The previous coding here supposed that if run-time partitioning applied to
a particular Append/MergeAppend plan, then all child plans of that node
must be members of a single partitioning hierarchy. This is totally wrong,
since an Append could be formed from a UNION ALL: we could have multiple
hierarchies sharing the same Append, or child plans that aren't part of any
hierarchy.
To fix, restructure the related plan-time and execution-time data
structures so that we can have a separate list or array for each
partitioning hierarchy. Also track subplans that are not part of any
hierarchy, and make sure they don't get pruned.
Per reports from Phil Florent and others. Back-patch to v11, since
the bug originated there.
David Rowley, with a lot of cosmetic adjustments by me; thanks also
to Amit Langote for review.
Discussion: https://postgr.es/m/HE1PR03MB17068BB27404C90B5B788BCABA7B0@HE1PR03MB1706.eurprd03.prod.outlook.com
CopyFrom allows multi-inserts to be used for non-partitioned tables, but
this was disabled for partitioned tables. The reason for this appeared
to be that the tuple may not belong to the same partition as the
previous tuple did. Not allowing multi-inserts here greatly slowed down
imports into partitioned tables. These could take twice as long as a
copy to an equivalent non-partitioned table. It seems wise to do
something about this, so this change allows the multi-inserts by
flushing the so-far inserted tuples to the partition when the next tuple
does not belong to the same partition, or when the buffer fills. This
improves performance when the next tuple in the stream commonly belongs
to the same partition as the previous tuple.
In cases where the target partition changes on every tuple, using
multi-inserts slightly slows the performance. To get around this we
track the average size of the batches that have been inserted and
adaptively enable or disable multi-inserts based on the size of the
batch. Some testing was done and the regression only seems to exist
when the average size of the insert batch is close to 1, so let's just
enable multi-inserts when the average size is at least 1.3. More
performance testing might reveal a better number for, this, but since
the slowdown was only 1-2% it does not seem critical enough to spend too
much time calculating it. In any case it may depend on other factors
rather than just the size of the batch.
Allowing multi-inserts for partitions required a bit of work around the
per-tuple memory contexts as we must flush the tuples when the next
tuple does not belong the same partition. In which case there is no
good time to reset the per-tuple context, as we've already built the new
tuple by this time. In order to work around this we maintain two
per-tuple contexts and just switch between them every time the partition
changes and reset the old one. This does mean that the first of each
batch of tuples is not allocated in the same memory context as the
others, but that does not matter since we only reset the context once
the previous batch has been inserted.
Author: David Rowley <david.rowley@2ndquadrant.com>
Reviewed-by: Melanie Plageman <melanieplageman@gmail.com>
The previous coding saved pointers into the partitioned table's relcache
entry, but then closed the relcache entry, causing those pointers to
nominally become dangling. Actual trouble would be seen in the field
only if a relcache flush occurred mid-query, but that's hardly out of
the question.
While we could fix this by copying all the data in question at query
start, it seems better to just hold the relcache entry open for the
whole query.
While at it, improve the handling of support-function lookups: do that
once per query not once per pruning test. There's still something to be
desired here, in that we fail to exploit the possibility of caching data
across queries in the fn_extra fields of the relcache's FmgrInfo structs,
which could happen if we just used those structs in-place rather than
copying them. However, combining that with the possibility of per-query
lookups of cross-type comparison functions seems to require changes in the
APIs of a lot of the pruning support functions, so it's too invasive to
consider as part of this patch. A win would ensue only for complex
partition key data types (e.g. arrays), so it may not be worth the
trouble.
David Rowley and Tom Lane
Discussion: https://postgr.es/m/17850.1528755844@sss.pgh.pa.us
Starting with commit f0e44751d7, ExecConstraints was in charge of
running the partition constraint; commit 19c47e7c82 modified that so
that caller could request to skip that checking depending on some
conditions, but that commit and 15ce775faa together introduced a small
bug there which caused ExecInsert to request skipping the constraint
check but have this not be honored -- in effect doing the check twice.
This could have been fixed in a very small patch, but on further
analysis of the involved function and its callsites, it turns out to be
simpler to give the responsibility of checking the partition constraint
fully to the caller, and return ExecConstraints to its original
(pre-partitioning) shape where it only checked tuple descriptor-related
constraints. Each caller must do partition constraint checking on its
own schedule, which is more convenient after commit 2f17844104 anyway.
Reported-by: David Rowley
Author: David Rowley, Álvaro Herrera
Reviewed-by: Amit Langote, Amit Khandekar, Simon Riggs
Discussion: https://postgr.es/m/CAKJS1f8w8+awsxgea8wt7_UX8qzOQ=Tm1LD+U1fHqBAkXxkW2w@mail.gmail.com
The initial coding of the run-time-pruning feature only coped with cases
where the partition key(s) are compared to Params. That is a bit silly;
we can allow it to work with any non-Var-containing stable expression, as
long as we take special care with expressions containing PARAM_EXEC Params.
The code is hardly any longer this way, and it's considerably clearer
(IMO at least). Per gripe from Pavel Stehule.
David Rowley, whacked around a bit by me
Discussion: https://postgr.es/m/CAFj8pRBjrufA3ocDm8o4LPGNye9Y+pm1b9kCwode4X04CULG3g@mail.gmail.com
Since the SPI stack has been moved from TopTransactionContext to
TopMemoryContext, setting _SPI_stack to NULL in AtEOXact_SPI() leaks
memory. In fact, we don't need to do that anymore: We just leave the
allocated stack around for the next SPI use.
Also, refactor the SPI cleanup so that it is run both at transaction end
and when returning to the main loop on an exception. The latter is
necessary when a procedure calls a COMMIT or ROLLBACK command that
itself causes an error.
This reverts commits d204ef6377,
83454e3c2b and a few more commits thereafter
(complete list at the end) related to MERGE feature.
While the feature was fully functional, with sufficient test coverage and
necessary documentation, it was felt that some parts of the executor and
parse-analyzer can use a different design and it wasn't possible to do that in
the available time. So it was decided to revert the patch for PG11 and retry
again in the future.
Thanks again to all reviewers and bug reporters.
List of commits reverted, in reverse chronological order:
f1464c5380 Improve parse representation for MERGE
ddb4158579 MERGE syntax diagram correction
530e69e59b Allow cpluspluscheck to pass by renaming variable
01b88b4df5 MERGE minor errata
3af7b2b0d4 MERGE fix variable warning in non-assert builds
a5d86181ec MERGE INSERT allows only one VALUES clause
4b2d44031f MERGE post-commit review
4923550c20 Tab completion for MERGE
aa3faa3c7a WITH support in MERGE
83454e3c2b New files for MERGE
d204ef6377 MERGE SQL Command following SQL:2016
Author: Pavan Deolasee
Reviewed-by: Michael Paquier
The HeapFetches counter was using a simple value in IndexOnlyScanState,
which fails to propagate values from parallel workers; so the counts are
wrong when IndexOnlyScan runs in parallel. Move it to Instrumentation,
like all the other counters.
While at it, change INSERT ON CONFLICT conflicting tuple counter to use
the new ntuples2 instead of nfiltered2, which is a blatant misuse.
Discussion: https://postgr.es/m/20180409215851.idwc75ct2bzi6tea@alvherre.pgsql
Existing partition pruning is only able to work at plan time, for query
quals that appear in the parsed query. This is good but limiting, as
there can be parameters that appear later that can be usefully used to
further prune partitions.
This commit adds support for pruning subnodes of Append which cannot
possibly contain any matching tuples, during execution, by evaluating
Params to determine the minimum set of subnodes that can possibly match.
We support more than just simple Params in WHERE clauses. Support
additionally includes:
1. Parameterized Nested Loop Joins: The parameter from the outer side of the
join can be used to determine the minimum set of inner side partitions to
scan.
2. Initplans: Once an initplan has been executed we can then determine which
partitions match the value from the initplan.
Partition pruning is performed in two ways. When Params external to the plan
are found to match the partition key we attempt to prune away unneeded Append
subplans during the initialization of the executor. This allows us to bypass
the initialization of non-matching subplans meaning they won't appear in the
EXPLAIN or EXPLAIN ANALYZE output.
For parameters whose value is only known during the actual execution
then the pruning of these subplans must wait. Subplans which are
eliminated during this stage of pruning are still visible in the EXPLAIN
output. In order to determine if pruning has actually taken place, the
EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never
executed due to the elimination of the partition then the execution
timing area will state "(never executed)". Whereas, if, for example in
the case of parameterized nested loops, the number of loops stated in
the EXPLAIN ANALYZE output for certain subplans may appear lower than
others due to the subplan having been scanned fewer times. This is due
to the list of matching subnodes having to be evaluated whenever a
parameter which was found to match the partition key changes.
This commit required some additional infrastructure that permits the
building of a data structure which is able to perform the translation of
the matching partition IDs, as returned by get_matching_partitions, into
the list index of a subpaths list, as exist in node types such as
Append, MergeAppend and ModifyTable. This allows us to translate a list
of clauses into a Bitmapset of all the subpath indexes which must be
included to satisfy the clause list.
Author: David Rowley, based on an earlier effort by Beena Emerson
Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi,
Jesper Pedersen
Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
When an update moves a row between partitions (supported since
2f17844104), our normal logic for following update chains in READ
COMMITTED mode doesn't work anymore. Cross partition updates are
modeled as an delete from the old and insert into the new
partition. No ctid chain exists across partitions, and there's no
convenient space to introduce that link.
Not throwing an error in a partitioned context when one would have
been thrown without partitioning is obviously problematic. This commit
introduces infrastructure to detect when a tuple has been moved, not
just plainly deleted. That allows to throw an error when encountering
a deletion that's actually a move, while attempting to following a
ctid chain.
The row deleted as part of a cross partition update is marked by
pointing it's t_ctid to an invalid block, instead of self as a normal
update would. That was deemed to be the least invasive and most
future proof way to represent the knowledge, given how few infomask
bits are there to be recycled (there's also some locking issues with
using infomask bits).
External code following ctid chains should be updated to check for
moved tuples. The most likely consequence of not doing so is a missed
error.
Author: Amul Sul, editorialized by me
Reviewed-By: Amit Kapila, Pavan Deolasee, Andres Freund, Robert Haas
Discussion: http://postgr.es/m/CAAJ_b95PkwojoYfz0bzXU8OokcTVGzN6vYGCNVUukeUDrnF3dw@mail.gmail.com
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
Review comments from Andres Freund
* Consolidate code into AfterTriggerGetTransitionTable()
* Rename nodeMerge.c to execMerge.c
* Rename nodeMerge.h to execMerge.h
* Move MERGE handling in ExecInitModifyTable()
into a execMerge.c ExecInitMerge()
* Move mt_merge_subcommands flags into execMerge.h
* Rename opt_and_condition to opt_merge_when_and_condition
* Wordsmith various comments
Author: Pavan Deolasee
Reviewer: Simon Riggs
MERGE performs actions that modify rows in the target table
using a source table or query. MERGE provides a single SQL
statement that can conditionally INSERT/UPDATE/DELETE rows
a task that would other require multiple PL statements.
e.g.
MERGE INTO target AS t
USING source AS s
ON t.tid = s.sid
WHEN MATCHED AND t.balance > s.delta THEN
UPDATE SET balance = t.balance - s.delta
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED AND s.delta > 0 THEN
INSERT VALUES (s.sid, s.delta)
WHEN NOT MATCHED THEN
DO NOTHING;
MERGE works with regular and partitioned tables, including
column and row security enforcement, as well as support for
row, statement and transition triggers.
MERGE is optimized for OLTP and is parameterizable, though
also useful for large scale ETL/ELT. MERGE is not intended
to be used in preference to existing single SQL commands
for INSERT, UPDATE or DELETE since there is some overhead.
MERGE can be used statically from PL/pgSQL.
MERGE does not yet support inheritance, write rules,
RETURNING clauses, updatable views or foreign tables.
MERGE follows SQL Standard per the most recent SQL:2016.
Includes full tests and documentation, including full
isolation tests to demonstrate the concurrent behavior.
This version written from scratch in 2017 by Simon Riggs,
using docs and tests originally written in 2009. Later work
from Pavan Deolasee has been both complex and deep, leaving
the lead author credit now in his hands.
Extensive discussion of concurrency from Peter Geoghegan,
with thanks for the time and effort contributed.
Various issues reported via sqlsmith by Andreas Seltenreich
Authors: Pavan Deolasee, Simon Riggs
Reviewer: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs
Discussion:
https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.comhttps://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
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
Reviewers: 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
So far, a nested CALL or DO in PL/pgSQL would not establish a context
where transaction control statements were allowed. This fixes that by
handling CALL and DO specially in PL/pgSQL, passing the atomic/nonatomic
execution context through and doing the required management around
transaction boundaries.
Reviewed-by: Tomas Vondra <tomas.vondra@2ndquadrant.com>
Instead using memset to set tts_isnull, call the new
slot_getmissingattrs().
Also fix a bug (= instead of >=) in the code generation. Normally = is
correct, but when repeatedly deforming fields not in a
tuple (e.g. deform up to natts + 1 and then natts + 2) >= is needed.
Discussion: https://postgr.es/m/20180328010053.i2qvsuuusst4lgmc@alap3.anarazel.de
Performing JIT compilation for deforming gains performance benefits
over unJITed deforming from compile-time knowledge of the tuple
descriptor. Fixed column widths, NOT NULLness, etc can be taken
advantage of.
Right now the JITed deforming is only used when deforming tuples as
part of expression evaluation (and obviously only if the descriptor is
known). It's likely to be beneficial in other cases, too.
By default tuple deforming is JITed whenever an expression is JIT
compiled. There's a separate boolean GUC controlling it, but that's
expected to be primarily useful for development and benchmarking.
Docs will follow in a later commit containing docs for the whole JIT
feature.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
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
"UPDATE/DELETE WHERE CURRENT OF cursor_name" failed, with an error message
like "cannot extract system attribute from virtual tuple", if the cursor
was using a index-only scan for the target table. Fix it by digging the
current TID out of the indexscan state.
It seems likely that the same failure could occur for CustomScan plans
and perhaps some FDW plan types, so that leaving this to be treated as an
internal error with an obscure message isn't as good an idea as it first
seemed. Hence, add a bit of heaptuple.c infrastructure to let us deliver
a more on-topic message. I chose to make the message match what you get
for the case where execCurrentOf can't identify the target scan node at
all, "cursor "foo" is not a simply updatable scan of table "bar"".
Perhaps it should be different, but we can always adjust that later.
In the future, it might be nice to provide hooks that would let custom
scan providers and/or FDWs deal with this in other ways; but that's
not a suitable topic for a back-patchable bug fix.
It's been like this all along, so back-patch to all supported branches.
Yugo Nagata and Tom Lane
Discussion: https://postgr.es/m/20180201013349.937dfc5f.nagata@sraoss.co.jp
In a top-level CALL, the values of INOUT arguments will be returned as a
result row. In PL/pgSQL, the values are assigned back to the input
arguments. In other languages, the same convention as for return a
record from a function is used. That does not require any code changes
in the PL implementations.
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
It's not necessary to fully initialize the executor data structures
for partitions to which no tuples are ever routed. Consider, for
example, an INSERT statement that inserts only one row: it only cares
about the partition to which that one row is routed. The new function
ExecInitPartitionInfo performs the initialization in question only
when a particular partition is about to receive a tuple. This includes
creating, validating, and saving a pointer to the ResultRelInfo,
setting up for speculative insertions, translating WCOs and
initializing the resulting expressions, translating returning lists
and building the appropriate projection information, and setting up a
tuple conversion map.
One thing that's not deferred is locking the child partitions; that
seems desirable but would need more thought. Still, testing shows
that this makes single-row inserts significantly faster on a table
with many partitions without harming the bulk-insert case.
Amit Langote, reviewed by Etsuro Fujita, with a few changes by me
Discussion: http://postgr.es/m/8975331d-d961-cbdd-f862-fdd3d97dc2d0@lab.ntt.co.jp
Previously tts_off was, for unknown reasons, of type long. For one
that's unnecessary as tuples are restricted in length, for another
long would be a bad choice of type even if that weren't the case, as
it's not reliably wider than an int. Also HeapTupleHeader->t_len is a
uint32.
This is split off from a larger patch implementing JITed tuple
deforming. Seems like an independent improvement, as tiny as it is.
Author: Andres Freund
The reason for doing so is that it will allow expression evaluation to
optimize based on the underlying tupledesc. In particular it will
allow to JIT tuple deforming together with the expression itself.
For that expression initialization needs to be moved after the
relevant slots are initialized - mostly unproblematic, except in the
case of nodeWorktablescan.c.
After doing so there's no need for ExecAssignResultType() and
ExecAssignResultTypeFromTL() anymore, as all former callers have been
converted to create a slot with a fixed descriptor.
When creating a slot with a fixed descriptor, tts_values/isnull can be
allocated together with the main slot, reducing allocation overhead
and increasing cache density a bit.
Author: Andres Freund
Discussion: https://postgr.es/m/20171206093717.vqdxe5icqttpxs3p@alap3.anarazel.de
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.
It's a common task to evaluate a qual and reset the corresponding
expression context. Currently that requires storing the result of the
qual eval, resetting the context, and then reacting on the result. As
that's awkward several places only reset the context next time through
a node. That's not great, so introduce a helper that evaluates and
resets.
It's a bit ugly that it currently uses MemoryContextReset() instead of
ResetExprContext(), but that seems easier than reordering all of
executor.h.
Author: Andres Freund
Discussion: https://postgr.es/m/20180109222544.f7loxrunqh3xjl5f@alap3.anarazel.de
In each of the supplied procedural languages (PL/pgSQL, PL/Perl,
PL/Python, PL/Tcl), add language-specific commit and rollback
functions/commands to control transactions in procedures in that
language. Add similar underlying functions to SPI. Some additional
cleanup so that transaction commit or abort doesn't blow away data
structures still used by the procedure call. Add execution context
tracking to CALL and DO statements so that transaction control commands
can only be issued in top-level procedure and block calls, not function
calls or other procedure or block calls.
- SPI
Add a new function SPI_connect_ext() that is like SPI_connect() but
allows passing option flags. The only option flag right now is
SPI_OPT_NONATOMIC. A nonatomic SPI connection can execute transaction
control commands, otherwise it's not allowed. This is meant to be
passed down from CALL and DO statements which themselves know in which
context they are called. A nonatomic SPI connection uses different
memory management. A normal SPI connection allocates its memory in
TopTransactionContext. For nonatomic connections we use PortalContext
instead. As the comment in SPI_connect_ext() (previously SPI_connect())
indicates, one could potentially use PortalContext in all cases, but it
seems safest to leave the existing uses alone, because this stuff is
complicated enough already.
SPI also gets new functions SPI_start_transaction(), SPI_commit(), and
SPI_rollback(), which can be used by PLs to implement their transaction
control logic.
- portalmem.c
Some adjustments were made in the code that cleans up portals at
transaction abort. The portal code could already handle a command
*committing* a transaction and continuing (e.g., VACUUM), but it was not
quite prepared for a command *aborting* a transaction and continuing.
In AtAbort_Portals(), remove the code that marks an active portal as
failed. As the comment there already predicted, this doesn't work if
the running command wants to keep running after transaction abort. And
it's actually not necessary, because pquery.c is careful to run all
portal code in a PG_TRY block and explicitly runs MarkPortalFailed() if
there is an exception. So the code in AtAbort_Portals() is never used
anyway.
In AtAbort_Portals() and AtCleanup_Portals(), we need to be careful not
to clean up active portals too much. This mirrors similar code in
PreCommit_Portals().
- PL/Perl
Gets new functions spi_commit() and spi_rollback()
- PL/pgSQL
Gets new commands COMMIT and ROLLBACK.
Update the PL/SQL porting example in the documentation to reflect that
transactions are now possible in procedures.
- PL/Python
Gets new functions plpy.commit and plpy.rollback.
- PL/Tcl
Gets new commands commit and rollback.
Reviewed-by: Andrew Dunstan <andrew.dunstan@2ndquadrant.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
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
At present, we always raise an ERROR if the partition constraint
is violated, but a pending patch for UPDATE tuple routing will
consider instead moving the tuple to the correct partition.
Refactor to make that simpler.
Amit Khandekar, reviewed by Amit Langote, David Rowley, and me.
Discussion: http://postgr.es/m/CAJ3gD9cue54GbEzfV-61nyGpijvjZgCcghvLsB0_nL8Nm8HzCA@mail.gmail.com
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
The previous coding relied (without any documentation) on the data[]
member of HashMemoryChunkData being at a MAXALIGN'ed offset. If it
was not, the tuples would not be maxaligned either, leading to failures
on alignment-picky machines. While there seems to be no live bug on any
platform we support, this is clearly pretty fragile: any addition to or
rearrangement of the fields in HashMemoryChunkData could break it.
Let's remove the hazard by getting rid of the data[] member and instead
using pointer arithmetic with an explicitly maxalign'ed offset.
Discussion: https://postgr.es/m/14483.1514938129@sss.pgh.pa.us
In a race case, EXPLAIN ANALYZE could fail to display correct nbatch
and size information. Refactor so that participants report only on
batches they worked on rather than trying to report on all of them,
and teach explain.c to consider the HashInstrumentation object from
all participants instead of picking the first one it can find. This
should fix an occasional build farm failure in the "join" regression
test.
Author: Thomas Munro
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/30219.1514428346%40sss.pgh.pa.us
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
Tom Lane
Peter Eisentraut
Alvaro Herrera
Bruce Momjian
Simon Riggs
Andres Freund
Robert Haas