| Commit message (Collapse) | Author | Age |
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In the normal course of operation, query trees will be serialized only if
they are stored as views or rules; and plan trees will be serialized only
if they get passed to parallel-query workers. This leaves an awful lot of
opportunity for bugs/oversights to not get detected, as indeed we've just
been reminded of the hard way.
To improve matters, this patch adds a new compile option
WRITE_READ_PARSE_PLAN_TREES, which is modeled on the longstanding option
COPY_PARSE_PLAN_TREES; but instead of passing all parse and plan trees
through copyObject, it passes them through nodeToString + stringToNode.
Enabling this option in a buildfarm animal or two will catch problems
at least for cases that are exercised by the regression tests.
A small problem with this idea is that readfuncs.c historically has
discarded location fields, on the reasonable grounds that parse
locations in a retrieved view are not relevant to the current query.
But doing that in WRITE_READ_PARSE_PLAN_TREES breaks pg_stat_statements,
and it could cause problems for future improvements that might try to
report error locations at runtime. To fix that, provide a variant
behavior in readfuncs.c that makes it restore location fields when
told to.
In passing, const-ify the string arguments of stringToNode and its
subsidiary functions, just because it annoyed me that they weren't
const already.
Discussion: https://postgr.es/m/17114.1537138992@sss.pgh.pa.us
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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
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The system expects TABLEFUNC RTEs to have coltypes, coltypmods, and
colcollations lists, but outfuncs doesn't dump them and readfuncs doesn't
restore them. This doesn't cause obvious failures, because the only things
that look at those fields are expandRTE() and get_rte_attribute_type(),
which are mostly used during parse analysis, before anything would've
passed the parsetree through outfuncs/readfuncs. But expandRTE() is used
in build_physical_tlist(), which means that that function will return a
wrong answer for a TABLEFUNC RTE that came from a view. Very accidentally,
this doesn't cause serious problems, because what it will return is NIL
which callers will interpret as "couldn't build a physical tlist because
of dropped columns". So you still get a plan that works, though it's
marginally less efficient than it could be. There are also some other
expandRTE() calls associated with transformation of whole-row Vars in
the planner. I have been unable to exhibit misbehavior from that, and
it may be unreachable in any case that anyone would care about ... but
I'm not entirely convinced, so this seems like something we should back-
patch a fix for. Fortunately, we can fix it without forcing a change
of stored rules and a catversion bump, because we can just copy these
lists from the subsidiary TableFunc object.
readfuncs.c was also missing support for NamedTuplestoreScan plan nodes.
This accidentally fails to break parallel query because a query using
a named tuplestore would never be considered parallel-safe anyway.
However, project policy since parallel query came in is that all plan
node types should have outfuncs/readfuncs support, so this is clearly
an oversight that should be repaired.
Noted while fooling around with a patch to test outfuncs/readfuncs more
thoroughly. That exposed some other issues too, but these are the only
ones that seem worth back-patching.
Back-patch to v10 where both of these features came in.
Discussion: https://postgr.es/m/17114.1537138992@sss.pgh.pa.us
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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
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This expands the support for the run-time partition pruning which was added
for Append in 499be013de to also allow unneeded subnodes of a MergeAppend
to be removed.
Author: David Rowley
Discussion: https://www.postgresql.org/message-id/CAKJS1f_F_V8D7Wu-HVdnH7zCUxhoGK8XhLLtd%3DCu85qDZzXrgg%40mail.gmail.com
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Use "subplan" rather than "subnode" to refer to the child plans of
a partitioning Append; this seems a bit more specific and hence
clearer. Improve assorted comments. No non-cosmetic changes.
David Rowley and Tom Lane
Discussion: https://postgr.es/m/CAFj8pRBjrufA3ocDm8o4LPGNye9Y+pm1b9kCwode4X04CULG3g@mail.gmail.com
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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
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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
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This field was a bool at one point, but now it's an int.
Spotted by Hari Babu; trivial patch is by Ashutosh Bapat.
Discussion: https://postgr.es/m/CAJrrPGedKiFE2fqntSauUfhapCksOJzam+QtHfSgx86LhXLeOQ@mail.gmail.com
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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
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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
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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
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Separation of parser data structures from executor, as
requested by Tom Lane. Further improvements possible.
While there, implement error for multiple VALUES clauses via parser
to allow line number of error, as requested by Andres Freund.
Author: Pavan Deolasee
Discussion: https://www.postgresql.org/message-id/CABOikdPpqjectFchg0FyTOpsGXyPoqwgC==OLKWuxgBOsrDDZw@mail.gmail.com
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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.com
https://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
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This reverts commit 354f13855e6381d288dfaa52bcd4f2cb0fd4a5eb.
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Reported-by: Michael Paquier, Abhijit Menon-Sen
Discussion: https://postgr.es/m/20180305045854.GB2266@paquier.xyz
Author: Michael Paquier, Abhijit Menon-Sen, me
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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
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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
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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
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Backpatch-through: certain files through 9.3
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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.com
https://postgr.es/m/CAEepm=37HKyJ4U6XOLi=JgfSHM3o6B-GaeO-6hkOmneTDkH+Uw@mail.gmail.com
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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
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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
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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
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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
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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
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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
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Any tuples that don't route to any other partition will route to the
default partition.
Jeevan Ladhe, Beena Emerson, Ashutosh Bapat, Rahila Syed, and Robert
Haas, with review and testing at various stages by (at least) Rushabh
Lathia, Keith Fiske, Amit Langote, Amul Sul, Rajkumar Raghuanshi, Sven
Kunze, Kyotaro Horiguchi, Thom Brown, Rafia Sabih, and Dilip Kumar.
Discussion: http://postgr.es/m/CAH2L28tbN4SYyhS7YV1YBWcitkqbhSWfQCy0G=apRcC_PEO-bg@mail.gmail.com
Discussion: http://postgr.es/m/CAOG9ApEYj34fWMcvBMBQ-YtqR9fTdXhdN82QEKG0SVZ6zeL1xg@mail.gmail.com
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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
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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
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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
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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.
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Change pg_bsd_indent to follow upstream rules for placement of comments
to the right of code, and remove pgindent hack that caused comments
following #endif to not obey the general rule.
Commit e3860ffa4dd0dad0dd9eea4be9cc1412373a8c89 wasn't actually using
the published version of pg_bsd_indent, but a hacked-up version that
tried to minimize the amount of movement of comments to the right of
code. The situation of interest is where such a comment has to be
moved to the right of its default placement at column 33 because there's
code there. BSD indent has always moved right in units of tab stops
in such cases --- but in the previous incarnation, indent was working
in 8-space tab stops, while now it knows we use 4-space tabs. So the
net result is that in about half the cases, such comments are placed
one tab stop left of before. This is better all around: it leaves
more room on the line for comment text, and it means that in such
cases the comment uniformly starts at the next 4-space tab stop after
the code, rather than sometimes one and sometimes two tabs after.
Also, ensure that comments following #endif are indented the same
as comments following other preprocessor commands such as #else.
That inconsistency turns out to have been self-inflicted damage
from a poorly-thought-through post-indent "fixup" in pgindent.
This patch is much less interesting than the first round of indent
changes, but also bulkier, so I thought it best to separate the effects.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
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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.
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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
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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
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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
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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
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Even though no actual tuples are ever inserted into a partitioned
table (the actual tuples are in the partitions, not the partitioned
table itself), we still need to have a ResultRelInfo for the
partitioned table, or per-statement triggers won't get fired.
Amit Langote, per a report from Rajkumar Raghuwanshi. Reviewed by me.
Discussion: http://postgr.es/m/CAKcux6%3DwYospCRY2J4XEFuVy0L41S%3Dfic7rmkbsU-GXhhSbmBg%40mail.gmail.com
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We'd managed to avoid doing this so far, but it seems pretty obvious
that it would be forced on us some day, and this is much the cleanest
way of approaching the open problem that parallel-unsafe subplans are
being transmitted to parallel workers. Anyway there's no space cost
due to alignment considerations, and the time cost is pretty minimal
since we're just copying the flag from the corresponding Path node.
(At least in most cases ... some of the klugier spots in createplan.c
have to work a bit harder.)
In principle we could perhaps get rid of SubPlan.parallel_safe,
but I thought it better to keep that in case there are reasons to
consider a SubPlan unsafe even when its child plan is parallel-safe.
This patch doesn't actually do anything with the new flags, but
I thought I'd commit it separately anyway.
Note: although this touches outfuncs/readfuncs, there's no need for
a catversion bump because Plan trees aren't stored on disk.
Discussion: https://postgr.es/m/87tw5x4vcu.fsf@credativ.de
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If there can certainly be no more than one matching inner row for a given
outer row, then the executor can move on to the next outer row as soon as
it's found one match; there's no need to continue scanning the inner
relation for this outer row. This saves useless scanning in nestloop
and hash joins. In merge joins, it offers the opportunity to skip
mark/restore processing, because we know we have not advanced past the
first possible match for the next outer row.
Of course, the devil is in the details: the proof of uniqueness must
depend only on joinquals (not otherquals), and if we want to skip
mergejoin mark/restore then it must depend only on merge clauses.
To avoid adding more planning overhead than absolutely necessary,
the present patch errs in the conservative direction: there are cases
where inner_unique or skip_mark_restore processing could be used, but
it will not do so because it's not sure that the uniqueness proof
depended only on "safe" clauses. This could be improved later.
David Rowley, reviewed and rather heavily editorialized on by me
Discussion: https://postgr.es/m/CAApHDvqF6Sw-TK98bW48TdtFJ+3a7D2mFyZ7++=D-RyPsL76gw@mail.gmail.com
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This is the SQL standard-conforming variant of PostgreSQL's serial
columns. It fixes a few usability issues that serial columns have:
- CREATE TABLE / LIKE copies default but refers to same sequence
- cannot add/drop serialness with ALTER TABLE
- dropping default does not drop sequence
- need to grant separate privileges to sequence
- other slight weirdnesses because serial is some kind of special macro
Reviewed-by: Vitaly Burovoy <vitaly.burovoy@gmail.com>
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A QueryEnvironment concept is added, which allows new types of
objects to be passed into queries from parsing on through
execution. At this point, the only thing implemented is a
collection of EphemeralNamedRelation objects -- relations which
can be referenced by name in queries, but do not exist in the
catalogs. The only type of ENR implemented is NamedTuplestore, but
provision is made to add more types fairly easily.
An ENR can carry its own TupleDesc or reference a relation in the
catalogs by relid.
Although these features can be used without SPI, convenience
functions are added to SPI so that ENRs can easily be used by code
run through SPI.
The initial use of all this is going to be transition tables in
AFTER triggers, but that will be added to each PL as a separate
commit.
An incidental effect of this patch is to produce a more informative
error message if an attempt is made to modify the contents of a CTE
from a referencing DML statement. No tests previously covered that
possibility, so one is added.
Kevin Grittner and Thomas Munro
Reviewed by Heikki Linnakangas, David Fetter, and Thomas Munro
with valuable comments and suggestions from many others
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Partitioned tables do not contain any data; only their unpartitioned
descendents need to be scanned. However, the partitioned tables still
need to be locked, even though they're not scanned. To make that
work, Append and MergeAppend relations now need to carry a list of
(unscanned) partitioned relations that must be locked, and InitPlan
must lock all partitioned result relations.
Aside from the obvious advantage of avoiding some work at execution
time, this has two other advantages. First, it may improve the
planner's decision-making in some cases since the empty relation
might throw things off. Second, it paves the way to getting rid of
the storage for partitioned tables altogether.
Amit Langote, reviewed by me.
Discussion: http://postgr.es/m/6837c359-45c4-8044-34d1-736756335a15@lab.ntt.co.jp
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Like Gather, we spawn multiple workers and run the same plan in each
one; however, Gather Merge is used when each worker produces the same
output ordering and we want to preserve that output ordering while
merging together the streams of tuples from various workers. (In a
way, Gather Merge is like a hybrid of Gather and MergeAppend.)
This works out to a win if it saves us from having to perform an
expensive Sort. In cases where only a small amount of data would need
to be sorted, it may actually be faster to use a regular Gather node
and then sort the results afterward, because Gather Merge sometimes
needs to wait synchronously for tuples whereas a pure Gather generally
doesn't. But if this avoids an expensive sort then it's a win.
Rushabh Lathia, reviewed and tested by Amit Kapila, Thomas Munro,
and Neha Sharma, and reviewed and revised by me.
Discussion: http://postgr.es/m/CAGPqQf09oPX-cQRpBKS0Gq49Z+m6KBxgxd_p9gX8CKk_d75HoQ@mail.gmail.com
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The index is scanned by a single process, but then all cooperating
processes can iterate jointly over the resulting set of heap blocks.
In the future, we might also want to support using a parallel bitmap
index scan to set up for a parallel bitmap heap scan, but that's a
job for another day.
Dilip Kumar, with some corrections and cosmetic changes by me. The
larger patch set of which this is a part has been reviewed and tested
by (at least) Andres Freund, Amit Khandekar, Tushar Ahuja, Rafia
Sabih, Haribabu Kommi, Thomas Munro, and me.
Discussion: http://postgr.es/m/CAFiTN-uc4=0WxRGfCzs-xfkMYcSEWUC-Fon6thkJGjkh9i=13A@mail.gmail.com
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XMLTABLE is defined by the SQL/XML standard as a feature that allows
turning XML-formatted data into relational form, so that it can be used
as a <table primary> in the FROM clause of a query.
This new construct provides significant simplicity and performance
benefit for XML data processing; what in a client-side custom
implementation was reported to take 20 minutes can be executed in 400ms
using XMLTABLE. (The same functionality was said to take 10 seconds
using nested PostgreSQL XPath function calls, and 5 seconds using
XMLReader under PL/Python).
The implemented syntax deviates slightly from what the standard
requires. First, the standard indicates that the PASSING clause is
optional and that multiple XML input documents may be given to it; we
make it mandatory and accept a single document only. Second, we don't
currently support a default namespace to be specified.
This implementation relies on a new executor node based on a hardcoded
method table. (Because the grammar is fixed, there is no extensibility
in the current approach; further constructs can be implemented on top of
this such as JSON_TABLE, but they require changes to core code.)
Author: Pavel Stehule, Álvaro Herrera
Extensively reviewed by: Craig Ringer
Discussion: https://postgr.es/m/CAFj8pRAgfzMD-LoSmnMGybD0WsEznLHWap8DO79+-GTRAPR4qA@mail.gmail.com
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This doesn't do anything to make Param nodes anything other than
parallel-restricted, so this only helps with uncorrelated subplans,
and it's not necessarily very cheap because each worker will run the
subplan separately (just as a Hash Join will build a separate copy of
the hash table in each participating process), but it's a first step
toward supporting cases that are more likely to help in practice, and
is occasionally useful on its own.
Amit Kapila, reviewed and tested by Rafia Sabih, Dilip Kumar, and
me.
Discussion: http://postgr.es/m/CAA4eK1+e8Z45D2n+rnDMDYsVEb5iW7jqaCH_tvPMYau=1Rru9w@mail.gmail.com
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