Rowley
Reviewed-by: Álvaro Herrera, Tomas Vondra
Discussion: https://postgr.es/m/CY1PR0601MB1927315B45667A1B679D0FD5E5EF0@CY1PR0601MB1927.namprd06.prod.outlook.com
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
Investigation of 2d2d06b7e27e3177d5bef0061801c75946871db3 revealed that
identity values were not applied in some further cases, including
logical replication subscribers, VALUES RTEs, and ALTER TABLE ... ADD
COLUMN. To fix all that, apply the identity column expression in
build_column_default() instead of repeating the same logic at each call
site.
For ALTER TABLE ... ADD COLUMN ... IDENTITY, the previous coding
completely ignored that existing rows for the new column should have
values filled in from the identity sequence. The coding using
build_column_default() fails for this because the sequence ownership
isn't registered until after ALTER TABLE, and we can't do it before
because we don't have the column in the catalog yet. So we specially
remember in ColumnDef the sequence name that we decided on and build a
custom NextValueExpr using that.
Reviewed-by: Michael Paquier <michael.paquier@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
When CREATE INDEX is run on a partitioned table, create catalog entries
for an index on the partitioned table (which is just a placeholder since
the table proper has no data of its own), and recurse to create actual
indexes on the existing partitions; create them in future partitions
also.
As a convenience gadget, if the new index definition matches some
existing index in partitions, these are picked up and used instead of
creating new ones. Whichever way these indexes come about, they become
attached to the index on the parent table and are dropped alongside it,
and cannot be dropped on isolation unless they are detached first.
To support pg_dump'ing these indexes, add commands
CREATE INDEX ON ONLY <table>
(which creates the index on the parent partitioned table, without
recursing) and
ALTER INDEX ATTACH PARTITION
(which is used after the indexes have been created individually on each
partition, to attach them to the parent index). These reconstruct prior
database state exactly.
Reviewed-by: (in alphabetical order) Peter Eisentraut, Robert Haas, Amit
Langote, Jesper Pedersen, Simon Riggs, David Rowley
Discussion: https://postgr.es/m/20171113170646.gzweigyrgg6pwsg4@alvherre.pgsql
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
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
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
Up until now, we only tracked the number of parameters, which was
sufficient to allocate an array of Datums of the appropriate size,
but not sufficient to, for example, know how to serialize a Datum
stored in one of those slots. An upcoming patch wants to do that,
so add this tracking to make it possible.
Patch by me, reviewed by Tom Lane and Amit Kapila.
Discussion: http://postgr.es/m/CA+TgmoYqpxDKn8koHdW8BEKk8FMUL0=e8m2Qe=M+r0UBjr3tuQ@mail.gmail.com
Hash partitioning is useful when you want to partition a growing data
set evenly. This can be useful to keep table sizes reasonable, which
makes maintenance operations such as VACUUM faster, or to enable
partition-wise join.
At present, we still depend on constraint exclusion for partitioning
pruning, and the shape of the partition constraints for hash
partitioning is such that that doesn't work. Work is underway to fix
that, which should both improve performance and make partitioning
pruning work with hash partitioning.
Amul Sul, reviewed and tested by Dilip Kumar, Ashutosh Bapat, Yugo
Nagata, Rajkumar Raghuwanshi, Jesper Pedersen, and by me. A few
final tweaks also by me.
Discussion: http://postgr.es/m/CAAJ_b96fhpJAP=ALbETmeLk1Uni_GFZD938zgenhF49qgDTjaQ@mail.gmail.com
This takes advantage of the infrastructure introduced by commit
81c5e46c490e2426db243eada186995da5bb0ba7 to greatly reduce the
likelihood that two different queries will end up with the same query
ID. It's still possible, of course, but whereas before it the chances
of a collision reached 25% around 50,000 queries, it will now take
more than 3 billion queries.
Backward incompatibility: Because the type exposed at the SQL level is
int8, users may now see negative query IDs in the pg_stat_statements
view (and also, query IDs more than 4 billion, which was the old
limit).
Patch by me, reviewed by Michael Paquier and Peter Geoghegan.
Discussion: http://postgr.es/m/CA+TgmobG_Kp4cBKFmsznUAaM1GWW6hhRNiZC0KjRMOOeYnz5Yw@mail.gmail.com
Allowing arrays with a domain type as their element type was left un-done
in the original domain patch, but not for any very good reason. This
omission leads to such surprising results as array_agg() not working on
a domain column, because the parser can't identify a suitable output type
for the polymorphic aggregate.
In order to fix this, first clean up the APIs of coerce_to_domain() and
some internal functions in parse_coerce.c so that we consistently pass
around a CoercionContext along with CoercionForm. Previously, we sometimes
passed an "isExplicit" boolean flag instead, which is strictly less
information; and coerce_to_domain() didn't even get that, but instead had
to reverse-engineer isExplicit from CoercionForm. That's contrary to the
documentation in primnodes.h that says that CoercionForm only affects
display and not semantics. I don't think this change fixes any live bugs,
but it makes things more consistent. The main reason for doing it though
is that now build_coercion_expression() receives ccontext, which it needs
in order to be able to recursively invoke coerce_to_target_type().
Next, reimplement ArrayCoerceExpr so that the node does not directly know
any details of what has to be done to the individual array elements while
performing the array coercion. Instead, the per-element processing is
represented by a sub-expression whose input is a source array element and
whose output is a target array element. This simplifies life in
parse_coerce.c, because it can build that sub-expression by a recursive
invocation of coerce_to_target_type(). The executor now handles the
per-element processing as a compiled expression instead of hard-wired code.
The main advantage of this is that we can use a single ArrayCoerceExpr to
handle as many as three successive steps per element: base type conversion,
typmod coercion, and domain constraint checking. The old code used two
stacked ArrayCoerceExprs to handle type + typmod coercion, which was pretty
inefficient, and adding yet another array deconstruction to do domain
constraint checking seemed very unappetizing.
In the case where we just need a single, very simple coercion function,
doing this straightforwardly leads to a noticeable increase in the
per-array-element runtime cost. Hence, add an additional shortcut evalfunc
in execExprInterp.c that skips unnecessary overhead for that specific form
of expression. The runtime speed of simple cases is within 1% or so of
where it was before, while cases that previously required two levels of
array processing are significantly faster.
Finally, create an implicit array type for every domain type, as we do for
base types, enums, etc. Everything except the array-coercion case seems
to just work without further effort.
Tom Lane, reviewed by Andrew Dunstan
Discussion: https://postgr.es/m/9852.1499791473@sss.pgh.pa.us
The ExecReScan machinery contains various optimizations for postponing
or skipping rescans of plan subtrees; for example a HashAgg node may
conclude that it can re-use the table it built before, instead of
re-reading its input subtree. But that is wrong if the input contains
a parallel-aware table scan node, since the portion of the table scanned
by the leader process is likely to vary from one rescan to the next.
This explains the timing-dependent buildfarm failures we saw after
commit a2b70c89c.
The established mechanism for showing that a plan node's output is
potentially variable is to mark it as depending on some runtime Param.
Hence, to fix this, invent a dummy Param (one that has a PARAM_EXEC
parameter number, but carries no actual value) associated with each Gather
or GatherMerge node, mark parallel-aware nodes below that node as dependent
on that Param, and arrange for ExecReScanGather[Merge] to flag that Param
as changed whenever the Gather[Merge] node is rescanned.
This solution breaks an undocumented assumption made by the parallel
executor logic, namely that all rescans of nodes below a Gather[Merge]
will happen synchronously during the ReScan of the top node itself.
But that's fundamentally contrary to the design of the ExecReScan code,
and so was doomed to fail someday anyway (even if you want to argue
that the bug being fixed here wasn't a failure of that assumption).
A follow-on patch will address that issue. In the meantime, the worst
that's expected to happen is that given very bad timing luck, the leader
might have to do all the work during a rescan, because workers think
they have nothing to do, if they are able to start up before the eventual
ReScan of the leader's parallel-aware table scan node has reset the
shared scan state.
Although this problem exists in 9.6, there does not seem to be any way
for it to manifest there. Without GatherMerge, it seems that a plan tree
that has a rescan-short-circuiting node below Gather will always also
have one above it that will short-circuit in the same cases, preventing
the Gather from being rescanned. Hence we won't take the risk of
back-patching this change into 9.6. But v10 needs it.
Discussion: https://postgr.es/m/CAA4eK1JkByysFJNh9M349u_nNjqETuEnY_y1VUc_kJiU0bxtaQ@mail.gmail.com
Change to appendStringInfoChar() or appendStringInfoString() where those
can be used.
Author: David Rowley <david.rowley@2ndquadrant.com>
Reviewed-by: Ashutosh Bapat <ashutosh.bapat@enterprisedb.com>
Previously, UNBOUNDED meant no lower bound when used in the FROM list,
and no upper bound when used in the TO list, which was OK for
single-column range partitioning, but problematic with multiple
columns. For example, an upper bound of (10.0, UNBOUNDED) would not be
collocated with a lower bound of (10.0, UNBOUNDED), thus making it
difficult or impossible to define contiguous multi-column range
partitions in some cases.
Fix this by using MINVALUE and MAXVALUE instead of UNBOUNDED to
represent a partition column that is unbounded below or above
respectively. This syntax removes any ambiguity, and ensures that if
one partition's lower bound equals another partition's upper bound,
then the partitions are contiguous.
Also drop the constraint prohibiting finite values after an unbounded
column, and just document the fact that any values after MINVALUE or
MAXVALUE are ignored. Previously it was necessary to repeat UNBOUNDED
multiple times, which was needlessly verbose.
Note: Forces a post-PG 10 beta2 initdb.
Report by Amul Sul, original patch by Amit Langote with some
additional hacking by me.
Discussion: https://postgr.es/m/CAAJ_b947mowpLdxL3jo3YLKngRjrq9+Ej4ymduQTfYR+8=YAYQ@mail.gmail.com
Add missing infrastructure for this node type, notably in ruleutils.c where
its lack could demonstrably cause EXPLAIN to fail. Add outfuncs/readfuncs
support. (outfuncs support is useful today for debugging purposes. The
readfuncs support may never be needed, since at present it would only
matter for parallel query and NextValueExpr should never appear in a
parallelizable query; but it seems like a bad idea to have a primnode type
that isn't fully supported here.) Teach planner infrastructure that
NextValueExpr is a volatile, parallel-unsafe, non-leaky expression node
with cost cpu_operator_cost. Given its limited scope of usage, there
*might* be no live bug today from the lack of that knowledge, but it's
certainly going to bite us on the rear someday. Teach pg_stat_statements
about the new node type, too.
While at it, also teach cost_qual_eval() that MinMaxExpr, SQLValueFunction,
XmlExpr, and CoerceToDomain should be charged as cpu_operator_cost.
Failing to do this for SQLValueFunction was an oversight in my commit
0bb51aa96. The others are longer-standing oversights, but no time like the
present to fix them. (In principle, CoerceToDomain could have cost much
higher than this, but it doesn't presently seem worth trying to examine the
domain's constraints here.)
Modify execExprInterp.c to execute NextValueExpr as an out-of-line
function; it seems quite unlikely to me that it's worth insisting that
it be inlined in all expression eval methods. Besides, providing the
out-of-line function doesn't stop anyone from inlining if they want to.
Adjust some places where NextValueExpr support had been inserted with the
aid of a dartboard rather than keeping it in the same order as elsewhere.
Discussion: https://postgr.es/m/23862.1499981661@sss.pgh.pa.us
WRITE_CHAR_FIELD() didn't do any escaping, so that for example a zero
byte would cause the whole output string to be truncated. To fix, pass
the char through outToken(), so it is escaped like a string. Adjust the
reading side to handle this.
The _equalTableFunc() omission of coltypmods has semantic significance,
but I did not track down resulting user-visible bugs, if any. The other
changes are cosmetic only, affecting order. catversion bump due to
readfuncs.c field order change.
Commit 18ce3a4ab22d2984f8540ab480979c851dae5338 failed to update
the comments in parsenodes.h for the new members, and made only
incomplete updates to src/backend/nodes
Thomas Munro, per a report from Noah Misch.
Discussion: http://postgr.es/m/20170611062525.GA1628882@rfd.leadboat.com
We could have limped along without this for v10, which was my intention
when I annotated the bug in commit 76a3df6e5. But consensus is that it's
better to fix it now and take the cost of a post-beta1 initdb (which is
needed because these node types are stored in pg_class.relpartbound).
Since we're forcing initdb anyway, take the opportunity to make the node
type identification strings match the node struct names, instead of being
randomly different from them.
Discussion: https://postgr.es/m/E1dFBEX-0004wt-8t@gemulon.postgresql.org
Fix failure to check that we got a plain Const from const-simplification of
a coercion request. This is the cause of bug #14666 from Tian Bing: there
is an int4 to money cast, but it's only stable not immutable (because of
dependence on lc_monetary), resulting in a FuncExpr that the code was
miserably unequipped to deal with, or indeed even to notice that it was
failing to deal with. Add test cases around this coercion behavior.
In view of the above, sprinkle the code liberally with castNode() macros,
in hope of catching the next such bug a bit sooner. Also, change some
functions that were randomly declared to take Node* to take more specific
pointer types. And change some struct fields that were declared Node*
but could be given more specific types, allowing removal of assorted
explicit casts.
Place PARTITION_MAX_KEYS check a bit closer to the code it's protecting.
Likewise check only-one-key-for-list-partitioning restriction in a less
random place.
Avoid not-per-project-style usages like !strcmp(...).
Fix assorted failures to avoid scribbling on the input of parse
transformation. I'm not sure how necessary this is, but it's entirely
silly for these functions to be expending cycles to avoid that and not
getting it right.
Add guards against partitioning on system columns.
Put backend/nodes/ support code into an order that matches handling
of these node types elsewhere.
Annotate the fact that somebody added location fields to PartitionBoundSpec
and PartitionRangeDatum but forgot to handle them in
outfuncs.c/readfuncs.c. This is fairly harmless for production purposes
(since readfuncs.c would just substitute -1 anyway) but it's still bogus.
It's not worth forcing a post-beta1 initdb just to fix this, but if we
have another reason to force initdb before 10.0, we should go back and
clean this up.
Contrariwise, somebody added location fields to PartitionElem and
PartitionSpec but forgot to teach exprLocation() about them.
Consolidate duplicative code in transformPartitionBound().
Improve a couple of error messages.
Improve assorted commentary.
Re-pgindent the files touched by this patch; this affects a few comment
blocks that must have been added quite recently.
Report: https://postgr.es/m/20170524024550.29935.14396@wrigleys.postgresql.org
skewColType/skewColTypmod are no longer used in the wake of commit
9aab83fc5, and seem unlikely to be wanted in future, so let's drop 'em.
Discussion: https://postgr.es/m/16364.1494520862@sss.pgh.pa.us
Previously, we had the WITH clause in the middle of the command, where
you'd specify both generic options as well as statistic types. Few
people liked this, so this commit changes it to remove the WITH keyword
from that clause and makes it accept statistic types only. (We
currently don't have any generic options, but if we invent in the
future, we will gain a new WITH clause, probably at the end of the
command).
Also, the column list is now specified without parens, which makes the
whole command look more similar to a SELECT command. This change will
let us expand the command to supporting expressions (not just columns
names) as well as multiple tables and their join conditions.
Tom added lots of code comments and fixed some parts of the CREATE
STATISTICS reference page, too; more changes in this area are
forthcoming. He also fixed a potential problem in the alter_generic
regression test, reducing verbosity on a cascaded drop to avoid
dependency on message ordering, as we do in other tests.
Tom also closed a security bug: we documented that table ownership was
required in order to create a statistics object on it, but didn't
actually implement it.
Implement tab-completion for statistics objects. This can stand some
more improvement.
Authors: Alvaro Herrera, with lots of cleanup by Tom Lane
Discussion: https://postgr.es/m/20170420212426.ltvgyhnefvhixm6i@alvherre.pgsql
