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 hash join appears in a parallel query, there may be no hash table
available for explain.c to inspect even though a hash table may have
been built in other processes. This could happen either because
parallel_leader_participation was set to off or because the leader
happened to hit the end of the outer relation immediately (even though
the complete relation is not empty) and decided not to build the hash
table.
Commit bf11e7ee introduced a way for workers to exchange
instrumentation via the DSM segment for Sort nodes even though they
are not parallel-aware. This commit does the same for Hash nodes, so
that explain.c has a way to find instrumentation data from an
arbitrary participant that actually built the hash table.
Author: Thomas Munro
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/CAEepm%3D3DUQC2-z252N55eOcZBer6DPdM%3DFzrxH9dZc5vYLsjaA%40mail.gmail.com
The lower case spellings are C and C++ standard and are used in most
parts of the PostgreSQL sources. The upper case spellings are only used
in some files/modules. So standardize on the standard spellings.
The APIs for ICU, Perl, and Windows define their own TRUE and FALSE, so
those are left as is when using those APIs.
In code comments, we use the lower-case spelling for the C concepts and
keep the upper-case spelling for the SQL concepts.
Reviewed-by: Michael Paquier <michael.paquier@gmail.com>
If we don't have to return any columns from heap tuples, and there's
no need to recheck qual conditions, and the heap page is all-visible,
then we can skip fetching the heap page altogether.
Skip prefetching pages too, when possible, on the assumption that the
recheck flag will remain the same from one page to the next. While that
assumption is hardly bulletproof, it seems like a good bet most of the
time, and better than prefetching pages we don't need.
This commit installs the executor infrastructure, but doesn't change
any planner cost estimates, thus possibly causing bitmap scans to
not be chosen in cases where this change renders them the best choice.
I (tgl) am not entirely convinced that we need to account for this
behavior in the planner, because I think typically the bitmap scan would
get chosen anyway if it's the best bet. In any case the submitted patch
took way too many shortcuts, resulting in too many clearly-bad choices,
to be committable.
Alexander Kuzmenkov, reviewed by Alexey Chernyshov, and whacked around
rather heavily by me.
Discussion: https://postgr.es/m/239a8955-c0fc-f506-026d-c837e86c827b@postgrespro.ru
If we try to run a parallel plan in serial mode because, for example,
it's going to be scanned via a cursor, but for some reason we're
already in parallel mode (for example because an outer query is
running in parallel), we'd incorrectly try to launch workers.
Fix by adding a flag to the EState, so that we can be certain that
ExecutePlan() and ExecGather()/ExecGatherMerge() will have the same
idea about whether we are executing serially or in parallel.
Report and fix by Amit Kapila with help from Kuntal Ghosh. A few
tweaks by me.
Discussion: http://postgr.es/m/CAA4eK1+_BuZrmVCeua5Eqnm4Co9DAXdM5HPAOE2J19ePbR912Q@mail.gmail.com
An aggregate's input expression(s) are not supposed to be evaluated
at all for a row where its FILTER test fails ... but commit 8ed3f11bb
overlooked that requirement. Reshuffle so that aggregates having a
filter clause evaluate their arguments separately from those without.
This still gets the benefit of doing only one ExecProject in the
common case of multiple Aggrefs, none of which have filters.
While at it, arrange for filter clauses to be included in the common
ExecProject evaluation, thus perhaps buying a little bit even when
there are filters.
Back-patch to v10 where the bug was introduced.
Discussion: https://postgr.es/m/30065.1508161354@sss.pgh.pa.us
The previous convention doesn't lend itself to creating ResultRelInfos
lazily, as we already do in ExecGetTriggerResultRel. This patch
doesn't make anything lazier than before, but the pending patch for
UPDATE tuple routing proposes to do so (and there might be other
opportunities as well).
Amit Khandekar with some adjustments by me.
Discussion: http://postgr.es/m/CA+TgmoYPVP9Lyf6vUFA5DwxS4c--x6LOj2y36BsJaYtp62eXPQ@mail.gmail.com
If we merge the transition calculations for two different aggregates,
it's reasonable to assume that the transition function should not care
which of those Aggref structs it gets from AggGetAggref(). It is not
reasonable to make the same assumption about an aggregate final function,
however. Commit 804163bc2 broke this, as it will pass whichever Aggref
was first associated with the transition state in both cases.
This doesn't create an observable bug so far as the core system is
concerned, because the only existing uses of AggGetAggref() are in
ordered-set aggregates that happen to not pay attention to anything
but the input properties of the Aggref; and besides that, we disabled
sharing of transition calculations for OSAs yesterday. Nonetheless,
if some third-party code were using AggGetAggref() in a normal aggregate,
they would be entitled to call this a bug. Hence, back-patch the fix
to 9.6 where the problem was introduced.
In passing, improve some of the comments about transition state sharing.
Discussion: https://postgr.es/m/CAB4ELO5RZhOamuT9Xsf72ozbenDLLXZKSk07FiSVsuJNZB861A@mail.gmail.com
Previously nodeProjectSet only released memory once per input tuple,
rather than once per returned tuple. If the computation of an
individual returned tuple requires a lot of memory, that can lead to
problems.
Instead change things so that the expression context can be reset once
per output tuple, which requires a new memory context to store SRF
arguments in.
This is a longstanding issue, but was hard to fix before 9.6, due to
the way tSRFs where evaluated. But it's fairly easy to fix now. We
could backpatch this into 10, but given there've been fewc omplaints
that doesn't seem worth the risk so far.
Reported-By: Lucas Fairchild
Author: Andres Freund, per discussion with Tom Lane
Discussion: https://postgr.es/m/4514.1507318623@sss.pgh.pa.us
The standard says that all changes of the same kind (insert, update, or
delete) caused in one table by a single SQL statement should be reported
in a single transition table; and by that, they mean to include foreign key
enforcement actions cascading from the statement's direct effects. It's
also reasonable to conclude that if the standard had wCTEs, they would say
that effects of wCTEs applying to the same table as each other or the outer
statement should be merged into one transition table. We weren't doing it
like that.
Hence, arrange to merge tuples from multiple update actions into a single
transition table as much as we can. There is a problem, which is that if
the firing of FK enforcement triggers and after-row triggers with
transition tables is interspersed, we might need to report more tuples
after some triggers have already seen the transition table. It seems like
a bad idea for the transition table to be mutable between trigger calls.
There's no good way around this without a major redesign of the FK logic,
so for now, resolve it by opening a new transition table each time this
happens.
Also, ensure that AFTER STATEMENT triggers fire just once per statement,
or once per transition table when we're forced to make more than one.
Previous versions of Postgres have allowed each FK enforcement query
to cause an additional firing of the AFTER STATEMENT triggers for the
referencing table, but that's certainly not per spec. (We're still
doing multiple firings of BEFORE STATEMENT triggers, though; is that
something worth changing?)
Also, forbid using transition tables with column-specific UPDATE triggers.
The spec requires such transition tables to show only the tuples for which
the UPDATE trigger would have fired, which means maintaining multiple
transition tables or else somehow filtering the contents at readout.
Maybe someday we'll bother to support that option, but it looks like a
lot of trouble for a marginal feature.
The transition tables are now managed by the AfterTriggers data structures,
rather than being directly the responsibility of ModifyTable nodes. This
removes a subtransaction-lifespan memory leak introduced by my previous
band-aid patch 3c4359521.
In passing, refactor the AfterTriggers data structures to reduce the
management overhead for them, by using arrays of structs rather than
several parallel arrays for per-query-level and per-subtransaction state.
I failed to resist the temptation to do some copy-editing on the SGML
docs about triggers, above and beyond merely documenting the effects
of this patch.
Back-patch to v10, because we don't want the semantics of transition
tables to change post-release.
Patch by me, with help and review from Thomas Munro.
Discussion: https://postgr.es/m/20170909064853.25630.12825@wrigleys.postgresql.org
Rescanning a GatherMerge led to leaking some memory in the executor's
query-lifespan context, because most of the node's working data structures
were simply abandoned and rebuilt from scratch. In practice, this might
never amount to much, given the cost of relaunching worker processes ---
but it's still pretty messy, so let's fix it.
We can rearrange things so that the tuple arrays are simply cleared and
reused, and we don't need to rebuild the TupleTableSlots either, just
clear them. One small complication is that because we might get a
different number of workers on each iteration, we can't keep the old
convention that the leader's gm_slots[] entry is the last one; the leader
might clobber a TupleTableSlot that we need for a worker in a future
iteration. Hence, adjust the logic so that the leader has slot 0 always,
while the active workers have slots 1..n.
Back-patch to v10 to keep all the existing versions of nodeGatherMerge.c
in sync --- because of the renumbering of the slots, there would otherwise
be a very large risk that any future backpatches in this module would
introduce bugs.
Discussion: https://postgr.es/m/8670.1504192177@sss.pgh.pa.us
Comment the fields of GatherMergeState, and organize them a bit more
sensibly. Comment GMReaderTupleBuffer more usefully too. Improve
assorted other comments that were obsolete or just not very good English.
Get rid of the use of a GMReaderTupleBuffer for the leader process;
that was confusing, since only the "done" field was used, and that
in a way redundant with need_to_scan_locally.
In gather_merge_init, avoid calling load_tuple_array for
already-known-exhausted workers. I'm not sure if there's a live bug there,
but the case is unlikely to be well tested due to timing considerations.
Remove some useless code, such as duplicating the tts_isempty test done by
TupIsNull.
Remove useless initialization of ps.qual, replacing that with an assertion
that we have no qual to check. (If we did, the code would fail to check
it.)
Avoid applying heap_copytuple to a null tuple. While that fails to crash,
it's confusing and it makes the code less legible not more so IMO.
Propagate a couple of these changes into nodeGather.c, as well.
Back-patch to v10, partly because of the possibility that the
gather_merge_init change is fixing a live bug, but mostly to keep
the branches in sync to ease future bug fixes.
Up until now, when parallel query was used, no details about the
sort method or space used by the workers were available; details
were shown only for any sorting done by the leader. Fix that.
Commit 1177ab1dab forced the test case
added by commit 1f6d515a67 to run
without parallelism; now that we have this infrastructure, allow
that again, with a little tweaking to make it pass with and without
force_parallel_mode.
Robert Haas and Tom Lane
Discussion: http://postgr.es/m/CA+Tgmoa2VBZW6S8AAXfhpHczb=Rf6RqQ2br+zJvEgwJ0uoD_tQ@mail.gmail.com
If we only need, say, 10 tuples in total, then we certainly don't need
more than 10 tuples from any single process. Pushing down the limit
lets workers exit early when possible. For Gather Merge, there is
an additional benefit: a Sort immediately below the Gather Merge can
be done as a bounded sort if there is an applicable limit.
Robert Haas and Tom Lane
Discussion: http://postgr.es/m/CA+TgmoYa3QKKrLj5rX7UvGqhH73G1Li4B-EKxrmASaca2tFu9Q@mail.gmail.com
Add a new EState member es_leaf_result_relations, so that the trigger
code knows about ResultRelInfos created by tuple routing. Also make
sure ExplainPrintTriggers knows about partition-related
ResultRelInfos.
Etsuro Fujita, reviewed by Amit Langote
Discussion: http://postgr.es/m/57163e18-8e56-da83-337a-22f2c0008051@lab.ntt.co.jp
This allows us to add stack-depth checks the first time an executor
node is called, and skip that overhead on following
calls. Additionally it yields a nice speedup.
While it'd probably have been a good idea to have that check all
along, it has become more important after the new expression
evaluation framework in b8d7f053c5 - there's no stack depth
check in common paths anymore now. We previously relied on
ExecEvalExpr() being executed somewhere.
We should move towards that model for further routines, but as this is
required for v10, it seems better to only do the necessary (which
already is quite large).
Author: Andres Freund, Tom Lane
Reported-By: Julien Rouhaud
Discussion:
https://postgr.es/m/22833.1490390175@sss.pgh.pa.ushttps://postgr.es/m/b0af9eaa-130c-60d0-9e4e-7a135b1e0c76@dalibo.com
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 e3860ffa4d 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
The new indent version includes numerous fixes thanks to Piotr Stefaniak.
The main changes visible in this commit are:
* Nicer formatting of function-pointer declarations.
* No longer unexpectedly removes spaces in expressions using casts,
sizeof, or offsetof.
* No longer wants to add a space in "struct structname *varname", as
well as some similar cases for const- or volatile-qualified pointers.
* Declarations using PG_USED_FOR_ASSERTS_ONLY are formatted more nicely.
* Fixes bug where comments following declarations were sometimes placed
with no space separating them from the code.
* Fixes some odd decisions for comments following case labels.
* Fixes some cases where comments following code were indented to less
than the expected column 33.
On the less good side, it now tends to put more whitespace around typedef
names that are not listed in typedefs.list. This might encourage us to
put more effort into typedef name collection; it's not really a bug in
indent itself.
There are more changes coming after this round, having to do with comment
indentation and alignment of lines appearing within parentheses. I wanted
to limit the size of the diffs to something that could be reviewed without
one's eyes completely glazing over, so it seemed better to split up the
changes as much as practical.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
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
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
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
This extends the Aggregate node with two new features: HashAggregate
can now run multiple hashtables concurrently, and a new strategy
MixedAggregate populates hashtables while doing sorted grouping.
The planner will now attempt to save as many sorts as possible when
planning grouping sets queries, while not exceeding work_mem for the
estimated combined sizes of all hashtables used. No SQL-level changes
are required. There should be no user-visible impact other than the
new EXPLAIN output and possible changes to result ordering when ORDER
BY was not used (which affected a few regression tests). The
enable_hashagg option is respected.
Author: Andrew Gierth
Reviewers: Mark Dilger, Andres Freund
Discussion: https://postgr.es/m/87vatszyhj.fsf@news-spur.riddles.org.uk
This replaces the old, recursive tree-walk based evaluation, with
non-recursive, opcode dispatch based, expression evaluation.
Projection is now implemented as part of expression evaluation.
This both leads to significant performance improvements, and makes
future just-in-time compilation of expressions easier.
The speed gains primarily come from:
- non-recursive implementation reduces stack usage / overhead
- simple sub-expressions are implemented with a single jump, without
function calls
- sharing some state between different sub-expressions
- reduced amount of indirect/hard to predict memory accesses by laying
out operation metadata sequentially; including the avoidance of
nearly all of the previously used linked lists
- more code has been moved to expression initialization, avoiding
constant re-checks at evaluation time
Future just-in-time compilation (JIT) has become easier, as
demonstrated by released patches intended to be merged in a later
release, for primarily two reasons: Firstly, due to a stricter split
between expression initialization and evaluation, less code has to be
handled by the JIT. Secondly, due to the non-recursive nature of the
generated "instructions", less performance-critical code-paths can
easily be shared between interpreted and compiled evaluation.
The new framework allows for significant future optimizations. E.g.:
- basic infrastructure for to later reduce the per executor-startup
overhead of expression evaluation, by caching state in prepared
statements. That'd be helpful in OLTPish scenarios where
initialization overhead is measurable.
- optimizing the generated "code". A number of proposals for potential
work has already been made.
- optimizing the interpreter. Similarly a number of proposals have
been made here too.
The move of logic into the expression initialization step leads to some
backward-incompatible changes:
- Function permission checks are now done during expression
initialization, whereas previously they were done during
execution. In edge cases this can lead to errors being raised that
previously wouldn't have been, e.g. a NULL array being coerced to a
different array type previously didn't perform checks.
- The set of domain constraints to be checked, is now evaluated once
during expression initialization, previously it was re-built
every time a domain check was evaluated. For normal queries this
doesn't change much, but e.g. for plpgsql functions, which caches
ExprStates, the old set could stick around longer. The behavior
around might still change.
Author: Andres Freund, with significant changes by Tom Lane,
changes by Heikki Linnakangas
Reviewed-By: Tom Lane, Heikki Linnakangas
Discussion: https://postgr.es/m/20161206034955.bh33paeralxbtluv@alap3.anarazel.de
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
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
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
With this change, you can see the query that a parallel worker is
executing in pg_stat_activity, and if the worker crashes you can
see what query it was executing when it crashed.
Rafia Sabih, reviewed by Kuntal Ghosh and Amit Kapila and slightly
revised by me.
Commit 5262f7a4fc added similar support
for parallel index scans; this extends that work to index-only scans.
As with parallel index scans, this requires support from the index AM,
so currently parallel index-only scans will only be possible for btree
indexes.
Rafia Sabih, reviewed and tested by Rahila Syed, Tushar Ahuja,
and Amit Kapila
Discussion: http://postgr.es/m/CAOGQiiPEAs4C=TBp0XShxBvnWXuzGL2u++Hm1=qnCpd6_Mf8Fw@mail.gmail.com
In combination with 569174f1be, which
taught the btree AM how to perform parallel index scans, this allows
parallel index scan plans on btree indexes. This infrastructure
should be general enough to support parallel index scans for other
index AMs as well, if someone updates them to support parallel
scans.
Amit Kapila, reviewed and tested by Anastasia Lubennikova, Tushar
Ahuja, and Haribabu Kommi, and me.
It's always been possible for index AMs to cache data across successive
amgettuple calls within a single SQL command: the IndexScanDesc.opaque
field is meant for precisely that. However, no comparable facility
exists for amortizing setup work across successive aminsert calls.
This patch adds such a feature and teaches GIN, GIST, and BRIN to use it
to amortize catalog lookups they'd previously been doing on every call.
(The other standard index AMs keep everything they need in the relcache,
so there's little to improve there.)
For GIN, the overall improvement in a statement that inserts many rows
can be as much as 10%, though it seems a bit less for the other two.
In addition, this makes a really significant difference in runtime
for CLOBBER_CACHE_ALWAYS tests, since in those builds the repeated
catalog lookups are vastly more expensive.
The reason this has been hard up to now is that the aminsert function is
not passed any useful place to cache per-statement data. What I chose to
do is to add suitable fields to struct IndexInfo and pass that to aminsert.
That's not widening the index AM API very much because IndexInfo is already
within the ken of ambuild; in fact, by passing the same info to aminsert
as to ambuild, this is really removing an inconsistency in the AM API.
Discussion: https://postgr.es/m/27568.1486508680@sss.pgh.pa.us
Since 69f4b9c plain expression evaluation (and thus normal projection)
can't return sets of tuples anymore. Thus remove code dealing with
that possibility.
This will require adjustments in external code using
ExecEvalExpr()/ExecProject() - that should neither be hard nor very
common.
Author: Andres Freund and Tom Lane
Discussion: https://postgr.es/m/20160822214023.aaxz5l4igypowyri@alap3.anarazel.de
Evaluation of set returning functions (SRFs_ in the targetlist (like SELECT
generate_series(1,5)) so far was done in the expression evaluation (i.e.
ExecEvalExpr()) and projection (i.e. ExecProject/ExecTargetList) code.
This meant that most executor nodes performing projection, and most
expression evaluation functions, had to deal with the possibility that an
evaluated expression could return a set of return values.
That's bad because it leads to repeated code in a lot of places. It also,
and that's my (Andres's) motivation, made it a lot harder to implement a
more efficient way of doing expression evaluation.
To fix this, introduce a new executor node (ProjectSet) that can evaluate
targetlists containing one or more SRFs. To avoid the complexity of the old
way of handling nested expressions returning sets (e.g. having to pass up
ExprDoneCond, and dealing with arguments to functions returning sets etc.),
those SRFs can only be at the top level of the node's targetlist. The
planner makes sure (via split_pathtarget_at_srfs()) that SRF evaluation is
only necessary in ProjectSet nodes and that SRFs are only present at the
top level of the node's targetlist. If there are nested SRFs the planner
creates multiple stacked ProjectSet nodes. The ProjectSet nodes always get
input from an underlying node.
We also discussed and prototyped evaluating targetlist SRFs using ROWS
FROM(), but that turned out to be more complicated than we'd hoped.
While moving SRF evaluation to ProjectSet would allow to retain the old
"least common multiple" behavior when multiple SRFs are present in one
targetlist (i.e. continue returning rows until all SRFs are at the end of
their input at the same time), we decided to instead only return rows till
all SRFs are exhausted, returning NULL for already exhausted ones. We
deemed the previous behavior to be too confusing, unexpected and actually
not particularly useful.
As a side effect, the previously prohibited case of multiple set returning
arguments to a function, is now allowed. Not because it's particularly
desirable, but because it ends up working and there seems to be no argument
for adding code to prohibit it.
Currently the behavior for COALESCE and CASE containing SRFs has changed,
returning multiple rows from the expression, even when the SRF containing
"arm" of the expression is not evaluated. That's because the SRFs are
evaluated in a separate ProjectSet node. As that's quite confusing, we're
likely to instead prohibit SRFs in those places. But that's still being
discussed, and the code would reside in places not touched here, so that's
a task for later.
There's a lot of, now superfluous, code dealing with set return expressions
around. But as the changes to get rid of those are verbose largely boring,
it seems better for readability to keep the cleanup as a separate commit.
Author: Tom Lane and Andres Freund
Discussion: https://postgr.es/m/20160822214023.aaxz5l4igypowyri@alap3.anarazel.de
After a tuple is routed to a partition, it has been converted from the
root table's row type to the partition's row type. ExecConstraints
needs to report the failure using the original tuple and the parent's
tuple descriptor rather than the ones for the selected partition.
Amit Langote
Commit 2ac3ef7a01 added a TupleTapleSlot
for partition tuple slot to EState (es_partition_tuple_slot) but it's
more logical to have it as part of ModifyTableState
(mt_partition_tuple_slot) and CopyState (partition_tuple_slot).
Discussion: http://postgr.es/m/1bd459d9-4c0c-197a-346e-e5e59e217d97@lab.ntt.co.jp
Amit Langote, per a gripe from me
The previous coding failed to work correctly when we have a
multi-level partitioned hierarchy where tables at successive levels
have different attribute numbers for the partition key attributes. To
fix, have each PartitionDispatch object store a standalone
TupleTableSlot initialized with the TupleDesc of the corresponding
partitioned table, along with a TupleConversionMap to map tuples from
the its parent's rowtype to own rowtype. After tuple routing chooses
a leaf partition, we must use the leaf partition's tuple descriptor,
not the root table's. To that end, a dedicated TupleTableSlot for
tuple routing is now allocated in EState.
Amit Langote
When the input value to a CoerceToDomain expression node is a read-write
expanded datum, we should pass a read-only pointer to any domain CHECK
expressions and then return the original read-write pointer as the
expression result. Previously we were blindly passing the same pointer to
all the consumers of the value, making it possible for a function in CHECK
to modify or even delete the expanded value. (Since a plpgsql function
will absorb a passed-in read-write expanded array as a local variable
value, it will in fact delete the value on exit.)
A similar hazard of passing the same read-write pointer to multiple
consumers exists in domain_check() and in ExecEvalCase, so fix those too.
The fix requires adding MakeExpandedObjectReadOnly calls at the appropriate
places, which is simple enough except that we need to get the data type's
typlen from somewhere. For the domain cases, solve this by redefining
DomainConstraintRef.tcache as okay for callers to access; there wasn't any
reason for the original convention against that, other than not wanting the
API of typcache.c to be any wider than it had to be. For CASE, there's
no good solution except to add a syscache lookup during executor start.
Per bug #14472 from Marcos Castedo. Back-patch to 9.5 where expanded
values were introduced.
Discussion: https://postgr.es/m/15225.1482431619@sss.pgh.pa.us
Commit 5dfc198146 introduced the use
of a new type of hash table with linear reprobing for hash aggregates.
Such a hash table behaves very poorly if keys are inserted in hash
order, which does in fact happen in the case where a query use a
Finalize HashAggregate node fed (via Gather) by a Partial
HashAggregate node. In fact, queries with this type of plan tend
to run effectively forever.
Fix that by seeding the hash value differently in each worker
(and in the leader, if it participates).
Andres Freund and Robert Haas
Table partitioning is like table inheritance and reuses much of the
existing infrastructure, but there are some important differences.
The parent is called a partitioned table and is always empty; it may
not have indexes or non-inherited constraints, since those make no
sense for a relation with no data of its own. The children are called
partitions and contain all of the actual data. Each partition has an
implicit partitioning constraint. Multiple inheritance is not
allowed, and partitioning and inheritance can't be mixed. Partitions
can't have extra columns and may not allow nulls unless the parent
does. Tuples inserted into the parent are automatically routed to the
correct partition, so tuple-routing ON INSERT triggers are not needed.
Tuple routing isn't yet supported for partitions which are foreign
tables, and it doesn't handle updates that cross partition boundaries.
Currently, tables can be range-partitioned or list-partitioned. List
partitioning is limited to a single column, but range partitioning can
involve multiple columns. A partitioning "column" can be an
expression.
Because table partitioning is less general than table inheritance, it
is hoped that it will be easier to reason about properties of
partitions, and therefore that this will serve as a better foundation
for a variety of possible optimizations, including query planner
optimizations. The tuple routing based which this patch does based on
the implicit partitioning constraints is an example of this, but it
seems likely that many other useful optimizations are also possible.
Amit Langote, reviewed and tested by Robert Haas, Ashutosh Bapat,
Amit Kapila, Rajkumar Raghuwanshi, Corey Huinker, Jaime Casanova,
Rushabh Lathia, Erik Rijkers, among others. Minor revisions by me.
So far the hashtable stored representative tuples in the form of its
input slot, with all columns in the hashtable that are not
needed (i.e. not grouped upon or functionally dependent) set to NULL.
Thats good for saving memory, but it turns out that having tuples full
of NULL isn't free. slot_deform_tuple is faster if there's no NULL
bitmap even if no NULLs are encountered, and skipping over leading NULLs
isn't free.
So compute a separate tuple descriptor that only contains the needed
columns. As columns have already been moved in/out the slot for the
hashtable that does not imply additional per-row overhead.
Author: Andres Freund
Reviewed-By: Heikki Linnakangas
Discussion: https://postgr.es/m/20161103110721.h5i5t5saxfk5eeik@alap3.anarazel.de
Previously we did a ExecProject() for each individual aggregate
argument. That turned out to be a performance bottleneck in queries with
multiple aggregates.
Doing all the argument computations in one ExecProject() is quite a bit
cheaper because ExecProject's fastpath can do the work at once in a
relatively tight loop, and because it can get all the required columns
with a single slot_getsomeattr and save some other redundant setup
costs.
Author: Andres Freund
Reviewed-By: Heikki Linnakangas
Discussion: https://postgr.es/m/20161103110721.h5i5t5saxfk5eeik@alap3.anarazel.de
The more efficient hashtable speeds up hash-aggregations with more than
a few hundred groups significantly. Improvements of over 120% have been
measured.
Due to the the different hash table queries that not fully
determined (e.g. GROUP BY without ORDER BY) may change their result
order.
The conversion is largely straight-forward, except that, due to the
static element types of simplehash.h type hashes, the additional data
some users store in elements (e.g. the per-group working data for hash
aggregaters) is now stored in TupleHashEntryData->additional. The
meaning of BuildTupleHashTable's entrysize (renamed to additionalsize)
has been changed to only be about the additionally stored size. That
size is only used for the initial sizing of the hash-table.
Reviewed-By: Tomas Vondra
Discussion: <20160727004333.r3e2k2y6fvk2ntup@alap3.anarazel.de>
lockdefs.h was only split from lock.h relatively recently, and
represents a minimal subset of the old lock.h. heapam.h only needs
that smaller subset, so adjust it to include only that. This requires
some corresponding adjustments elsewhere.
Peter Geoghegan
The original coding had three separate booleans representing partial
aggregation behavior, which was confusing, unreadable, and error-prone,
not least because the booleans weren't always listed in the same order.
It was also inadequate for the allegedly-desirable future extension to
support intermediate partial aggregation, because we'd need separate
markers for serialization and deserialization in such a case.
Merge these bools into an enum "AggSplit" to provide symbolic names for
the supported operating modes (and document what those are). By assigning
the values of the enum constants carefully, we can treat AggSplit values
as options bitmasks so that tests of what to do aren't noticeably more
expensive than before.
While at it, get rid of Aggref.aggoutputtype. That's not needed since
commit 59a3795c2 got rid of setrefs.c's special-purpose Aggref comparison
code, and it likewise seemed more confusing than helpful.
Assorted comment cleanup as well (there's still more that I want to do
in that line).
catversion bump for change in Aggref node contents. Should be the last
one for partial-aggregation changes.
Discussion: <29309.1466699160@sss.pgh.pa.us>
The previous display was sort of confusing, because it didn't
distinguish between the number of workers that we planned to launch
and the number that actually got launched. This has already confused
several people, so display both numbers and label them clearly.
Julien Rouhaud, reviewed by me.
Now indexes (but only B-tree for now) can contain "extra" column(s) which
doesn't participate in index structure, they are just stored in leaf
tuples. It allows to use index only scan by using single index instead
of two or more indexes.
Author: Anastasia Lubennikova with minor editorializing by me
Reviewers: David Rowley, Peter Geoghegan, Jeff Janes
This is necessary infrastructure for supporting parallel aggregation
for aggregates whose transition type is "internal". Such values
can't be passed between cooperating processes, because they are
just pointers.
David Rowley, reviewed by Tomas Vondra and by me.
Per discussion, the new extensible node framework is thought to be
better designed than the custom path/scan/scanstate stuff we added
in PostgreSQL 9.5. Rework the latter to be more like the former.
This is not backward-compatible, but we generally don't promise that
for C APIs, and there probably aren't many people using this yet
anyway.
KaiGai Kohei, reviewed by Petr Jelinek and me. Some further
cosmetic changes by me.
postgres_fdw can now sent an UPDATE or DELETE statement directly to
the foreign server in simple cases, rather than sending a SELECT FOR
UPDATE statement and then updating or deleting rows one-by-one.
Etsuro Fujita, reviewed by Rushabh Lathia, Shigeru Hanada, Kyotaro
Horiguchi, Albe Laurenz, Thom Brown, and me.
This patch widens SPI_processed, EState's es_processed field, PortalData's
portalPos field, FuncCallContext's call_cntr and max_calls fields,
ExecutorRun's count argument, PortalRunFetch's result, and the max number
of rows in a SPITupleTable to uint64, and deals with (I hope) all the
ensuing fallout. Some of these values were declared uint32 before, and
others "long".
I also removed PortalData's posOverflow field, since that logic seems
pretty useless given that portalPos is now always 64 bits.
The user-visible results are that command tags for SELECT etc will
correctly report tuple counts larger than 4G, as will plpgsql's GET
GET DIAGNOSTICS ... ROW_COUNT command. Queries processing more tuples
than that are still not exactly the norm, but they're becoming more
common.
Most values associated with FETCH/MOVE distances, such as PortalRun's count
argument and the count argument of most SPI functions that have one, remain
declared as "long". It's not clear whether it would be worth promoting
those to int64; but it would definitely be a large dollop of additional
API churn on top of this, and it would only help 32-bit platforms which
seem relatively less likely to see any benefit.
Andreas Scherbaum, reviewed by Christian Ullrich, additional hacking by me
This patch doesn't put the new infrastructure to use anywhere, and
indeed it's not clear how it could ever be used for something like
postgres_fdw which has to send an SQL query and wait for a reply,
but there might be FDWs or custom scan providers that are CPU-bound,
so let's give them a way to join club parallel.
KaiGai Kohei, reviewed by me.
Aggregate nodes now have two new modes: a "partial" mode where they
output the unfinalized transition state, and a "finalize" mode where
they accept unfinalized transition states rather than individual
values as input.
These new modes are not used anywhere yet, but they will be necessary
for parallel aggregation. The infrastructure also figures to be
useful for cases where we want to aggregate local data and remote
data via the FDW interface, and want to bring back partial aggregates
from the remote side that can then be combined with locally generated
partial aggregates to produce the final value. It may also be useful
even when neither FDWs nor parallelism are in play, as explained in
the comments in nodeAgg.c.
David Rowley and Simon Riggs, reviewed by KaiGai Kohei, Heikki
Linnakangas, Haribabu Kommi, and me.
The original parallel sequential scan commit included only very limited
changes to the EXPLAIN output. Aggregated totals from all workers were
displayed, but there was no way to see what each individual worker did
or to distinguish the effort made by the workers from the effort made by
the leader.
Per a gripe by Thom Brown (and maybe others). Patch by me, reviewed
by Amit Kapila.
In addition, this path fills in a number of missing bits and pieces in
the parallel infrastructure. Paths and plans now have a parallel_aware
flag indicating whether whatever parallel-aware logic they have should
be engaged. It is believed that we will need this flag for a number of
path/plan types, not just sequential scans, which is why the flag is
generic rather than part of the SeqScan structures specifically.
Also, execParallel.c now gives parallel nodes a chance to initialize
their PlanState nodes from the DSM during parallel worker startup.
Amit Kapila, with a fair amount of adjustment by me. Review of previous
patch versions by Haribabu Kommi and others.
Commit 4a4e6893aa, which introduced this
mechanism, failed to account for the fact that the RECORD pseudo-type
uses transient typmods that are only meaningful within a single
backend. Transferring such tuples without modification between two
cooperating backends does not work. This commit installs a system
for passing the tuple descriptors over the same shm_mq being used to
send the tuples themselves. The two sides might not assign the same
transient typmod to any given tuple descriptor, so we must also
substitute the appropriate receiver-side typmod for the one used by
the sender. That adds some CPU overhead, but still seems better than
being unable to pass records between cooperating parallel processes.
Along the way, move the logic for handling multiple tuple queues from
tqueue.c to nodeGather.c; tqueue.c now provides a TupleQueueReader,
which reads from a single queue, rather than a TupleQueueFunnel, which
potentially reads from multiple queues. This change was suggested
previously as a way to make sure that nodeGather.c rather than tqueue.c
had policy control over the order in which to read from queues, but
it wasn't clear to me until now how good an idea it was. typmod
mapping needs to be performed separately for each queue, and it is
much simpler if the tqueue.c code handles that and leaves multiplexing
multiple queues to higher layers of the stack.
The original Gather code failed to mark a Gather node as not able to
do projection, but it couldn't, even though it did call initialize its
projection info via ExecAssignProjectionInfo. There doesn't seem to
be any good reason for this node not to have projection capability,
so clean things up so that it does. Without this, plans using Gather
nodes might need to carry extra Result nodes to do projection.
In the previous coding, before returning from ExecutorRun, we'd shut
down all parallel workers. This was dead wrong if ExecutorRun was
called with a non-zero tuple count; it had the effect of truncating
the query output. To fix, give ExecutePlan control over whether to
enter parallel mode, and have it refuse to do so if the tuple count
is non-zero. Rewrite the Gather logic so that it can cope with being
called outside parallel mode.
Commit 7aea8e4f2d is largely to blame
for this problem, though this patch modifies some subsequently-committed
code which relied on the guarantees it purported to make.
This fixes a long-standing bug which was discovered while investigating
the interaction between the new join pushdown code and the EvalPlanQual
machinery: if a ForeignScan appears on the inner side of a paramaterized
nestloop, an EPQ recheck would re-return the original tuple even if
it no longer satisfied the pushed-down quals due to changed parameter
values.
This fix adds a new member to ForeignScan and ForeignScanState and a
new argument to make_foreignscan, and requires changes to FDWs which
push down quals to populate that new argument with a list of quals they
have chosen to push down. Therefore, I'm only back-patching to 9.5,
even though the bug is not new in 9.5.
Etsuro Fujita, reviewed by me and by Kyotaro Horiguchi.
A Gather executor node runs any number of copies of a plan in an equal
number of workers and merges all of the results into a single tuple
stream. It can also run the plan itself, if the workers are
unavailable or haven't started up yet. It is intended to work with
the Partial Seq Scan node which will be added in future commits.
It could also be used to implement parallel query of a different sort
by itself, without help from Partial Seq Scan, if the single_copy mode
is used. In that mode, a worker executes the plan, and the parallel
leader does not, merely collecting the worker's results. So, a Gather
node could be inserted into a plan to split the execution of that plan
across two processes. Nested Gather nodes aren't currently supported,
but we might want to add support for that in the future.
There's nothing in the planner to actually generate Gather nodes yet,
so it's not quite time to break out the champagne. But we're getting
close.
Amit Kapila. Some designs suggestions were provided by me, and I also
reviewed the patch. Single-copy mode, documentation, and other minor
changes also by me.
Per discussion, nowadays it is possible to have tablespaces that have
wildly different I/O characteristics from others. Setting different
effective_io_concurrency parameters for those has been measured to
improve performance.
Author: Julien Rouhaud
Reviewed by: Andres Freund
If there are two different aggregates in the query with same inputs, and
the aggregates have the same initial condition and transition function,
only calculate the state value once, and only call the final functions
separately. For example, AVG(x) and SUM(x) aggregates have the same
transition function, which accumulates the sum and number of input tuples.
For a query like "SELECT AVG(x), SUM(x) FROM x", we can therefore
accumulate the state function only once, which gives a nice speedup.
David Rowley, reviewed and edited by me.
The original implementation of TABLESAMPLE modeled the tablesample method
API on index access methods, which wasn't a good choice because, without
specialized DDL commands, there's no way to build an extension that can
implement a TSM. (Raw inserts into system catalogs are not an acceptable
thing to do, because we can't undo them during DROP EXTENSION, nor will
pg_upgrade behave sanely.) Instead adopt an API more like procedural
language handlers or foreign data wrappers, wherein the only SQL-level
support object needed is a single handler function identified by having
a special return type. This lets us get rid of the supporting catalog
altogether, so that no custom DDL support is needed for the feature.
Adjust the API so that it can support non-constant tablesample arguments
(the original coding assumed we could evaluate the argument expressions at
ExecInitSampleScan time, which is undesirable even if it weren't outright
unsafe), and discourage sampling methods from looking at invisible tuples.
Make sure that the BERNOULLI and SYSTEM methods are genuinely repeatable
within and across queries, as required by the SQL standard, and deal more
honestly with methods that can't support that requirement.
Make a full code-review pass over the tablesample additions, and fix
assorted bugs, omissions, infelicities, and cosmetic issues (such as
failure to put the added code stanzas in a consistent ordering).
Improve EXPLAIN's output of tablesample plans, too.
Back-patch to 9.5 so that we don't have to support the original API
in production.
Allow CustomPath to have a list of paths, CustomPlan a list of plans,
and CustomPlanState a list of planstates known to the core system, so
that custom path/plan providers can more reasonably use this
infrastructure for nodes with multiple children.
KaiGai Kohei, per a design suggestion from Tom Lane, with some
further kibitzing by me.
This SQL standard functionality allows to aggregate data by different
GROUP BY clauses at once. Each grouping set returns rows with columns
grouped by in other sets set to NULL.
This could previously be achieved by doing each grouping as a separate
query, conjoined by UNION ALLs. Besides being considerably more concise,
grouping sets will in many cases be faster, requiring only one scan over
the underlying data.
The current implementation of grouping sets only supports using sorting
for input. Individual sets that share a sort order are computed in one
pass. If there are sets that don't share a sort order, additional sort &
aggregation steps are performed. These additional passes are sourced by
the previous sort step; thus avoiding repeated scans of the source data.
The code is structured in a way that adding support for purely using
hash aggregation or a mix of hashing and sorting is possible. Sorting
was chosen to be supported first, as it is the most generic method of
implementation.
Instead of, as in an earlier versions of the patch, representing the
chain of sort and aggregation steps as full blown planner and executor
nodes, all but the first sort are performed inside the aggregation node
itself. This avoids the need to do some unusual gymnastics to handle
having to return aggregated and non-aggregated tuples from underlying
nodes, as well as having to shut down underlying nodes early to limit
memory usage. The optimizer still builds Sort/Agg node to describe each
phase, but they're not part of the plan tree, but instead additional
data for the aggregation node. They're a convenient and preexisting way
to describe aggregation and sorting. The first (and possibly only) sort
step is still performed as a separate execution step. That retains
similarity with existing group by plans, makes rescans fairly simple,
avoids very deep plans (leading to slow explains) and easily allows to
avoid the sorting step if the underlying data is sorted by other means.
A somewhat ugly side of this patch is having to deal with a grammar
ambiguity between the new CUBE keyword and the cube extension/functions
named cube (and rollup). To avoid breaking existing deployments of the
cube extension it has not been renamed, neither has cube been made a
reserved keyword. Instead precedence hacking is used to make GROUP BY
cube(..) refer to the CUBE grouping sets feature, and not the function
cube(). To actually group by a function cube(), unlikely as that might
be, the function name has to be quoted.
Needs a catversion bump because stored rules may change.
Author: Andrew Gierth and Atri Sharma, with contributions from Andres Freund
Reviewed-By: Andres Freund, Noah Misch, Tom Lane, Svenne Krap, Tomas
Vondra, Erik Rijkers, Marti Raudsepp, Pavel Stehule
Discussion: CAOeZVidmVRe2jU6aMk_5qkxnB7dfmPROzM7Ur8JPW5j8Y5X-Lw@mail.gmail.com
Add a TABLESAMPLE clause to SELECT statements that allows
user to specify random BERNOULLI sampling or block level
SYSTEM sampling. Implementation allows for extensible
sampling functions to be written, using a standard API.
Basic version follows SQLStandard exactly. Usable
concrete use cases for the sampling API follow in later
commits.
Petr Jelinek
Reviewed by Michael Paquier and Simon Riggs
The distance function can now set *recheck = false, like index quals. The
executor will then re-check the ORDER BY expressions, and use a queue to
reorder the results on the fly.
This makes it possible to do kNN-searches on polygons and circles, which
don't store the exact value in the index, but just a bounding box.
Alexander Korotkov and me
Previously, FDWs could only do "early row locking", that is lock a row as
soon as it's fetched, even though local restriction/join conditions might
discard the row later. This patch adds callbacks that allow FDWs to do
late locking in the same way that it's done for regular tables.
To make use of this feature, an FDW must support the "ctid" column as a
unique row identifier. Currently, since ctid has to be of type TID,
the feature is of limited use, though in principle it could be used by
postgres_fdw. We may eventually allow FDWs to specify another data type
for ctid, which would make it possible for more FDWs to use this feature.
This commit does not modify postgres_fdw to use late locking. We've
tested some prototype code for that, but it's not in committable shape,
and besides it's quite unclear whether it actually makes sense to do late
locking against a remote server. The extra round trips required are likely
to outweigh any benefit from improved concurrency.
Etsuro Fujita, reviewed by Ashutosh Bapat, and hacked up a lot by me
The newly added ON CONFLICT clause allows to specify an alternative to
raising a unique or exclusion constraint violation error when inserting.
ON CONFLICT refers to constraints that can either be specified using a
inference clause (by specifying the columns of a unique constraint) or
by naming a unique or exclusion constraint. DO NOTHING avoids the
constraint violation, without touching the pre-existing row. DO UPDATE
SET ... [WHERE ...] updates the pre-existing tuple, and has access to
both the tuple proposed for insertion and the existing tuple; the
optional WHERE clause can be used to prevent an update from being
executed. The UPDATE SET and WHERE clauses have access to the tuple
proposed for insertion using the "magic" EXCLUDED alias, and to the
pre-existing tuple using the table name or its alias.
This feature is often referred to as upsert.
This is implemented using a new infrastructure called "speculative
insertion". It is an optimistic variant of regular insertion that first
does a pre-check for existing tuples and then attempts an insert. If a
violating tuple was inserted concurrently, the speculatively inserted
tuple is deleted and a new attempt is made. If the pre-check finds a
matching tuple the alternative DO NOTHING or DO UPDATE action is taken.
If the insertion succeeds without detecting a conflict, the tuple is
deemed inserted.
To handle the possible ambiguity between the excluded alias and a table
named excluded, and for convenience with long relation names, INSERT
INTO now can alias its target table.
Bumps catversion as stored rules change.
Author: Peter Geoghegan, with significant contributions from Heikki
Linnakangas and Andres Freund. Testing infrastructure by Jeff Janes.
Reviewed-By: Heikki Linnakangas, Andres Freund, Robert Haas, Simon Riggs,
Dean Rasheed, Stephen Frost and many others.
The RLS capability is built on top of the WITH CHECK OPTION
system which was added for auto-updatable views, however, unlike
WCOs on views (which are mandated by the SQL spec to not fire until
after all other constraints and checks are done), it makes much more
sense for RLS checks to happen earlier than constraint and uniqueness
checks.
This patch reworks the structure which holds the WCOs a bit to be
explicitly either VIEW or RLS checks and the RLS-related checks are
done prior to the constraint and uniqueness checks. This also allows
better error reporting as we are now reporting when a violation is due
to a WITH CHECK OPTION and when it's due to an RLS policy violation,
which was independently noted by Craig Ringer as being confusing.
The documentation is also updated to include a paragraph about when RLS
WITH CHECK handling is performed, as there have been a number of
questions regarding that and the documentation was previously silent on
the matter.
Author: Dean Rasheed, with some kabitzing and comment changes by me.
Foreign tables can now be inheritance children, or parents. Much of the
system was already ready for this, but we had to fix a few things of
course, mostly in the area of planner and executor handling of row locks.
As side effects of this, allow foreign tables to have NOT VALID CHECK
constraints (and hence to accept ALTER ... VALIDATE CONSTRAINT), and to
accept ALTER SET STORAGE and ALTER SET WITH/WITHOUT OIDS. Continuing to
disallow these things would've required bizarre and inconsistent special
cases in inheritance behavior. Since foreign tables don't enforce CHECK
constraints anyway, a NOT VALID one is a complete no-op, but that doesn't
mean we shouldn't allow it. And it's possible that some FDWs might have
use for SET STORAGE or SET WITH OIDS, though doubtless they will be no-ops
for most.
An additional change in support of this is that when a ModifyTable node
has multiple target tables, they will all now be explicitly identified
in EXPLAIN output, for example:
Update on pt1 (cost=0.00..321.05 rows=3541 width=46)
Update on pt1
Foreign Update on ft1
Foreign Update on ft2
Update on child3
-> Seq Scan on pt1 (cost=0.00..0.00 rows=1 width=46)
-> Foreign Scan on ft1 (cost=100.00..148.03 rows=1170 width=46)
-> Foreign Scan on ft2 (cost=100.00..148.03 rows=1170 width=46)
-> Seq Scan on child3 (cost=0.00..25.00 rows=1200 width=46)
This was done mainly to provide an unambiguous place to attach "Remote SQL"
fields, but it is useful for inherited updates even when no foreign tables
are involved.
Shigeru Hanada and Etsuro Fujita, reviewed by Ashutosh Bapat and Kyotaro
Horiguchi, some additional hacking by me
Previously, we cached domain constraints for the life of a query, or
really for the life of the FmgrInfo struct that was used to invoke
domain_in() or domain_check(). But plpgsql (and probably other places)
are set up to cache such FmgrInfos for the whole lifespan of a session,
which meant they could be enforcing really stale sets of constraints.
On the other hand, searching pg_constraint once per query gets kind of
expensive too: testing says that as much as half the runtime of a
trivial query such as "SELECT 0::domaintype" went into that.
To fix this, delegate the responsibility for tracking a domain's
constraints to the typcache, which has the infrastructure needed to
detect syscache invalidation events that signal possible changes.
This not only removes unnecessary repeat reads of pg_constraint,
but ensures that we never apply stale constraint data: whatever we
use is the current data according to syscache rules.
Unfortunately, the current configuration of the system catalogs means
we have to flush cached domain-constraint data whenever either pg_type
or pg_constraint changes, which happens rather a lot (eg, creation or
deletion of a temp table will do it). It might be worth rearranging
things to split pg_constraint into two catalogs, of which the domain
constraint one would probably be very low-traffic. That's a job for
another patch though, and in any case this patch should improve matters
materially even with that handicap.
This patch makes use of the recently-added memory context reset callback
feature to manage the lifespan of domain constraint caches, so that we
don't risk deleting a cache that might be in the midst of evaluation.
Although this is a bug fix as well as a performance improvement, no
back-patch. There haven't been many if any field complaints about
stale domain constraint checks, so it doesn't seem worth taking the
risk of modifying data structures as basic as MemoryContexts in back
branches.
Make it work more like FDW plans do: instead of assuming that there are
expressions in a CustomScan plan node that the core code doesn't know
about, insist that all subexpressions that need planner attention be in
a "custom_exprs" list in the Plan representation. (Of course, the
custom plugin can break the list apart again at executor initialization.)
This lets us revert the parts of the patch that exposed setrefs.c and
subselect.c processing to the outside world.
Also revert the GetSpecialCustomVar stuff in ruleutils.c; that concept
may work in future, but it's far from fully baked right now.
There seems no prospect that any of this will ever be useful, and indeed
it's questionable whether some of it would work if it ever got called;
it's certainly not been exercised in a very long time, if ever. So let's
get rid of it, and make the comments about mark/restore in execAmi.c less
wishy-washy.
The mark/restore support for Result nodes is also currently dead code,
but that's due to planner limitations not because it's impossible that
it could be useful. So I left it in.
Get rid of the pernicious entanglement between planner and executor headers
introduced by commit 0b03e5951b.
Also, rearrange the CustomFoo struct/typedef definitions so that all the
typedef names are seen as used by the compiler. Without this pgindent
will mess things up a bit, which is not so important perhaps, but it also
removes a bizarre discrepancy between the declaration arrangement used for
CustomExecMethods and that used for CustomScanMethods and
CustomPathMethods.
Clean up the commentary around ExecSupportsMarkRestore to reflect the
rather large change in its API.
Const-ify register_custom_path_provider's argument. This necessitates
casting away const in the function, but that seems better than forcing
callers of the function to do so (or else not const-ify their method
pointer structs, which was sort of the whole point).
De-export fix_expr_common. I don't like the exporting of fix_scan_expr
or replace_nestloop_params either, but this one surely has got little
excuse.
At one time it wasn't terribly important what column names were associated
with the fields of a composite Datum, but since the introduction of
operations like row_to_json(), it's important that looking up the rowtype
ID embedded in the Datum returns the column names that users would expect.
That did not work terribly well before this patch: you could get the column
names of the underlying table, or column aliases from any level of the
query, depending on minor details of the plan tree. You could even get
totally empty field names, which is disastrous for cases like row_to_json().
To fix this for whole-row Vars, look to the RTE referenced by the Var, and
make sure its column aliases are applied to the rowtype associated with
the result Datums. This is a tad scary because we might have to return
a transient RECORD type even though the Var is declared as having some
named rowtype. In principle it should be all right because the record
type will still be physically compatible with the named rowtype; but
I had to weaken one Assert in ExecEvalConvertRowtype, and there might be
third-party code containing similar assumptions.
Similarly, RowExprs have to be willing to override the column names coming
from a named composite result type and produce a RECORD when the column
aliases visible at the site of the RowExpr differ from the underlying
table's column names.
In passing, revert the decision made in commit 398f70ec07 to add
an alias-list argument to ExecTypeFromExprList: better to provide that
functionality in a separate function. This also reverts most of the code
changes in d685814835, which we don't need because we're no longer
depending on the tupdesc found in the child plan node's result slot to be
blessed.
Back-patch to 9.4, but not earlier, since this solution changes the results
in some cases that users might not have realized were buggy. We'll apply a
more restricted form of this patch in older branches.
This allows extension modules to define their own methods for
scanning a relation, and get the core code to use them. It's
unclear as yet how much use this capability will find, but we
won't find out if we never commit it.
KaiGai Kohei, reviewed at various times and in various levels
of detail by Shigeru Hanada, Tom Lane, Andres Freund, Álvaro
Herrera, and myself.
This clause changes the behavior of SELECT locking clauses in the
presence of locked rows: instead of causing a process to block waiting
for the locks held by other processes (or raise an error, with NOWAIT),
SKIP LOCKED makes the new reader skip over such rows. While this is not
appropriate behavior for general purposes, there are some cases in which
it is useful, such as queue-like tables.
Catalog version bumped because this patch changes the representation of
stored rules.
Reviewed by Craig Ringer (based on a previous attempt at an
implementation by Simon Riggs, who also provided input on the syntax
used in the current patch), David Rowley, and Álvaro Herrera.
Author: Thomas Munro
ExecMakeTableFunctionResult evaluated the arguments for a function-in-FROM
in the query-lifespan memory context. This is insignificant in simple
cases where the function relation is scanned only once; but if the function
is in a sub-SELECT or is on the inside of a nested loop, any memory
consumed during argument evaluation can add up quickly. (The potential for
trouble here had been foreseen long ago, per existing comments; but we'd
not previously seen a complaint from the field about it.) To fix, create
an additional temporary context just for this purpose.
Per an example from MauMau. Back-patch to all active branches.
This SQL-standard feature allows a sub-SELECT yielding multiple columns
(but only one row) to be used to compute the new values of several columns
to be updated. While the same results can be had with an independent
sub-SELECT per column, such a workaround can require a great deal of
duplicated computation.
The standard actually says that the source for a multi-column assignment
could be any row-valued expression. The implementation used here is
tightly tied to our existing sub-SELECT support and can't handle other
cases; the Bison grammar would have some issues with them too. However,
I don't feel too bad about this since other cases can be converted into
sub-SELECTs. For instance, "SET (a,b,c) = row_valued_function(x)" could
be written "SET (a,b,c) = (SELECT * FROM row_valued_function(x))".
Until now, when executing an aggregate function as a window function
within a window with moving frame start (that is, any frame start mode
except UNBOUNDED PRECEDING), we had to recalculate the aggregate from
scratch each time the frame head moved. This patch allows an aggregate
definition to include an alternate "moving aggregate" implementation
that includes an inverse transition function for removing rows from
the aggregate's running state. As long as this can be done successfully,
runtime is proportional to the total number of input rows, rather than
to the number of input rows times the average frame length.
This commit includes the core infrastructure, documentation, and regression
tests using user-defined aggregates. Follow-on commits will update some
of the built-in aggregates to use this feature.
David Rowley and Florian Pflug, reviewed by Dean Rasheed; additional
hacking by me
This patch introduces generic support for ordered-set and hypothetical-set
aggregate functions, as well as implementations of the instances defined in
SQL:2008 (percentile_cont(), percentile_disc(), rank(), dense_rank(),
percent_rank(), cume_dist()). We also added mode() though it is not in the
spec, as well as versions of percentile_cont() and percentile_disc() that
can compute multiple percentile values in one pass over the data.
Unlike the original submission, this patch puts full control of the sorting
process in the hands of the aggregate's support functions. To allow the
support functions to find out how they're supposed to sort, a new API
function AggGetAggref() is added to nodeAgg.c. This allows retrieval of
the aggregate call's Aggref node, which may have other uses beyond the
immediate need. There is also support for ordered-set aggregates to
install cleanup callback functions, so that they can be sure that
infrastructure such as tuplesort objects gets cleaned up.
In passing, make some fixes in the recently-added support for variadic
aggregates, and make some editorial adjustments in the recent FILTER
additions for aggregates. Also, simplify use of IsBinaryCoercible() by
allowing it to succeed whenever the target type is ANY or ANYELEMENT.
It was inconsistent that it dealt with other polymorphic target types
but not these.
Atri Sharma and Andrew Gierth; reviewed by Pavel Stehule and Vik Fearing,
and rather heavily editorialized upon by Tom Lane
Robert Haas
Andres Freund
Peter Eisentraut
Tom Lane
Andrew Gierth
Magnus Hagander
Bruce Momjian
Kevin Grittner
Alvaro Herrera
Teodor Sigaev
Heikki Linnakangas
Simon Riggs
Stephen Frost