Also enable this for postgres_fdw.
Etsuro Fujita, based on an earlier patch by Amit Langote. The larger
patch series of which this is a part has been reviewed by Amit
Langote, David Fetter, Maksim Milyutin, Álvaro Herrera, Stephen Frost,
and me. Minor documentation changes to the final version by me.
Discussion: http://postgr.es/m/29906a26-da12-8c86-4fb9-d8f88442f2b9@lab.ntt.co.jp
MERGE performs actions that modify rows in the target table
using a source table or query. MERGE provides a single SQL
statement that can conditionally INSERT/UPDATE/DELETE rows
a task that would other require multiple PL statements.
e.g.
MERGE INTO target AS t
USING source AS s
ON t.tid = s.sid
WHEN MATCHED AND t.balance > s.delta THEN
UPDATE SET balance = t.balance - s.delta
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED AND s.delta > 0 THEN
INSERT VALUES (s.sid, s.delta)
WHEN NOT MATCHED THEN
DO NOTHING;
MERGE works with regular and partitioned tables, including
column and row security enforcement, as well as support for
row, statement and transition triggers.
MERGE is optimized for OLTP and is parameterizable, though
also useful for large scale ETL/ELT. MERGE is not intended
to be used in preference to existing single SQL commands
for INSERT, UPDATE or DELETE since there is some overhead.
MERGE can be used statically from PL/pgSQL.
MERGE does not yet support inheritance, write rules,
RETURNING clauses, updatable views or foreign tables.
MERGE follows SQL Standard per the most recent SQL:2016.
Includes full tests and documentation, including full
isolation tests to demonstrate the concurrent behavior.
This version written from scratch in 2017 by Simon Riggs,
using docs and tests originally written in 2009. Later work
from Pavan Deolasee has been both complex and deep, leaving
the lead author credit now in his hands.
Extensive discussion of concurrency from Peter Geoghegan,
with thanks for the time and effort contributed.
Various issues reported via sqlsmith by Andreas Seltenreich
Authors: Pavan Deolasee, Simon Riggs
Reviewer: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs
Discussion:
https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.comhttps://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
Performing JIT compilation for deforming gains performance benefits
over unJITed deforming from compile-time knowledge of the tuple
descriptor. Fixed column widths, NOT NULLness, etc can be taken
advantage of.
Right now the JITed deforming is only used when deforming tuples as
part of expression evaluation (and obviously only if the descriptor is
known). It's likely to be beneficial in other cases, too.
By default tuple deforming is JITed whenever an expression is JIT
compiled. There's a separate boolean GUC controlling it, but that's
expected to be primarily useful for development and benchmarking.
Docs will follow in a later commit containing docs for the whole JIT
feature.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
Commit eb7ed3f306 enabled unique constraints on partitioned tables,
but one thing that was not working properly is INSERT/ON CONFLICT.
This commit introduces a new node keeps state related to the ON CONFLICT
clause per partition, and fills it when that partition is about to be
used for tuple routing.
Author: Amit Langote, Álvaro Herrera
Reviewed-by: Etsuro Fujita, Pavan Deolasee
Discussion: https://postgr.es/m/20180228004602.cwdyralmg5ejdqkq@alvherre.pgsql
For any interesting JIT target, fields inside structs need to be
accessed. b96d550e contains infrastructure for syncing the definition
of types between postgres C code and runtime code generation with
LLVM. But that doesn't sync the number or names of fields inside
structs, just the types (including padding etc).
One option would be to hardcode the offset numbers in the JIT code,
but that'd be hard to keep in sync. Instead add macros indicating the
field offset to the fields that need to be accessed. Not pretty, but
manageable.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
This adds simple cost based plan time decision about whether JIT
should be performed. jit_above_cost, jit_optimize_above_cost are
compared with the total cost of a plan, and if the cost is above them
JIT is performed / optimization is performed respectively.
For that PlannedStmt and EState have a jitFlags (es_jit_flags) field
that stores information about what JIT operations should be performed.
EState now also has a new es_jit field, which can store a
JitContext. When there are no errors the context is released in
standard_ExecutorEnd().
It is likely that the default values for jit_[optimize_]above_cost
will need to be adapted further, but in my test these values seem to
work reasonably.
Author: Andres Freund, with feedback by Peter Eisentraut
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
These values can be obtained from the ModifyTable node which is already
a part of both the ModifyTableState and ExecInsert.
Author: Álvaro Herrera, Amit Langote
Reviewed-by: Peter Geoghegan
Discussion: https://postgr.es/m/20180316151303.rml2p5wffn3o6qy6@alvherre.pgsql
We make some changes to ModifyTableState and the EState it uses whenever
we route tuples to partitions; but we weren't restoring properly in all
cases, possibly causing crashes when partitions with different tuple
descriptors are targeted by tuples inserted in the same command.
Refactor some code, creating ExecPrepareTupleRouting, to encapsulate the
needed state changing logic, and have it invoked one level above its
current place (ie. put it in ExecModifyTable instead of ExecInsert);
this makes it all more readable.
Add a test case to exercise this.
We don't support having views as partitions; and since only views can
have INSTEAD OF triggers, there is no point in testing for INSTEAD OF
when processing insertions into a partitioned table. Remove code that
appears to support this (but which is actually never relevant.)
In passing, fix location of some very confusing comments in
ModifyTableState.
Reported-by: Amit Langote
Author: Etsuro Fujita, Amit Langote
Discussion: https://postgr/es/m/0473bf5c-57b1-f1f7-3d58-455c2230bc5f@lab.ntt.co.jp
This has a performance benefit on own, although not hugely so. The
primary benefit is that it will allow for to JIT tuple deforming and
comparator invocations.
Large parts of this were previously committed (773aec7aa), but the
commit contained an omission around cross-type comparisons and was
thus reverted.
Author: Andres Freund
Discussion: https://postgr.es/m/20171129080934.amqqkke2zjtekd4t@alap3.anarazel.de
This reverts commit 773aec7aa9.
There's an unresolved issue in the reverted commit: It only creates
one comparator function, but in for the nodeSubplan.c case we need
more (c.f. FindTupleHashEntry vs LookupTupleHashEntry calls in
nodeSubplan.c).
This isn't too difficult to fix, but it's not entirely trivial
either. The fact that the issue only causes breakage on 32bit systems
shows that the current test coverage isn't that great. To avoid
turning half the buildfarm red till those two issues are addressed,
revert.
Doing so causes EXPLAIN ANALYZE to show trigger statistics multiple
times. Commit 2f17844104 seems to
be to blame for this.
Amit Langote, revieed by Amit Khandekar, Etsuro Fujita, and me.
This patch adds the ability to use "RANGE offset PRECEDING/FOLLOWING"
frame boundaries in window functions. We'd punted on that back in the
original patch to add window functions, because it was not clear how to
do it in a reasonably data-type-extensible fashion. That problem is
resolved here by adding the ability for btree operator classes to provide
an "in_range" support function that defines how to add or subtract the
RANGE offset value. Factoring it this way also allows the operator class
to avoid overflow problems near the ends of the datatype's range, if it
wishes to expend effort on that. (In the committed patch, the integer
opclasses handle that issue, but it did not seem worth the trouble to
avoid overflow failures for datetime types.)
The patch includes in_range support for the integer_ops opfamily
(int2/int4/int8) as well as the standard datetime types. Support for
other numeric types has been requested, but that seems like suitable
material for a follow-on patch.
In addition, the patch adds GROUPS mode which counts the offset in
ORDER-BY peer groups rather than rows, and it adds the frame_exclusion
options specified by SQL:2011. As far as I can see, we are now fully
up to spec on window framing options.
Existing behaviors remain unchanged, except that I changed the errcode
for a couple of existing error reports to meet the SQL spec's expectation
that negative "offset" values should be reported as SQLSTATE 22013.
Internally and in relevant parts of the documentation, we now consistently
use the terminology "offset PRECEDING/FOLLOWING" rather than "value
PRECEDING/FOLLOWING", since the term "value" is confusingly vague.
Oliver Ford, reviewed and whacked around some by me
Discussion: https://postgr.es/m/CAGMVOdu9sivPAxbNN0X+q19Sfv9edEPv=HibOJhB14TJv_RCQg@mail.gmail.com
To make this work, tuplesort.c and logtape.c must also support
parallelism, so this patch adds that infrastructure and then applies
it to the particular case of parallel btree index builds. Testing
to date shows that this can often be 2-3x faster than a serial
index build.
The model for deciding how many workers to use is fairly primitive
at present, but it's better than not having the feature. We can
refine it as we get more experience.
Peter Geoghegan with some help from Rushabh Lathia. While Heikki
Linnakangas is not an author of this patch, he wrote other patches
without which this feature would not have been possible, and
therefore the release notes should possibly credit him as an author
of this feature. Reviewed by Claudio Freire, Heikki Linnakangas,
Thomas Munro, Tels, Amit Kapila, me.
Discussion: http://postgr.es/m/CAM3SWZQKM=Pzc=CAHzRixKjp2eO5Q0Jg1SoFQqeXFQ647JiwqQ@mail.gmail.com
Discussion: http://postgr.es/m/CAH2-Wz=AxWqDoVvGU7dq856S4r6sJAj6DBn7VMtigkB33N5eyg@mail.gmail.com
When an UPDATE causes a row to no longer match the partition
constraint, try to move it to a different partition where it does
match the partition constraint. In essence, the UPDATE is split into
a DELETE from the old partition and an INSERT into the new one. This
can lead to surprising behavior in concurrency scenarios because
EvalPlanQual rechecks won't work as they normally did; the known
problems are documented. (There is a pending patch to improve the
situation further, but it needs more review.)
Amit Khandekar, reviewed and tested by Amit Langote, David Rowley,
Rajkumar Raghuwanshi, Dilip Kumar, Amul Sul, Thomas Munro, Álvaro
Herrera, Amit Kapila, and me. A few final revisions by me.
Discussion: http://postgr.es/m/CAJ3gD9do9o2ccQ7j7+tSgiE1REY65XRiMb=yJO3u3QhyP8EEPQ@mail.gmail.com
When CREATE INDEX is run on a partitioned table, create catalog entries
for an index on the partitioned table (which is just a placeholder since
the table proper has no data of its own), and recurse to create actual
indexes on the existing partitions; create them in future partitions
also.
As a convenience gadget, if the new index definition matches some
existing index in partitions, these are picked up and used instead of
creating new ones. Whichever way these indexes come about, they become
attached to the index on the parent table and are dropped alongside it,
and cannot be dropped on isolation unless they are detached first.
To support pg_dump'ing these indexes, add commands
CREATE INDEX ON ONLY <table>
(which creates the index on the parent partitioned table, without
recursing) and
ALTER INDEX ATTACH PARTITION
(which is used after the indexes have been created individually on each
partition, to attach them to the parent index). These reconstruct prior
database state exactly.
Reviewed-by: (in alphabetical order) Peter Eisentraut, Robert Haas, Amit
Langote, Jesper Pedersen, Simon Riggs, David Rowley
Discussion: https://postgr.es/m/20171113170646.gzweigyrgg6pwsg4@alvherre.pgsql
Previously aggregate transition and combination functions were invoked
by special case code in nodeAgg.c, evaluating input and filters
separately using the expression evaluation machinery. That turns out
to not be great for performance for several reasons:
- repeated expression evaluations have some cost
- the transition functions invocations are poorly predicted, as
commonly there are multiple aggregates in a query, resulting in the
same call-stack invoking different functions.
- filter and input computation had to be done separately
- the special case code made it hard to implement JITing of the whole
transition function invocation
Address this by building one large expression that computes input,
evaluates filters, and invokes transition functions.
This leads to moderate speedups in queries bottlenecked by aggregate
computations, and enables large speedups for similar cases once JITing
is done.
There's potential for further improvement:
- It'd be nice if we could simplify the somewhat expensive
aggstate->all_pergroups lookups.
- right now there's still an advance_transition_function invocation in
nodeAgg.c, leading to some code duplication.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
Instead of having ExecSetupPartitionTupleRouting return multiple out
parameters, have it return a pointer to a structure containing all of
those different things. Also, provide and use a cleanup function,
ExecCleanupTupleRouting, instead of cleaning up all of the resources
allocated by ExecSetupPartitionTupleRouting individually.
Amit Khandekar, reviewed by Amit Langote, David Rowley, and me
Discussion: http://postgr.es/m/CAJ3gD9fWfxgKC+PfJZF3hkgAcNOy-LpfPxVYitDEXKHjeieWQQ@mail.gmail.com
- Remove unnecessary #include mistakenly added in execnodes.h.
- Fix mistake in comment in choose_next_subplan_for_leader.
- Adjust row estimates in cost_append for a possibly-different
parallel divisor.
- Clamp row estimates in cost_append after operations that may
not produce integers.
Amit Kapila, with cosmetic adjustments by me.
Discussion: http://postgr.es/m/CAA4eK1+qcbeai3coPpRW=GFCzFeLUsuY4T-AKHqMjxpEGZBPQg@mail.gmail.com
Previously aggregate transition values for hash and other forms of
aggregation (i.e. sort and no group by) were represented
differently. Hash based aggregation used a grouping set indexed array
pointing to an array of transition values, whereas other forms of
aggregation used one flattened array with the index being computed out
of grouping set and transition offsets.
That made upcoming changes hard, so represent both as grouping set
indexed array of per-group data.
As a nice side-effect this also makes aggregation slightly faster,
because computing offsets with `transno + (setno * numTrans)` turns
out not to be that cheap (too big for x86 lea for example).
Author: Andres Freund
Discussion: https://postgr.es/m/20171128003121.nmxbm2ounxzb6n2t@alap3.anarazel.de
This reduces code duplication a bit, but the primary benefit that it
makes JITing expression evaluation easier. When doing so we can't, as
previously done in the interpreted case, really change opcode without
recompiling. Nor dow we just carry around unnecessary branches to
avoid re-checking over and over.
As a minor side-effect this makes ExecEvalStepOp() O(log(N)) rather
than O(N).
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
This patch does three interrelated things:
* Create a new expression execution step type EEOP_PARAM_CALLBACK
and add the infrastructure needed for add-on modules to generate that.
As discussed, the best control mechanism for that seems to be to add
another hook function to ParamListInfo, which will be called by
ExecInitExpr if it's supplied and a PARAM_EXTERN Param is found.
For stand-alone expressions, we add a new entry point to allow the
ParamListInfo to be specified directly, since it can't be retrieved
from the parent plan node's EState.
* Redesign the API for the ParamListInfo paramFetch hook so that the
ParamExternData array can be entirely virtual. This also lets us get rid
of ParamListInfo.paramMask, instead leaving it to the paramFetch hook to
decide which param IDs should be accessible or not. plpgsql_param_fetch
was already doing the identical masking check, so having callers do it too
seemed redundant. While I was at it, I added a "speculative" flag to
paramFetch that the planner can specify as TRUE to avoid unwanted failures.
This solves an ancient problem for plpgsql that it couldn't provide values
of non-DTYPE_VAR variables to the planner for fear of triggering premature
"record not assigned yet" or "field not found" errors during planning.
* Rework plpgsql to get rid of the need for "unshared" parameter lists,
by dint of turning the single ParamListInfo per estate into a nearly
read-only data structure that doesn't instantiate any per-variable data.
Instead, the paramFetch hook controls access to per-variable data and can
make the right decisions on the fly, replacing the cases that we used to
need multiple ParamListInfos for. This might perhaps have been a
performance loss on its own, but by using a paramCompile hook we can
bypass plpgsql_param_fetch entirely during normal query execution.
(It's now only called when, eg, we copy the ParamListInfo into a cursor
portal. copyParamList() or SerializeParamList() effectively instantiate
the virtual parameter array as a simple physical array without a
paramFetch hook, which is what we want in those cases.) This allows
reverting most of commit 6c82d8d1f, though I kept the cosmetic
code-consolidation aspects of that (eg the assign_simple_var function).
Performance testing shows this to be at worst a break-even change,
and it can provide wins ranging up to 20% in test cases involving
accesses to fields of "record" variables. The fact that values of
such variables can now be exposed to the planner might produce wins
in some situations, too, but I've not pursued that angle.
In passing, remove the "parent" pointer from the arguments to
ExecInitExprRec and related functions, instead storing that pointer in a
transient field in ExprState. The ParamListInfo pointer for a stand-alone
expression is handled the same way; we'd otherwise have had to add
yet another recursively-passed-down argument in expression compilation.
Discussion: https://postgr.es/m/32589.1513706441@sss.pgh.pa.us
Introduce parallel-aware hash joins that appear in EXPLAIN plans as Parallel
Hash Join with Parallel Hash. While hash joins could already appear in
parallel queries, they were previously always parallel-oblivious and had a
partial subplan only on the outer side, meaning that the work of the inner
subplan was duplicated in every worker.
After this commit, the planner will consider using a partial subplan on the
inner side too, using the Parallel Hash node to divide the work over the
available CPU cores and combine its results in shared memory. If the join
needs to be split into multiple batches in order to respect work_mem, then
workers process different batches as much as possible and then work together
on the remaining batches.
The advantages of a parallel-aware hash join over a parallel-oblivious hash
join used in a parallel query are that it:
* avoids wasting memory on duplicated hash tables
* avoids wasting disk space on duplicated batch files
* divides the work of building the hash table over the CPUs
One disadvantage is that there is some communication between the participating
CPUs which might outweigh the benefits of parallelism in the case of small
hash tables. This is avoided by the planner's existing reluctance to supply
partial plans for small scans, but it may be necessary to estimate
synchronization costs in future if that situation changes. Another is that
outer batch 0 must be written to disk if multiple batches are required.
A potential future advantage of parallel-aware hash joins is that right and
full outer joins could be supported, since there is a single set of matched
bits for each hashtable, but that is not yet implemented.
A new GUC enable_parallel_hash is defined to control the feature, defaulting
to on.
Author: Thomas Munro
Reviewed-By: Andres Freund, Robert Haas
Tested-By: Rafia Sabih, Prabhat Sahu
Discussion:
https://postgr.es/m/CAEepm=2W=cOkiZxcg6qiFQP-dHUe09aqTrEMM7yJDrHMhDv_RA@mail.gmail.comhttps://postgr.es/m/CAEepm=37HKyJ4U6XOLi=JgfSHM3o6B-GaeO-6hkOmneTDkH+Uw@mail.gmail.com
When we create an Append node, we can spread out the workers over the
subplans instead of piling on to each subplan one at a time, which
should typically be a bit more efficient, both because the startup
cost of any plan executed entirely by one worker is paid only once and
also because of reduced contention. We can also construct Append
plans using a mix of partial and non-partial subplans, which may allow
for parallelism in places that otherwise couldn't support it.
Unfortunately, this patch doesn't handle the important case of
parallelizing UNION ALL by running each branch in a separate worker;
the executor infrastructure is added here, but more planner work is
needed.
Amit Khandekar, Robert Haas, Amul Sul, reviewed and tested by
Ashutosh Bapat, Amit Langote, Rafia Sabih, Amit Kapila, and
Rajkumar Raghuwanshi.
Discussion: http://postgr.es/m/CAJ3gD9dy0K_E8r727heqXoBmWZ83HwLFwdcaSSmBQ1+S+vRuUQ@mail.gmail.com
If a 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.
Robert Haas
Simon Riggs
Andres Freund
Alvaro Herrera
Tom Lane
Bruce Momjian
Peter Eisentraut
Andrew Gierth
Magnus Hagander
Kevin Grittner
Teodor Sigaev
Heikki Linnakangas