50e17ad28 increased the size of ExprEvalStep from 64 bytes up to 88 bytes.
Lots of effort was spent during the development of the current expression
evaluation code to make an instance of this struct as small as possible.
Making this struct larger than needed reduces CPU cache efficiency during
expression evaluation which causes noticeable slowdowns during query
execution.
In order to reduce the size of the struct, here we remove the fn_addr
field. The values from this field can be obtained via fcinfo, just with
some extra pointer dereferencing. The extra indirection does not seem to
cause any noticeable slowdowns.
Various other fields have been moved into the ScalarArrayOpExprHashTable
struct. These fields are only used when the ScalarArrayOpExprHashTable
pointer has already been dereferenced, so no additional pointer
dereferences occur for these. Here we also make hash_fcinfo_data the last
field in ScalarArrayOpExprHashTable so that we can avoid a further pointer
dereference to get the FunctionCallInfoBaseData. This also saves a call to
palloc().
50e17ad28 was added in 14, but it's too late to adjust the size of the
ExprEvalStep in that version, so here we just backpatch to 15, which is
currently in beta.
Author: Andres Freund, David Rowley
Discussion: https://postgr.es/m/20220616233130.rparivafipt6doj3@alap3.anarazel.de
Backpatch-through: 15
The new expression step types increased the size of ExprEvalStep by ~4 for all
types of expression steps, slowing down expression evaluation noticeably. Move
them out of line.
There's other issues with these expression steps, but addressing them is
largely independent of this aspect.
Author: Andres Freund <andres@anarazel.de>
Reviewed-By: Andrew Dunstan <andrew@dunslane.net>
Discussion: https://postgr.es/m/20220616233130.rparivafipt6doj3@alap3.anarazel.de
Backpatch: 15-
Previously, the output of EXPLAIN (BUFFERS) option showed only the I/O
timing spent reading and writing shared and local buffers. This commit
adds on top of that the I/O timing for temporary buffers in the output
of EXPLAIN (for spilled external sorts, hashes, materialization. etc).
This can be helpful for users in cases where the I/O related to
temporary buffers is the bottleneck.
Like its cousin, this information is available only when track_io_timing
is enabled. Playing the patch, this is showing an extra overhead of up
to 1% even when using gettimeofday() as implementation for interval
timings, which is slightly within the usual range noise still that's
measurable.
Author: Masahiko Sawada
Reviewed-by: Georgios Kokolatos, Melanie Plageman, Julien Rouhaud,
Ranier Vilela
Discussion: https://postgr.es/m/CAD21AoAJgotTeP83p6HiAGDhs_9Fw9pZ2J=_tYTsiO5Ob-V5GQ@mail.gmail.com
Modify the subroutines called by RI trigger functions that want to check
if a given referenced value exists in the referenced relation to simply
scan the foreign key constraint's unique index, instead of using SPI to
execute
SELECT 1 FROM referenced_relation WHERE ref_key = $1
This saves a lot of work, especially when inserting into or updating a
referencing relation.
This rewrite allows to fix a PK row visibility bug caused by a partition
descriptor hack which requires ActiveSnapshot to be set to come up with
the correct set of partitions for the RI query running under REPEATABLE
READ isolation. We now set that snapshot indepedently of the snapshot
to be used by the PK index scan, so the two no longer interfere. The
buggy output in src/test/isolation/expected/fk-snapshot.out of the
relevant test case added by commit 00cb86e75d has been corrected.
(The bug still exists in branch 14, however, but this fix is too
invasive to backpatch.)
Author: Amit Langote <amitlangote09@gmail.com>
Reviewed-by: Kyotaro Horiguchi <horikyota.ntt@gmail.com>
Reviewed-by: Corey Huinker <corey.huinker@gmail.com>
Reviewed-by: Li Japin <japinli@hotmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Zhihong Yu <zyu@yugabyte.com>
Discussion: https://postgr.es/m/CA+HiwqGkfJfYdeq5vHPh6eqPKjSbfpDDY+j-kXYFePQedtSLeg@mail.gmail.com
* Move the execution pruning initialization steps that are common
between both ExecInitAppend() and ExecInitMergeAppend() into a new
function ExecInitPartitionPruning() defined in execPartition.c.
Those steps include creation of a PartitionPruneState to be used for
all instances of pruning and determining the minimal set of child
subplans that need to be initialized by performing initial pruning if
needed, and finally adjusting the subplan_map arrays in the
PartitionPruneState to reflect the new set of subplans remaining
after initial pruning if it was indeed performed.
ExecCreatePartitionPruneState() is no longer exported out of
execPartition.c and has been renamed to CreatePartitionPruneState()
as a local sub-routine of ExecInitPartitionPruning().
* Likewise, ExecFindInitialMatchingSubPlans() that was in charge of
performing initial pruning no longer needs to be exported. In fact,
since it would now have the same body as the more generally named
ExecFindMatchingSubPlans(), except differing in the value of
initial_prune passed to the common subroutine
find_matching_subplans_recurse(), it seems better to remove it and add
an initial_prune argument to ExecFindMatchingSubPlans().
* Add an ExprContext field to PartitionPruneContext to remove the
implicit assumption in the runtime pruning code that the ExprContext to
use to compute pruning expressions that need one can always rely on the
PlanState providing it. A future patch will allow runtime pruning (at
least the initial pruning steps) to be performed without the
corresponding PlanState yet having been created, so this will help.
Author: Amit Langote <amitlangote09@gmail.com>
Discussion: https://postgr.es/m/CA+HiwqEYCpEqh2LMDOp9mT+4-QoVe8HgFMKBjntEMCTZLpcCCA@mail.gmail.com
This feature allows jsonb data to be treated as a table and thus used in
a FROM clause like other tabular data. Data can be selected from the
jsonb using jsonpath expressions, and hoisted out of nested structures
in the jsonb to form multiple rows, more or less like an outer join.
Nikita Glukhov
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zhihong Yu (whose
name I previously misspelled), Himanshu Upadhyaya, Daniel Gustafsson,
Justin Pryzby.
Discussion: https://postgr.es/m/7e2cb85d-24cf-4abb-30a5-1a33715959bd@postgrespro.ru
This Patch introduces three SQL standard JSON functions:
JSON() (incorrectly mentioned in my commit message for f4fb45d15c)
JSON_SCALAR()
JSON_SERIALIZE()
JSON() produces json values from text, bytea, json or jsonb values, and
has facilitites for handling duplicate keys.
JSON_SCALAR() produces a json value from any scalar sql value, including
json and jsonb.
JSON_SERIALIZE() produces text or bytea from input which containis or
represents json or jsonb;
For the most part these functions don't add any significant new
capabilities, but they will be of use to users wanting standard
compliant JSON handling.
Nikita Glukhov
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zihong Yu,
Himanshu Upadhyaya, Daniel Gustafsson, Justin Pryzby.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
This introduces the SQL/JSON functions for querying JSON data using
jsonpath expressions. The functions are:
JSON_EXISTS()
JSON_QUERY()
JSON_VALUE()
All of these functions only operate on jsonb. The workaround for now is
to cast the argument to jsonb.
JSON_EXISTS() tests if the jsonpath expression applied to the jsonb
value yields any values. JSON_VALUE() must return a single value, and an
error occurs if it tries to return multiple values. JSON_QUERY() must
return a json object or array, and there are various WRAPPER options for
handling scalar or multi-value results. Both these functions have
options for handling EMPTY and ERROR conditions.
Nikita Glukhov
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zihong Yu,
Himanshu Upadhyaya, Daniel Gustafsson, Justin Pryzby.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
This patch intrdocuces the SQL standard IS JSON predicate. It operates
on text and bytea values representing JSON as well as on the json and
jsonb types. Each test has an IS and IS NOT variant. The tests are:
IS JSON [VALUE]
IS JSON ARRAY
IS JSON OBJECT
IS JSON SCALAR
IS JSON WITH | WITHOUT UNIQUE KEYS
These are mostly self-explanatory, but note that IS JSON WITHOUT UNIQUE
KEYS is true whenever IS JSON is true, and IS JSON WITH UNIQUE KEYS is
true whenever IS JSON is true except it IS JSON OBJECT is true and there
are duplicate keys (which is never the case when applied to jsonb values).
Nikita Glukhov
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zihong Yu,
Himanshu Upadhyaya, Daniel Gustafsson, Justin Pryzby.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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 otherwise
require multiple PL statements. For example,
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 tables, partitioned tables and inheritance
hierarchies, including column and row security enforcement, as well as
support for row and statement triggers and transition tables therein.
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 from PL/pgSQL.
MERGE does not support targetting updatable views or foreign tables, and
RETURNING clauses are not allowed either. These limitations are likely
fixable with sufficient effort. Rewrite rules are also not supported,
but it's not clear that we'd want to support them.
Author: Pavan Deolasee <pavan.deolasee@gmail.com>
Author: Álvaro Herrera <alvherre@alvh.no-ip.org>
Author: Amit Langote <amitlangote09@gmail.com>
Author: Simon Riggs <simon.riggs@enterprisedb.com>
Reviewed-by: Peter Eisentraut <peter.eisentraut@enterprisedb.com>
Reviewed-by: Andres Freund <andres@anarazel.de> (earlier versions)
Reviewed-by: Peter Geoghegan <pg@bowt.ie> (earlier versions)
Reviewed-by: Robert Haas <robertmhaas@gmail.com> (earlier versions)
Reviewed-by: Japin Li <japinli@hotmail.com>
Reviewed-by: Justin Pryzby <pryzby@telsasoft.com>
Reviewed-by: Tomas Vondra <tomas.vondra@enterprisedb.com>
Reviewed-by: Zhihong Yu <zyu@yugabyte.com>
Discussion: https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.com
Discussion: https://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
Discussion: https://postgr.es/m/20201231134736.GA25392@alvherre.pgsql
This patch introduces the SQL/JSON standard constructors for JSON:
JSON()
JSON_ARRAY()
JSON_ARRAYAGG()
JSON_OBJECT()
JSON_OBJECTAGG()
For the most part these functions provide facilities that mimic
existing json/jsonb functions. However, they also offer some useful
additional functionality. In addition to text input, the JSON() function
accepts bytea input, which it will decode and constuct a json value from.
The other functions provide useful options for handling duplicate keys
and null values.
This series of patches will be followed by a consolidated documentation
patch.
Nikita Glukhov
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zihong Yu,
Himanshu Upadhyaya, Daniel Gustafsson, Justin Pryzby.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
When an update on a partitioned table referenced in foreign key
constraints causes a row to move from one partition to another,
the fact that the move is implemented as a delete followed by an insert
on the target partition causes the foreign key triggers to have
surprising behavior. For example, a given foreign key's delete trigger
which implements the ON DELETE CASCADE clause of that key will delete
any referencing rows when triggered for that internal DELETE, although
it should not, because the referenced row is simply being moved from one
partition of the referenced root partitioned table into another, not
being deleted from it.
This commit teaches trigger.c to skip queuing such delete trigger events
on the leaf partitions in favor of an UPDATE event fired on the root
target relation. Doing so is sensible because both the old and the new
tuple "logically" belong to the root relation.
The after trigger event queuing interface now allows passing the source
and the target partitions of a particular cross-partition update when
registering the update event for the root partitioned table. Along with
the two ctids of the old and the new tuple, the after trigger event now
also stores the OIDs of those partitions. The tuples fetched from the
source and the target partitions are converted into the root table
format, if necessary, before they are passed to the trigger function.
The implementation currently has a limitation that only the foreign keys
pointing into the query's target relation are considered, not those of
its sub-partitioned partitions. That seems like a reasonable
limitation, because it sounds rare to have distinct foreign keys
pointing to sub-partitioned partitions instead of to the root table.
This misbehavior stems from commit f56f8f8da6 (which added support for
foreign keys to reference partitioned tables) not paying sufficient
attention to commit 2f17844104 (which had introduced cross-partition
updates a year earlier). Even though the former commit goes back to
Postgres 12, we're not backpatching this fix at this time for fear of
destabilizing things too much, and because there are a few ABI breaks in
it that we'd have to work around in older branches. It also depends on
commit f4566345cf, which had its own share of backpatchability issues
as well.
Author: Amit Langote <amitlangote09@gmail.com>
Reviewed-by: Masahiko Sawada <sawada.mshk@gmail.com>
Reviewed-by: Álvaro Herrera <alvherre@alvh.no-ip.org>
Reported-by: Eduard Català <eduard.catala@gmail.com>
Discussion: https://postgr.es/m/CA+HiwqFvkBCmfwkQX_yBqv2Wz8ugUGiBDxum8=WvVbfU1TXaNg@mail.gmail.com
Discussion: https://postgr.es/m/CAL54xNZsLwEM1XCk5yW9EqaRzsZYHuWsHQkA2L5MOSKXAwviCQ@mail.gmail.com
SPI_commit previously left it up to the caller to recover from any error
occurring during commit. Since that's complicated and requires use of
low-level xact.c facilities, it's not too surprising that no caller got
it right. Let's move the responsibility for cleanup into spi.c. Doing
that requires redefining SPI_commit as starting a new transaction, so
that it becomes equivalent to SPI_commit_and_chain except that you get
default transaction characteristics instead of preserving the prior
transaction's characteristics. We can make this pretty transparent
API-wise by redefining SPI_start_transaction() as a no-op. Callers
that expect to do something in between might be surprised, but
available evidence is that no callers do so.
Having made that API redefinition, we can fix this mess by having
SPI_commit[_and_chain] trap errors and start a new, clean transaction
before re-throwing the error. Likewise for SPI_rollback[_and_chain].
Some cleanup is also needed in AtEOXact_SPI, which was nowhere near
smart enough to deal with SPI contexts nested inside a committing
context.
While plperl and pltcl need no changes beyond removing their now-useless
SPI_start_transaction() calls, plpython needs some more work because it
hadn't gotten the memo about catching commit/rollback errors in the
first place. Such an error resulted in longjmp'ing out of the Python
interpreter, which leaks Python stack entries at present and is reported
to crash Python 3.11 altogether. Add the missing logic to catch such
errors and convert them into Python exceptions.
We are probably going to have to back-patch this once Python 3.11 ships,
but it's a sufficiently basic change that I'm a bit nervous about doing
so immediately. Let's let it bake awhile in HEAD first.
Peter Eisentraut and Tom Lane
Discussion: https://postgr.es/m/3375ffd8-d71c-2565-e348-a597d6e739e3@enterprisedb.com
Discussion: https://postgr.es/m/17416-ed8fe5d7213d6c25@postgresql.org
Prior to v14, we insisted that the query in RETURN QUERY be of a type
that returns tuples. (For instance, INSERT RETURNING was allowed,
but not plain INSERT.) That happened indirectly because we opened a
cursor for the query, so spi.c checked SPI_is_cursor_plan(). As a
consequence, the error message wasn't terribly on-point, but at least
it was there.
Commit 2f48ede08 lost this detail. Instead, plain RETURN QUERY
insisted that the query be a SELECT (by checking for SPI_OK_SELECT)
while RETURN QUERY EXECUTE failed to check the query type at all.
Neither of these changes was intended.
The only convenient place to check this in the EXECUTE case is inside
_SPI_execute_plan, because we haven't done parse analysis until then.
So we need to pass down a flag saying whether to enforce that the
query returns tuples. Fortunately, we can squeeze another boolean
into struct SPIExecuteOptions without an ABI break, since there's
padding space there. (It's unlikely that any extensions would
already be using this new struct, but preserving ABI in v14 seems
like a smart idea anyway.)
Within spi.c, it seemed like _SPI_execute_plan's parameter list
was already ridiculously long, and I didn't want to make it longer.
So I thought of passing SPIExecuteOptions down as-is, allowing that
parameter list to become much shorter. This makes the patch a bit
more invasive than it might otherwise be, but it's all internal to
spi.c, so that seems fine.
Per report from Marc Bachmann. Back-patch to v14 where the
faulty code came in.
Discussion: https://postgr.es/m/1F2F75F0-27DF-406F-848D-8B50C7EEF06A@gmail.com
Up to now the size of a query's rangetable has been limited by the
constants INNER_VAR et al, which mustn't be equal to any real
rangetable index. 65000 doubtless seemed like enough for anybody,
and it still is orders of magnitude larger than the number of joins
we can realistically handle. However, we need a rangetable entry
for each child partition that is (or might be) processed by a query.
Queries with a few thousand partitions are getting more realistic,
so that the day when that limit becomes a problem is in sight,
even if it's not here yet. Hence, let's raise the limit.
Rather than just increase the values of INNER_VAR et al, this patch
adopts the approach of making them small negative values, so that
rangetables could theoretically become as long as INT_MAX.
The bulk of the patch is concerned with changing Var.varno and some
related variables from "Index" (unsigned int) to plain "int". This
is basically cosmetic, with little actual effect other than to help
debuggers print their values nicely. As such, I've only bothered
with changing places that could actually see INNER_VAR et al, which
the parser and most of the planner don't. We do have to be careful
in places that are performing less/greater comparisons on varnos,
but there are very few such places, other than the IS_SPECIAL_VARNO
macro itself.
A notable side effect of this patch is that while it used to be
possible to add INNER_VAR et al to a Bitmapset, that will now
draw an error. I don't see any likelihood that it wouldn't be a
bug to include these fake varnos in a bitmapset of real varnos,
so I think this is all to the good.
Although this touches outfuncs/readfuncs, I don't think a catversion
bump is required, since stored rules would never contain Vars
with these fake varnos.
Andrey Lepikhov and Tom Lane, after a suggestion by Peter Eisentraut
Discussion: https://postgr.es/m/43c7f2f5-1e27-27aa-8c65-c91859d15190@postgrespro.ru
"Result Cache" was never a great name for this node, but nobody managed
to come up with another name that anyone liked enough. That was until
David Johnston mentioned "Node Memoization", which Tom Lane revised to
just "Memoize". People seem to like "Memoize", so let's do the rename.
Reviewed-by: Justin Pryzby
Discussion: https://postgr.es/m/20210708165145.GG1176@momjian.us
Backpatch-through: 14, where Result Cache was introduced
Similar to 50e17ad28, which allowed hash tables to be used for IN clauses
with a set of constants, here we add the same feature for NOT IN clauses.
NOT IN evaluates the same as: WHERE a <> v1 AND a <> v2 AND a <> v3.
Obviously, if we're using a hash table we must be exactly equivalent to
that and return the same result taking into account that either side of
the condition could contain a NULL. This requires a little bit of
special handling to make work with the hash table version.
When processing NOT IN, the ScalarArrayOpExpr's operator will be the <>
operator. To be able to build and lookup a hash table we must use the
<>'s negator operator. The planner checks if that exists and is hashable
and sets the relevant fields in ScalarArrayOpExpr to instruct the executor
to use hashing.
Author: David Rowley, James Coleman
Reviewed-by: James Coleman, Zhihong Yu
Discussion: https://postgr.es/m/CAApHDvoF1mum_FRk6D621edcB6KSHBi2+GAgWmioj5AhOu2vwQ@mail.gmail.com
COMMIT/ROLLBACK necessarily destroys all snapshots within the session.
The original implementation of intra-procedure transactions just
cavalierly did that, ignoring the fact that this left us executing in
a rather different environment than normal. In particular, it turns
out that handling of toasted datums depends rather critically on there
being an outer ActiveSnapshot: otherwise, when SPI or the core
executor pop whatever snapshot they used and return, it's unsafe to
dereference any toasted datums that may appear in the query result.
It's possible to demonstrate "no known snapshots" and "missing chunk
number N for toast value" errors as a result of this oversight.
Historically this outer snapshot has been held by the Portal code,
and that seems like a good plan to preserve. So add infrastructure
to pquery.c to allow re-establishing the Portal-owned snapshot if it's
not there anymore, and add enough bookkeeping support that we can tell
whether it is or not.
We can't, however, just re-establish the Portal snapshot as part of
COMMIT/ROLLBACK. As in normal transaction start, acquiring the first
snapshot should wait until after SET and LOCK commands. Hence, teach
spi.c about doing this at the right time. (Note that this patch
doesn't fix the problem for any PLs that try to run intra-procedure
transactions without using SPI to execute SQL commands.)
This makes SPI's no_snapshots parameter rather a misnomer, so in HEAD,
rename that to allow_nonatomic.
replication/logical/worker.c also needs some fixes, because it wasn't
careful to hold a snapshot open around AFTER trigger execution.
That code doesn't use a Portal, which I suspect someday we're gonna
have to fix. But for now, just rearrange the order of operations.
This includes back-patching the recent addition of finish_estate()
to centralize the cleanup logic there.
This also back-patches commit 2ecfeda3e into v13, to improve the
test coverage for worker.c (it was that test that exposed that
worker.c's snapshot management is wrong).
Per bug #15990 from Andreas Wicht. Back-patch to v11 where
intra-procedure COMMIT was added.
Discussion: https://postgr.es/m/15990-eee2ac466b11293d@postgresql.org
1) Previously there were both pgstat_send_wal() and pgstat_report_wal()
in order to send WAL activity to the stats collector. With the former being
used by wal writer, the latter by most other processes. They were a bit
redundant and so this commit merges them into pgstat_send_wal() to
simplify the code.
2) Previously WAL global statistics counters were calculated and then
compared with zero-filled buffer in order to determine whether any WAL
activity has happened since the last submission. These calculation and
comparison were not cheap. This was regularly exercised even in read-only
workloads. This commit fixes the issue by making some WAL activity
counters directly be checked to determine if there's WAL activity stats
to send.
3) Previously pgstat_report_stat() did not check if there's WAL activity
stats to send as part of the "Don't expend a clock check if nothing to do"
check at the top. It's probably rare to have pending WAL stats without
also passing one of the other conditions, but for safely this commit
changes pgstat_report_stats() so that it checks also some WAL activity
counters at the top.
This commit also adds the comments about the design of WAL stats.
Reported-by: Andres Freund
Author: Masahiro Ikeda
Reviewed-by: Kyotaro Horiguchi, Atsushi Torikoshi, Andres Freund, Fujii Masao
Discussion: https://postgr.es/m/20210324232224.vrfiij2rxxwqqjjb@alap3.anarazel.de
Also "make reformat-dat-files".
The only change worthy of note is that pgindent messed up the formatting
of launcher.c's struct LogicalRepWorkerId, which led me to notice that
that struct wasn't used at all anymore, so I just took it out.
EXPLAIN ANALYZE for an async-capable ForeignScan node associated with
postgres_fdw is done just by using instrumentation for ExecProcNode()
called from the node's callbacks, causing the following problems:
1) If the remote table to scan is empty, the node is incorrectly
considered as "never executed" by the command even if the node is
executed, as ExecProcNode() isn't called from the node's callbacks at
all in that case.
2) The command fails to collect timings for things other than
ExecProcNode() done in the node, such as creating a cursor for the
node's remote query.
To fix these problems, add instrumentation for async-capable nodes, and
modify postgres_fdw accordingly.
My oversight in commit 27e1f1456.
While at it, update a comment for the AsyncRequest struct in execnodes.h
and the documentation for the ForeignAsyncRequest API in fdwhandler.sgml
to match the code in ExecAsyncAppendResponse() in nodeAppend.c, and fix
typos in comments in nodeAppend.c.
Per report from Andrey Lepikhov, though I didn't use his patch.
Reviewed-by: Andrey Lepikhov
Discussion: https://postgr.es/m/2eb662bb-105d-fc20-7412-2f027cc3ca72%40postgrespro.ru
Previously long was used as the data type for some counters in BufferUsage
and WalUsage. But long is only four byte, e.g., on Windows, and it's entirely
possible to wrap a four byte counter. For example, emitting more than
four billion WAL records in one transaction isn't actually particularly rare.
To avoid the overflows of those counters, this commit changes the data type
of them from long to int64.
Suggested-by: Andres Freund
Author: Masahiro Ikeda
Reviewed-by: Fujii Masao
Discussion: https://postgr.es/m/20201221211650.k7b53tcnadrciqjo@alap3.anarazel.de
Discussion: https://postgr.es/m/af0964ac-7080-1984-dc23-513754987716@oss.nttdata.com
It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE
list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present.
If it happens, the ON CONFLICT UPDATE code path would end up storing
tuples that include the values of the extra resjunk columns. That's
fairly harmless in the short run, but if new columns are added to
the table then the values would become accessible, possibly leading
to malfunctions if they don't match the datatypes of the new columns.
This had escaped notice through a confluence of missing sanity checks,
including
* There's no cross-check that a tuple presented to heap_insert or
heap_update matches the table rowtype. While it's difficult to
check that fully at reasonable cost, we can easily add assertions
that there aren't too many columns.
* The output-column-assignment cases in execExprInterp.c lacked
any sanity checks on the output column numbers, which seems like
an oversight considering there are plenty of assertion checks on
input column numbers. Add assertions there too.
* We failed to apply nodeModifyTable's ExecCheckPlanOutput() to
the ON CONFLICT UPDATE tlist. That wouldn't have caught this
specific error, since that function is chartered to ignore resjunk
columns; but it sure seems like a bad omission now that we've seen
this bug.
In HEAD, the right way to fix this is to make the processing of
ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists
now do, that is don't add "SET x = x" entries, and use
ExecBuildUpdateProjection to evaluate the tlist and combine it with
old values of the not-set columns. This adds a little complication
to ExecBuildUpdateProjection, but allows removal of a comparable
amount of now-dead code from the planner.
In the back branches, the most expedient solution seems to be to
(a) use an output slot for the ON CONFLICT UPDATE projection that
actually matches the target table, and then (b) invent a variant of
ExecBuildProjectionInfo that can be told to not store values resulting
from resjunk columns, so it doesn't try to store into nonexistent
columns of the output slot. (We can't simply ignore the resjunk columns
altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.)
This works back to v10. In 9.6, projections work much differently and
we can't cheaply give them such an option. The 9.6 version of this
patch works by inserting a JunkFilter when it's necessary to get rid
of resjunk columns.
In addition, v11 and up have the reverse problem when trying to
perform ON CONFLICT UPDATE on a partitioned table. Through a
further oversight, adjust_partition_tlist() discarded resjunk columns
when re-ordering the ON CONFLICT UPDATE tlist to match a partition.
This accidentally prevented the storing-bogus-tuples problem, but
at the cost that MULTIEXPR_SUBLINK cases didn't work, typically
crashing if more than one row has to be updated. Fix by preserving
resjunk columns in that routine. (I failed to resist the temptation
to add more assertions there too, and to do some minor code
beautification.)
Per report from Andres Freund. Back-patch to all supported branches.
Security: CVE-2021-32028
Commit e717a9a18 changed the longstanding rule that prosrc is NOT NULL
because when a SQL-language function is written in SQL-standard style,
we don't currently have anything useful to put there. This seems a poor
decision though, as it could easily have negative impacts on external
PLs (opening them to crashes they didn't use to have, for instance).
SQL-function-related code can just as easily test "is prosqlbody not
null" as "is prosrc null", so there's no real gain there either.
Hence, revert the NOT NULL marking removal and adjust related logic.
For now, we just put an empty string into prosrc for SQL-standard
functions. Maybe we'll have a better idea later, although the
history of things like pg_attrdef.adsrc suggests that it's not
easy to maintain a string equivalent of a node tree.
This also adds an assertion that queryDesc->sourceText != NULL
to standard_ExecutorStart. We'd been silently relying on that
for awhile, so let's make it less silent.
Also fix some overlooked documentation and test cases.
Discussion: https://postgr.es/m/2197698.1617984583@sss.pgh.pa.us
Previously, get_cached_rowtype() cached a pointer to a reference-counted
tuple descriptor from the typcache, relying on the ExprContextCallback
mechanism to release the tupdesc refcount when the expression tree
using the tupdesc was destroyed. This worked fine when it was designed,
but the introduction of within-DO-block COMMITs broke it. The refcount
is logged in a transaction-lifespan resource owner, but plpgsql won't
destroy simple expressions made within the DO block (before its first
commit) until the DO block is exited. That results in a warning about
a leaked tupdesc refcount when the COMMIT destroys the original resource
owner, and then an error about the active resource owner not holding a
matching refcount when the expression is destroyed.
To fix, get rid of the need to have a shutdown callback at all, by
instead caching a pointer to the relevant typcache entry. Those
survive for the life of the backend, so we needn't worry about the
pointer becoming stale. (For registered RECORD types, we can still
cache a pointer to the tupdesc, knowing that it won't change for the
life of the backend.) This mechanism has been in use in plpgsql
and expandedrecord.c since commit 4b93f5799, and seems to work well.
This change requires modifying the ExprEvalStep structs used by the
relevant expression step types, which is slightly worrisome for
back-patching. However, there seems no good reason for extensions
to be familiar with the details of these particular sub-structs.
Per report from Rohit Bhogate. Back-patch to v11 where within-DO-block
COMMITs became a thing.
Discussion: https://postgr.es/m/CAAV6ZkQRCVBh8qAY+SZiHnz+U+FqAGBBDaDTjF2yiKa2nJSLKg@mail.gmail.com
ScalarArrayOpExprs with "useOr=true" and a set of Consts on the righthand
side have traditionally been evaluated by using a linear search over the
array. When these arrays contain large numbers of elements then this
linear search could become a significant part of execution time.
Here we add a new method of evaluating ScalarArrayOpExpr expressions to
allow them to be evaluated by first building a hash table containing each
element, then on subsequent evaluations, we just probe that hash table to
determine if there is a match.
The planner is in charge of determining when this optimization is possible
and it enables it by setting hashfuncid in the ScalarArrayOpExpr. The
executor will only perform the hash table evaluation when the hashfuncid
is set.
This means that not all cases are optimized. For example CHECK constraints
containing an IN clause won't go through the planner, so won't get the
hashfuncid set. We could maybe do something about that at some later
date. The reason we're not doing it now is from fear that we may slow
down cases where the expression is evaluated only once. Those cases can
be common, for example, a single row INSERT to a table with a CHECK
constraint containing an IN clause.
In the planner, we enable this when there are suitable hash functions for
the ScalarArrayOpExpr's operator and only when there is at least
MIN_ARRAY_SIZE_FOR_HASHED_SAOP elements in the array. The threshold is
currently set to 9.
Author: James Coleman, David Rowley
Reviewed-by: David Rowley, Tomas Vondra, Heikki Linnakangas
Discussion: https://postgr.es/m/CAAaqYe8x62+=wn0zvNKCj55tPpg-JBHzhZFFc6ANovdqFw7-dA@mail.gmail.com
This adds support for writing CREATE FUNCTION and CREATE PROCEDURE
statements for language SQL with a function body that conforms to the
SQL standard and is portable to other implementations.
Instead of the PostgreSQL-specific AS $$ string literal $$ syntax,
this allows writing out the SQL statements making up the body
unquoted, either as a single statement:
CREATE FUNCTION add(a integer, b integer) RETURNS integer
LANGUAGE SQL
RETURN a + b;
or as a block
CREATE PROCEDURE insert_data(a integer, b integer)
LANGUAGE SQL
BEGIN ATOMIC
INSERT INTO tbl VALUES (a);
INSERT INTO tbl VALUES (b);
END;
The function body is parsed at function definition time and stored as
expression nodes in a new pg_proc column prosqlbody. So at run time,
no further parsing is required.
However, this form does not support polymorphic arguments, because
there is no more parse analysis done at call time.
Dependencies between the function and the objects it uses are fully
tracked.
A new RETURN statement is introduced. This can only be used inside
function bodies. Internally, it is treated much like a SELECT
statement.
psql needs some new intelligence to keep track of function body
boundaries so that it doesn't send off statements when it sees
semicolons that are inside a function body.
Tested-by: Jaime Casanova <jcasanov@systemguards.com.ec>
Reviewed-by: Julien Rouhaud <rjuju123@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/1c11f1eb-f00c-43b7-799d-2d44132c02d7@2ndquadrant.com
Arrange to do some things on-demand, rather than immediately during
executor startup, because there's a fair chance of never having to do
them at all:
* Don't open result relations' indexes until needed.
* Don't initialize partition tuple routing, nor the child-to-root
tuple conversion map, until needed.
This wins in UPDATEs on partitioned tables when only some of the
partitions will actually receive updates; with larger partition
counts the savings is quite noticeable. Also, we can remove some
sketchy heuristics in ExecInitModifyTable about whether to set up
tuple routing.
Also, remove execPartition.c's private hash table tracking which
partitions were already opened by the ModifyTable node. Instead
use the hash added to ModifyTable itself by commit 86dc90056.
To allow lazy computation of the conversion maps, we now set
ri_RootResultRelInfo in all child ResultRelInfos. We formerly set it
only in some, not terribly well-defined, cases. This has user-visible
side effects in that now more error messages refer to the root
relation instead of some partition (and provide error data in the
root's column order, too). It looks to me like this is a strict
improvement in consistency, so I don't have a problem with the
output changes visible in this commit.
Extracted from a larger patch, which seemed to me to be too messy
to push in one commit.
Amit Langote, reviewed at different times by Heikki Linnakangas and
myself
Discussion: https://postgr.es/m/CA+HiwqG7ZruBmmih3wPsBZ4s0H2EhywrnXEduckY5Hr3fWzPWA@mail.gmail.com
Here we add a new executor node type named "Result Cache". The planner
can include this node type in the plan to have the executor cache the
results from the inner side of parameterized nested loop joins. This
allows caching of tuples for sets of parameters so that in the event that
the node sees the same parameter values again, it can just return the
cached tuples instead of rescanning the inner side of the join all over
again. Internally, result cache uses a hash table in order to quickly
find tuples that have been previously cached.
For certain data sets, this can significantly improve the performance of
joins. The best cases for using this new node type are for join problems
where a large portion of the tuples from the inner side of the join have
no join partner on the outer side of the join. In such cases, hash join
would have to hash values that are never looked up, thus bloating the hash
table and possibly causing it to multi-batch. Merge joins would have to
skip over all of the unmatched rows. If we use a nested loop join with a
result cache, then we only cache tuples that have at least one join
partner on the outer side of the join. The benefits of using a
parameterized nested loop with a result cache increase when there are
fewer distinct values being looked up and the number of lookups of each
value is large. Also, hash probes to lookup the cache can be much faster
than the hash probe in a hash join as it's common that the result cache's
hash table is much smaller than the hash join's due to result cache only
caching useful tuples rather than all tuples from the inner side of the
join. This variation in hash probe performance is more significant when
the hash join's hash table no longer fits into the CPU's L3 cache, but the
result cache's hash table does. The apparent "random" access of hash
buckets with each hash probe can cause a poor L3 cache hit ratio for large
hash tables. Smaller hash tables generally perform better.
The hash table used for the cache limits itself to not exceeding work_mem
* hash_mem_multiplier in size. We maintain a dlist of keys for this cache
and when we're adding new tuples and realize we've exceeded the memory
budget, we evict cache entries starting with the least recently used ones
until we have enough memory to add the new tuples to the cache.
For parameterized nested loop joins, we now consider using one of these
result cache nodes in between the nested loop node and its inner node. We
determine when this might be useful based on cost, which is primarily
driven off of what the expected cache hit ratio will be. Estimating the
cache hit ratio relies on having good distinct estimates on the nested
loop's parameters.
For now, the planner will only consider using a result cache for
parameterized nested loop joins. This works for both normal joins and
also for LATERAL type joins to subqueries. It is possible to use this new
node for other uses in the future. For example, to cache results from
correlated subqueries. However, that's not done here due to some
difficulties obtaining a distinct estimation on the outer plan to
calculate the estimated cache hit ratio. Currently we plan the inner plan
before planning the outer plan so there is no good way to know if a result
cache would be useful or not since we can't estimate the number of times
the subplan will be called until the outer plan is generated.
The functionality being added here is newly introducing a dependency on
the return value of estimate_num_groups() during the join search.
Previously, during the join search, we only ever needed to perform
selectivity estimations. With this commit, we need to use
estimate_num_groups() in order to estimate what the hit ratio on the
result cache will be. In simple terms, if we expect 10 distinct values
and we expect 1000 outer rows, then we'll estimate the hit ratio to be
99%. Since cache hits are very cheap compared to scanning the underlying
nodes on the inner side of the nested loop join, then this will
significantly reduce the planner's cost for the join. However, it's
fairly easy to see here that things will go bad when estimate_num_groups()
incorrectly returns a value that's significantly lower than the actual
number of distinct values. If this happens then that may cause us to make
use of a nested loop join with a result cache instead of some other join
type, such as a merge or hash join. Our distinct estimations have been
known to be a source of trouble in the past, so the extra reliance on them
here could cause the planner to choose slower plans than it did previous
to having this feature. Distinct estimations are also fairly hard to
estimate accurately when several tables have been joined already or when a
WHERE clause filters out a set of values that are correlated to the
expressions we're estimating the number of distinct value for.
For now, the costing we perform during query planning for result caches
does put quite a bit of faith in the distinct estimations being accurate.
When these are accurate then we should generally see faster execution
times for plans containing a result cache. However, in the real world, we
may find that we need to either change the costings to put less trust in
the distinct estimations being accurate or perhaps even disable this
feature by default. There's always an element of risk when we teach the
query planner to do new tricks that it decides to use that new trick at
the wrong time and causes a regression. Users may opt to get the old
behavior by turning the feature off using the enable_resultcache GUC.
Currently, this is enabled by default. It remains to be seen if we'll
maintain that setting for the release.
Additionally, the name "Result Cache" is the best name I could think of
for this new node at the time I started writing the patch. Nobody seems
to strongly dislike the name. A few people did suggest other names but no
other name seemed to dominate in the brief discussion that there was about
names. Let's allow the beta period to see if the current name pleases
enough people. If there's some consensus on a better name, then we can
change it before the release. Please see the 2nd discussion link below
for the discussion on the "Result Cache" name.
Author: David Rowley
Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu, Hou Zhijie
Tested-By: Konstantin Knizhnik
Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com
This removes "Add Result Cache executor node". It seems that something
weird is going on with the tracking of cache hits and misses as
highlighted by many buildfarm animals. It's not yet clear what the
problem is as other parts of the plan indicate that the cache did work
correctly, it's just the hits and misses that were being reported as 0.
This is especially a bad time to have the buildfarm so broken, so
reverting before too many more animals go red.
Discussion: https://postgr.es/m/CAApHDvq_hydhfovm4=izgWs+C5HqEeRScjMbOgbpC-jRAeK3Yw@mail.gmail.com
Here we add a new executor node type named "Result Cache". The planner
can include this node type in the plan to have the executor cache the
results from the inner side of parameterized nested loop joins. This
allows caching of tuples for sets of parameters so that in the event that
the node sees the same parameter values again, it can just return the
cached tuples instead of rescanning the inner side of the join all over
again. Internally, result cache uses a hash table in order to quickly
find tuples that have been previously cached.
For certain data sets, this can significantly improve the performance of
joins. The best cases for using this new node type are for join problems
where a large portion of the tuples from the inner side of the join have
no join partner on the outer side of the join. In such cases, hash join
would have to hash values that are never looked up, thus bloating the hash
table and possibly causing it to multi-batch. Merge joins would have to
skip over all of the unmatched rows. If we use a nested loop join with a
result cache, then we only cache tuples that have at least one join
partner on the outer side of the join. The benefits of using a
parameterized nested loop with a result cache increase when there are
fewer distinct values being looked up and the number of lookups of each
value is large. Also, hash probes to lookup the cache can be much faster
than the hash probe in a hash join as it's common that the result cache's
hash table is much smaller than the hash join's due to result cache only
caching useful tuples rather than all tuples from the inner side of the
join. This variation in hash probe performance is more significant when
the hash join's hash table no longer fits into the CPU's L3 cache, but the
result cache's hash table does. The apparent "random" access of hash
buckets with each hash probe can cause a poor L3 cache hit ratio for large
hash tables. Smaller hash tables generally perform better.
The hash table used for the cache limits itself to not exceeding work_mem
* hash_mem_multiplier in size. We maintain a dlist of keys for this cache
and when we're adding new tuples and realize we've exceeded the memory
budget, we evict cache entries starting with the least recently used ones
until we have enough memory to add the new tuples to the cache.
For parameterized nested loop joins, we now consider using one of these
result cache nodes in between the nested loop node and its inner node. We
determine when this might be useful based on cost, which is primarily
driven off of what the expected cache hit ratio will be. Estimating the
cache hit ratio relies on having good distinct estimates on the nested
loop's parameters.
For now, the planner will only consider using a result cache for
parameterized nested loop joins. This works for both normal joins and
also for LATERAL type joins to subqueries. It is possible to use this new
node for other uses in the future. For example, to cache results from
correlated subqueries. However, that's not done here due to some
difficulties obtaining a distinct estimation on the outer plan to
calculate the estimated cache hit ratio. Currently we plan the inner plan
before planning the outer plan so there is no good way to know if a result
cache would be useful or not since we can't estimate the number of times
the subplan will be called until the outer plan is generated.
The functionality being added here is newly introducing a dependency on
the return value of estimate_num_groups() during the join search.
Previously, during the join search, we only ever needed to perform
selectivity estimations. With this commit, we need to use
estimate_num_groups() in order to estimate what the hit ratio on the
result cache will be. In simple terms, if we expect 10 distinct values
and we expect 1000 outer rows, then we'll estimate the hit ratio to be
99%. Since cache hits are very cheap compared to scanning the underlying
nodes on the inner side of the nested loop join, then this will
significantly reduce the planner's cost for the join. However, it's
fairly easy to see here that things will go bad when estimate_num_groups()
incorrectly returns a value that's significantly lower than the actual
number of distinct values. If this happens then that may cause us to make
use of a nested loop join with a result cache instead of some other join
type, such as a merge or hash join. Our distinct estimations have been
known to be a source of trouble in the past, so the extra reliance on them
here could cause the planner to choose slower plans than it did previous
to having this feature. Distinct estimations are also fairly hard to
estimate accurately when several tables have been joined already or when a
WHERE clause filters out a set of values that are correlated to the
expressions we're estimating the number of distinct value for.
For now, the costing we perform during query planning for result caches
does put quite a bit of faith in the distinct estimations being accurate.
When these are accurate then we should generally see faster execution
times for plans containing a result cache. However, in the real world, we
may find that we need to either change the costings to put less trust in
the distinct estimations being accurate or perhaps even disable this
feature by default. There's always an element of risk when we teach the
query planner to do new tricks that it decides to use that new trick at
the wrong time and causes a regression. Users may opt to get the old
behavior by turning the feature off using the enable_resultcache GUC.
Currently, this is enabled by default. It remains to be seen if we'll
maintain that setting for the release.
Additionally, the name "Result Cache" is the best name I could think of
for this new node at the time I started writing the patch. Nobody seems
to strongly dislike the name. A few people did suggest other names but no
other name seemed to dominate in the brief discussion that there was about
names. Let's allow the beta period to see if the current name pleases
enough people. If there's some consensus on a better name, then we can
change it before the release. Please see the 2nd discussion link below
for the discussion on the "Result Cache" name.
Author: David Rowley
Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu
Tested-By: Konstantin Knizhnik
Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com
This patch makes two closely related sets of changes:
1. For UPDATE, the subplan of the ModifyTable node now only delivers
the new values of the changed columns (i.e., the expressions computed
in the query's SET clause) plus row identity information such as CTID.
ModifyTable must re-fetch the original tuple to merge in the old
values of any unchanged columns. The core advantage of this is that
the changed columns are uniform across all tables of an inherited or
partitioned target relation, whereas the other columns might not be.
A secondary advantage, when the UPDATE involves joins, is that less
data needs to pass through the plan tree. The disadvantage of course
is an extra fetch of each tuple to be updated. However, that seems to
be very nearly free in context; even worst-case tests don't show it to
add more than a couple percent to the total query cost. At some point
it might be interesting to combine the re-fetch with the tuple access
that ModifyTable must do anyway to mark the old tuple dead; but that
would require a good deal of refactoring and it seems it wouldn't buy
all that much, so this patch doesn't attempt it.
2. For inherited UPDATE/DELETE, instead of generating a separate
subplan for each target relation, we now generate a single subplan
that is just exactly like a SELECT's plan, then stick ModifyTable
on top of that. To let ModifyTable know which target relation a
given incoming row refers to, a tableoid junk column is added to
the row identity information. This gets rid of the horrid hack
that was inheritance_planner(), eliminating O(N^2) planning cost
and memory consumption in cases where there were many unprunable
target relations.
Point 2 of course requires point 1, so that there is a uniform
definition of the non-junk columns to be returned by the subplan.
We can't insist on uniform definition of the row identity junk
columns however, if we want to keep the ability to have both
plain and foreign tables in a partitioning hierarchy. Since
it wouldn't scale very far to have every child table have its
own row identity column, this patch includes provisions to merge
similar row identity columns into one column of the subplan result.
In particular, we can merge the whole-row Vars typically used as
row identity by FDWs into one column by pretending they are type
RECORD. (It's still okay for the actual composite Datums to be
labeled with the table's rowtype OID, though.)
There is more that can be done to file down residual inefficiencies
in this patch, but it seems to be committable now.
FDW authors should note several API changes:
* The argument list for AddForeignUpdateTargets() has changed, and so
has the method it must use for adding junk columns to the query. Call
add_row_identity_var() instead of manipulating the parse tree directly.
You might want to reconsider exactly what you're adding, too.
* PlanDirectModify() must now work a little harder to find the
ForeignScan plan node; if the foreign table is part of a partitioning
hierarchy then the ForeignScan might not be the direct child of
ModifyTable. See postgres_fdw for sample code.
* To check whether a relation is a target relation, it's no
longer sufficient to compare its relid to root->parse->resultRelation.
Instead, check it against all_result_relids or leaf_result_relids,
as appropriate.
Amit Langote and Tom Lane
Discussion: https://postgr.es/m/CA+HiwqHpHdqdDn48yCEhynnniahH78rwcrv1rEX65-fsZGBOLQ@mail.gmail.com
This implements asynchronous execution, which runs multiple parts of a
non-parallel-aware Append concurrently rather than serially to improve
performance when possible. Currently, the only node type that can be
run concurrently is a ForeignScan that is an immediate child of such an
Append. In the case where such ForeignScans access data on different
remote servers, this would run those ForeignScans concurrently, and
overlap the remote operations to be performed simultaneously, so it'll
improve the performance especially when the operations involve
time-consuming ones such as remote join and remote aggregation.
We may extend this to other node types such as joins or aggregates over
ForeignScans in the future.
This also adds the support for postgres_fdw, which is enabled by the
table-level/server-level option "async_capable". The default is false.
Robert Haas, Kyotaro Horiguchi, Thomas Munro, and myself. This commit
is mostly based on the patch proposed by Robert Haas, but also uses
stuff from the patch proposed by Kyotaro Horiguchi and from the patch
proposed by Thomas Munro. Reviewed by Kyotaro Horiguchi, Konstantin
Knizhnik, Andrey Lepikhov, Movead Li, Thomas Munro, Justin Pryzby, and
others.
Discussion: https://postgr.es/m/CA%2BTgmoaXQEt4tZ03FtQhnzeDEMzBck%2BLrni0UWHVVgOTnA6C1w%40mail.gmail.com
Discussion: https://postgr.es/m/CA%2BhUKGLBRyu0rHrDCMC4%3DRn3252gogyp1SjOgG8SEKKZv%3DFwfQ%40mail.gmail.com
Discussion: https://postgr.es/m/20200228.170650.667613673625155850.horikyota.ntt%40gmail.com
Commit 3048898e dropped -ING from some wait event names that correspond
to barrier phases. Update the phases' names to match.
While we're here making cosmetic changes, also rename "DONE" to "FREE".
That pairs better with "ALLOCATE", and describes the activity that
actually happens in that phase (as we do for the other phases) rather
than describing a state. The distinction is clearer after bugfix commit
3b8981b6 split the phase into two. As for the growth barriers, rename
their "ALLOCATE" phase to "REALLOCATE", which is probably a better
description of what happens then. Also improve the comments about
the phases a bit.
Discussion: https://postgr.es/m/CA%2BhUKG%2BMDpwF2Eo2LAvzd%3DpOh81wUTsrwU1uAwR-v6OGBB6%2B7g%40mail.gmail.com
With very unlucky timing and parallel_leader_participation off, PHJ
could attempt to access per-batch state just as it was being freed.
There was code intended to prevent that by checking for a cleared
pointer, but it was buggy.
Fix, by introducing an extra barrier phase. The new phase
PHJ_BUILD_RUNNING means that it's safe to access the per-batch state to
find a batch to help with, and PHJ_BUILD_DONE means that it is too late.
The last to detach will free the array of per-batch state as before, but
now it will also atomically advance the phase at the same time, so that
late attachers can avoid the hazard, without the data race. This
mirrors the way per-batch hash tables are freed (see phases
PHJ_BATCH_PROBING and PHJ_BATCH_DONE).
Revealed by a one-off build farm failure, where BarrierAttach() failed a
sanity check assertion, because the memory had been clobbered by
dsa_free().
Back-patch to 11, where the code arrived.
Reported-by: Michael Paquier <michael@paquier.xyz>
Discussion: https://postgr.es/m/20200929061142.GA29096%40paquier.xyz
This adds a new executor node named TID Range Scan. The query planner
will generate paths for TID Range scans when quals are discovered on base
relations which search for ranges on the table's ctid column. These
ranges may be open at either end. For example, WHERE ctid >= '(10,0)';
will return all tuples on page 10 and over.
To support this, two new optional callback functions have been added to
table AM. scan_set_tidrange is used to set the scan range to just the
given range of TIDs. scan_getnextslot_tidrange fetches the next tuple
in the given range.
For AMs were scanning ranges of TIDs would not make sense, these functions
can be set to NULL in the TableAmRoutine. The query planner won't
generate TID Range Scan Paths in that case.
Author: Edmund Horner, David Rowley
Reviewed-by: David Rowley, Tomas Vondra, Tom Lane, Andres Freund, Zhihong Yu
Discussion: https://postgr.es/m/CAMyN-kB-nFTkF=VA_JPwFNo08S0d-Yk0F741S2B7LDmYAi8eyA@mail.gmail.com
If a cross-partition UPDATE violates a constraint on the target partition,
and the columns in the new partition are in different physical order than
in the parent, the error message can reveal columns that the user does not
have SELECT permission on. A similar bug was fixed earlier in commit
804b6b6db4.
The cause of the bug is that the callers of the
ExecBuildSlotValueDescription() function got confused when constructing
the list of modified columns. If the tuple was routed from a parent, we
converted the tuple to the parent's format, but the list of modified
columns was grabbed directly from the child's RTE entry.
ExecUpdateLockMode() had a similar issue. That lead to confusion on which
columns are key columns, leading to wrong tuple lock being taken on tables
referenced by foreign keys, when a row is updated with INSERT ON CONFLICT
UPDATE. A new isolation test is added for that corner case.
With this patch, the ri_RangeTableIndex field is no longer set for
partitions that don't have an entry in the range table. Previously, it was
set to the RTE entry of the parent relation, but that was confusing.
NOTE: This modifies the ResultRelInfo struct, replacing the
ri_PartitionRoot field with ri_RootResultRelInfo. That's a bit risky to
backpatch, because it breaks any extensions accessing the field. The
change that ri_RangeTableIndex is not set for partitions could potentially
break extensions, too. The ResultRelInfos are visible to FDWs at least,
and this patch required small changes to postgres_fdw. Nevertheless, this
seem like the least bad option. I don't think these fields widely used in
extensions; I don't think there are FDWs out there that uses the FDW
"direct update" API, other than postgres_fdw. If there is, you will get a
compilation error, so hopefully it is caught quickly.
Backpatch to 11, where support for both cross-partition UPDATEs, and unique
indexes on partitioned tables, were added.
Reviewed-by: Amit Langote
Security: CVE-2021-3393
SPI_execute_with_receiver and SPI_cursor_parse_open_with_paramlist are
new in v14 (cf. commit 2f48ede08). Before they can get out the door,
let's change their APIs to follow the practice recently established by
SPI_prepare_extended etc: shove all optional arguments into a struct
that callers are supposed to pre-zero. The hope is to allow future
addition of more options without either API breakage or a continuing
proliferation of new SPI entry points. With that in mind, choose
slightly more generic names for them: SPI_execute_extended and
SPI_cursor_parse_open respectively.
Discussion: https://postgr.es/m/CAFj8pRCLPdDAETvR7Po7gC5y_ibkn_-bOzbeJb39WHms01194Q@mail.gmail.com
This patch essentially is cleaning up technical debt left behind
by the original implementation of plpgsql procedures, particularly
commit d92bc83c4. That patch (or more precisely, follow-on patches
fixing its worst bugs) forced us to re-plan CALL and DO statements
each time through, if we're in a non-atomic context. That wasn't
for any fundamental reason, but just because use of a saved plan
requires having a ResourceOwner to hold a reference count for the
plan, and we had no suitable resowner at hand, nor would the
available APIs support using one if we did. While it's not that
expensive to create a "plan" for CALL/DO, the cycles do add up
in repeated executions.
This patch therefore makes the following API changes:
* GetCachedPlan/ReleaseCachedPlan are modified to let the caller
specify which resowner to use to pin the plan, rather than forcing
use of CurrentResourceOwner.
* spi.c gains a "SPI_execute_plan_extended" entry point that lets
callers say which resowner to use to pin the plan. This borrows the
idea of an options struct from the recently added SPI_prepare_extended,
hopefully allowing future options to be added without more API breaks.
This supersedes SPI_execute_plan_with_paramlist (which I've marked
deprecated) as well as SPI_execute_plan_with_receiver (which is new
in v14, so I just took it out altogether).
* I also took the opportunity to remove the crude hack of letting
plpgsql reach into SPI private data structures to mark SPI plans as
"no_snapshot". It's better to treat that as an option of
SPI_prepare_extended.
Now, when running a non-atomic procedure or DO block that contains
any CALL or DO commands, plpgsql creates a ResourceOwner that
will be used to pin the plans of the CALL/DO commands. (In an
atomic context, we just use CurrentResourceOwner, as before.)
Having done this, we can just save CALL/DO plans normally,
whether or not they are used across transaction boundaries.
This seems to be good for something like 2X speedup of a CALL
of a trivial procedure with a few simple argument expressions.
By restricting the creation of an extra ResourceOwner like this,
there's essentially zero penalty in cases that can't benefit.
Pavel Stehule, with some further hacking by me
Discussion: https://postgr.es/m/CAFj8pRCLPdDAETvR7Po7gC5y_ibkn_-bOzbeJb39WHms01194Q@mail.gmail.com
Add an executor aminsert() hint mechanism that informs index AMs that
the incoming index tuple (the tuple that accompanies the hint) is not
being inserted by execution of an SQL statement that logically modifies
any of the index's key columns.
The hint is received by indexes when an UPDATE takes place that does not
apply an optimization like heapam's HOT (though only for indexes where
all key columns are logically unchanged). Any index tuple that receives
the hint on insert is expected to be a duplicate of at least one
existing older version that is needed for the same logical row. Related
versions will typically be stored on the same index page, at least
within index AMs that apply the hint.
Recognizing the difference between MVCC version churn duplicates and
true logical row duplicates at the index AM level can help with cleanup
of garbage index tuples. Cleanup can intelligently target tuples that
are likely to be garbage, without wasting too many cycles on less
promising tuples/pages (index pages with little or no version churn).
This is infrastructure for an upcoming commit that will teach nbtree to
perform bottom-up index deletion. No index AM actually applies the hint
just yet.
Author: Peter Geoghegan <pg@bowt.ie>
Reviewed-By: Victor Yegorov <vyegorov@gmail.com>
Discussion: https://postgr.es/m/CAH2-Wz=CEKFa74EScx_hFVshCOn6AA5T-ajFASTdzipdkLTNQQ@mail.gmail.com
This patch essentially allows gram.y to implement a family of related
syntax trees, rather than necessarily always parsing a list of SQL
statements. raw_parser() gains a new argument, enum RawParseMode,
to say what to do. As proof of concept, add a mode that just parses
a TypeName without any other decoration, and use that to greatly
simplify typeStringToTypeName().
In addition, invent a new SPI entry point SPI_prepare_extended() to
allow SPI users (particularly plpgsql) to get at this new functionality.
In hopes of making this the last variant of SPI_prepare(), set up its
additional arguments as a struct rather than direct arguments, and
promise that future additions to the struct can default to zero.
SPI_prepare_cursor() and SPI_prepare_params() can perhaps go away at
some point.
Discussion: https://postgr.es/m/4165684.1607707277@sss.pgh.pa.us
This patch generalizes the subscripting infrastructure so that any
data type can be subscripted, if it provides a handler function to
define what that means. Traditional variable-length (varlena) arrays
all use array_subscript_handler(), while the existing fixed-length
types that support subscripting use raw_array_subscript_handler().
It's expected that other types that want to use subscripting notation
will define their own handlers. (This patch provides no such new
features, though; it only lays the foundation for them.)
To do this, move the parser's semantic processing of subscripts
(including coercion to whatever data type is required) into a
method callback supplied by the handler. On the execution side,
replace the ExecEvalSubscriptingRef* layer of functions with direct
calls to callback-supplied execution routines. (Thus, essentially
no new run-time overhead should be caused by this patch. Indeed,
there is room to remove some overhead by supplying specialized
execution routines. This patch does a little bit in that line,
but more could be done.)
Additional work is required here and there to remove formerly
hard-wired assumptions about the result type, collation, etc
of a SubscriptingRef expression node; and to remove assumptions
that the subscript values must be integers.
One useful side-effect of this is that we now have a less squishy
mechanism for identifying whether a data type is a "true" array:
instead of wiring in weird rules about typlen, we can look to see
if pg_type.typsubscript == F_ARRAY_SUBSCRIPT_HANDLER. For this
to be bulletproof, we have to forbid user-defined types from using
that handler directly; but there seems no good reason for them to
do so.
This patch also removes assumptions that the number of subscripts
is limited to MAXDIM (6), or indeed has any hard-wired limit.
That limit still applies to types handled by array_subscript_handler
or raw_array_subscript_handler, but to discourage other dependencies
on this constant, I've moved it from c.h to utils/array.h.
Dmitry Dolgov, reviewed at various times by Tom Lane, Arthur Zakirov,
Peter Eisentraut, Pavel Stehule
Discussion: https://postgr.es/m/CA+q6zcVDuGBv=M0FqBYX8DPebS3F_0KQ6OVFobGJPM507_SZ_w@mail.gmail.com
Discussion: https://postgr.es/m/CA+q6zcVovR+XY4mfk-7oNk-rF91gH0PebnNfuUjuuDsyHjOcVA@mail.gmail.com
Previously, ExecInitModifyTable relied on ExecInitJunkFilter,
and thence ExecCleanTypeFromTL, to build the target descriptor from
the query tlist. While we just checked (in ExecCheckPlanOutput)
that the tlist produces compatible output, this is not a great
substitute for the relation's actual tuple descriptor that's
available from the relcache. For one thing, dropped columns will
not be correctly marked attisdropped; it's a bit surprising that
we've gotten away with that this long. But the real reason for
being concerned with this is that using the table's descriptor means
that the slot will have correct attrmissing data, allowing us to
revert the klugy fix of commit ba9f18abd. (This commit undoes
that one's changes in trigger.c, but keeps the new test case.)
Thus we can solve the bogus-trigger-tuple problem with fewer cycles
rather than more.
No back-patch, since this doesn't fix any additional bug, and it
seems somewhat more likely to have unforeseen side effects than
ba9f18abd's narrow fix.
Discussion: https://postgr.es/m/16644-5da7ef98a7ac4545@postgresql.org
Since commit 913bbd88d, check_sql_fn_retval() can either insert type
coercion steps in-line in the Query that produces the SQL function's
results, or generate a new top-level Query to perform the coercions,
if modifying the Query's output in-place wouldn't be safe. However,
it appears that the latter case has never actually worked, because
the code tried to inject the new Query back into the query list it was
passed ... which is not the list that will be used for later processing
when we execute the SQL function "normally" (without inlining it).
So we ended up with no coercion happening at run-time, leading to
wrong results or crashes depending on the datatypes involved.
While the regression tests look like they cover this area well enough,
through a huge bit of bad luck all the test cases that exercise the
separate-Query path were checking either inline-able cases (which
accidentally didn't have the bug) or cases that are no-ops at runtime
(e.g., varchar to text), so that the failure to perform the coercion
wasn't obvious. The fact that the cases that don't work weren't
allowed at all before v13 probably contributed to not noticing the
problem sooner, too.
To fix, get rid of the separate "flat" list of Query nodes and instead
pass the real two-level list that is going to be used later. I chose
to make the same change in check_sql_fn_statements(), although that has
no actual bug, just so that we don't need that data structure at all.
This is an API change, as evidenced by the adjustments needed to
callers outside functions.c. That's a bit scary to be doing in a
released branch, but so far as I can tell from a quick search,
there are no outside callers of these functions (and they are
sufficiently specific to our semantics for SQL-language functions that
it's not apparent why any extension would need to call them). In any
case, v13 already changed the API of check_sql_fn_retval() compared to
prior branches.
Per report from pinker. Back-patch to v13 where this code came in.
Discussion: https://postgr.es/m/1603050466566-0.post@n3.nabble.com
Store the tuple conversion map to convert a tuple from a child table's
format to the root format in a new ri_ChildToRootMap field in
ResultRelInfo. It is initialized if transition tuple capture for FOR
STATEMENT triggers or INSERT tuple routing on a partitioned table is
needed. Previously, ModifyTable kept the maps in the per-subplan
ModifyTableState->mt_per_subplan_tupconv_maps array, or when tuple
routing was used, in
ResultRelInfo->ri_Partitioninfo->pi_PartitionToRootMap. The new field
replaces both of those.
Now that the child-to-root tuple conversion map is always available in
ResultRelInfo (when needed), remove the TransitionCaptureState.tcs_map
field. The callers of Exec*Trigger() functions no longer need to set or
save it, which is much less confusing and bug-prone. Also, as a future
optimization, this will allow us to delay creating the map for a given
result relation until the relation is actually processed during
execution.
Author: Amit Langote
Discussion: https://www.postgresql.org/message-id/CA%2BHiwqHtCWLdK-LO%3DNEsvOdHx%2B7yv4mE_zYK0i3BH7dXb-wxog%40mail.gmail.com
Maintaining 'es_result_relation_info' correctly at all times has become
cumbersome, especially with partitioning where each partition gets its
own result relation info. Having to set and reset it across arbitrary
operations has caused bugs in the past.
This changes all the places that used 'es_result_relation_info', to
receive the currently active ResultRelInfo via function parameters
instead.
Author: Amit Langote
Discussion: https://www.postgresql.org/message-id/CA%2BHiwqGEmiib8FLiHMhKB%2BCH5dRgHSLc5N5wnvc4kym%2BZYpQEQ%40mail.gmail.com
Instead of allocating all the ResultRelInfos upfront in one big array,
allocate them in ExecInitModifyTable(). es_result_relations is now an
array of ResultRelInfo pointers, rather than an array of structs, and it
is indexed by the RT index.
This simplifies things: we get rid of the separate concept of a "result
rel index", and don't need to set it in setrefs.c anymore. This also
allows follow-up optimizations (not included in this commit yet) to skip
initializing ResultRelInfos for target relations that were not needed at
runtime, and removal of the es_result_relation_info pointer.
The EState arrays of regular result rels and root result rels are merged
into one array. Similarly, the resultRelations and rootResultRelations
lists in PlannedStmt are merged into one. It's not actually clear to me
why they were kept separate in the first place, but now that the
es_result_relations array is indexed by RT index, it certainly seems
pointless.
The PlannedStmt->resultRelations list is now only needed for
ExecRelationIsTargetRelation(). One visible effect of this change is that
ExecRelationIsTargetRelation() will now return 'true' also for the
partition root, if a partitioned table is updated. That seems like a good
thing, although the function isn't used in core code, and I don't see any
reason for an FDW to call it on a partition root.
Author: Amit Langote
Discussion: https://www.postgresql.org/message-id/CA%2BHiwqGEmiib8FLiHMhKB%2BCH5dRgHSLc5N5wnvc4kym%2BZYpQEQ%40mail.gmail.com
When commit bd3daddaf introduced AlternativeSubPlans, I had some
ambitions towards allowing the choice of subplan to change during
execution. That has not happened, or even been thought about, in the
ensuing twelve years; so it seems like a failed experiment. So let's
rip that out and resolve the choice of subplan at the end of planning
(in setrefs.c) rather than during executor startup. This has a number
of positive benefits:
* Removal of a few hundred lines of executor code, since
AlternativeSubPlans need no longer be supported there.
* Removal of executor-startup overhead (particularly, initialization
of subplans that won't be used).
* Removal of incidental costs of having a larger plan tree, such as
tree-scanning and copying costs in the plancache; not to mention
setrefs.c's own costs of processing the discarded subplans.
* EXPLAIN no longer has to print a weird (and undocumented)
representation of an AlternativeSubPlan choice; it sees only the
subplan actually used. This should mean less confusion for users.
* Since setrefs.c knows which subexpression of a plan node it's
working on at any instant, it's possible to adjust the estimated
number of executions of the subplan based on that. For example,
we should usually estimate more executions of a qual expression
than a targetlist expression. The implementation used here is
pretty simplistic, because we don't want to expend a lot of cycles
on the issue; but it's better than ignoring the point entirely,
as the executor had to.
That last point might possibly result in shifting the choice
between hashed and non-hashed EXISTS subplans in a few cases,
but in general this patch isn't meant to change planner choices.
Since we're doing the resolution so late, it's really impossible
to change any plan choices outside the AlternativeSubPlan itself.
Patch by me; thanks to David Rowley for review.
Discussion: https://postgr.es/m/1992952.1592785225@sss.pgh.pa.us
Add a GUC that acts as a multiplier on work_mem. It gets applied when
sizing executor node hash tables that were previously size constrained
using work_mem alone.
The new GUC can be used to preferentially give hash-based nodes more
memory than the generic work_mem limit. It is intended to enable admin
tuning of the executor's memory usage. Overall system throughput and
system responsiveness can be improved by giving hash-based executor
nodes more memory (especially over sort-based alternatives, which are
often much less sensitive to being memory constrained).
The default value for hash_mem_multiplier is 1.0, which is also the
minimum valid value. This means that hash-based nodes continue to apply
work_mem in the traditional way by default.
hash_mem_multiplier is generally useful. However, it is being added now
due to concerns about hash aggregate performance stability for users
that upgrade to Postgres 13 (which added disk-based hash aggregation in
commit 1f39bce0). While the old hash aggregate behavior risked
out-of-memory errors, it is nevertheless likely that many users actually
benefited. Hash agg's previous indifference to work_mem during query
execution was not just faster; it also accidentally made aggregation
resilient to grouping estimate problems (at least in cases where this
didn't create destabilizing memory pressure).
hash_mem_multiplier can provide a certain kind of continuity with the
behavior of Postgres 12 hash aggregates in cases where the planner
incorrectly estimates that all groups (plus related allocations) will
fit in work_mem/hash_mem. This seems necessary because hash-based
aggregation is usually much slower when only a small fraction of all
groups can fit. Even when it isn't possible to totally avoid hash
aggregates that spill, giving hash aggregation more memory will reliably
improve performance (the same cannot be said for external sort
operations, which appear to be almost unaffected by memory availability
provided it's at least possible to get a single merge pass).
The PostgreSQL 13 release notes should advise users that increasing
hash_mem_multiplier can help with performance regressions associated
with hash aggregation. That can be taken care of by a later commit.
Author: Peter Geoghegan
Reviewed-By: Álvaro Herrera, Jeff Davis
Discussion: https://postgr.es/m/20200625203629.7m6yvut7eqblgmfo@alap3.anarazel.de
Discussion: https://postgr.es/m/CAH2-WzmD%2Bi1pG6rc1%2BCjc4V6EaFJ_qSuKCCHVnH%3DoruqD-zqow%40mail.gmail.com
Backpatch: 13-, where disk-based hash aggregation was introduced.
Use HyperLogLog to estimate the group cardinality in a spilled
partition. This estimate is used to choose the number of partitions if
we recurse.
The previous behavior was to use the number of tuples in a spilled
partition as the estimate for the number of groups, which lead to
overpartitioning. That could cause the number of batches to be much
higher than expected (with each batch being very small), which made it
harder to interpret EXPLAIN ANALYZE results.
Reviewed-by: Peter Geoghegan
Discussion: https://postgr.es/m/a856635f9284bc36f7a77d02f47bbb6aaf7b59b3.camel@j-davis.com
Backpatch-through: 13
This representation saves 8 bytes per tuple compared to HeapTuple, and
avoids the need to allocate, copy and free on the receiving side.
Gather can emit the returned MinimalTuple directly, but GatherMerge now
needs to make an explicit copy because it buffers multiple tuples at a
time. That should be no worse than before.
Reviewed-by: Soumyadeep Chakraborty <soumyadeep2007@gmail.com>
Discussion: https://postgr.es/m/CA%2BhUKG%2B8T_ggoUTAE-U%3DA%2BOcPc4%3DB0nPPHcSfffuQhvXXjML6w%40mail.gmail.com
Since 1f39bce02, HashAgg nodes have had the ability to spill to disk when
memory consumption exceeds work_mem. That commit added new properties to
EXPLAIN ANALYZE to show the maximum memory usage and disk usage, however,
it didn't quite go as far as showing that information for parallel
workers. Since workers may have experienced something very different from
the main process, we should show this information per worker, as is done
in Sort.
Reviewed-by: Justin Pryzby
Reviewed-by: Jeff Davis
Discussion: https://postgr.es/m/CAApHDvpEKbfZa18mM1TD7qV6PG+w97pwCWq5tVD0dX7e11gRJw@mail.gmail.com
Backpatch-through: 13, where the hashagg spilling code was added.
plpgsql has always executed the query given in a RETURN QUERY command
by opening it as a cursor and then fetching a few rows at a time,
which it turns around and dumps into the function's result tuplestore.
The point of this was to keep from blowing out memory with an oversized
SPITupleTable result (note that while a tuplestore can spill tuples
to disk, SPITupleTable cannot). However, it's rather inefficient, both
because of extra data copying and because of executor entry/exit
overhead. In recent versions, a new performance problem has emerged:
use of a cursor prevents use of a parallel plan for the executed query.
We can improve matters by skipping use of a cursor and having the
executor push result tuples directly into the function's result
tuplestore. However, a moderate amount of new infrastructure is needed
to make that idea work:
* We can use the existing tstoreReceiver.c DestReceiver code to funnel
executor output to the tuplestore, but it has to be extended to support
plpgsql's requirement for possibly applying a tuple conversion map.
* SPI needs to be extended to allow use of a caller-supplied
DestReceiver instead of its usual receiver that puts tuples into
a SPITupleTable. Two new API calls are needed to handle both the
RETURN QUERY and RETURN QUERY EXECUTE cases.
I also felt that I didn't want these new API calls to use the legacy
method of specifying query parameter values with "char" null flags
(the old ' '/'n' convention); rather they should accept ParamListInfo
objects containing the parameter type and value info. This required
a bit of additional new infrastructure since we didn't yet have any
parse analysis callback that would interpret $N parameter symbols
according to type data supplied in a ParamListInfo. There seems to be
no harm in letting makeParamList install that callback by default,
rather than leaving a new ParamListInfo's parserSetup hook as NULL.
(Indeed, as of HEAD, I couldn't find anyplace that was using the
parserSetup field at all; plpgsql was using parserSetupArg for its
own purposes, but parserSetup seemed to be write-only.)
We can actually get plpgsql out of the business of using legacy null
flags altogether, and using ParamListInfo instead of its ad-hoc
PreparedParamsData structure; but this requires inventing one more
SPI API call that can replace SPI_cursor_open_with_args. That seems
worth doing, though.
SPI_execute_with_args and SPI_cursor_open_with_args are now unused
anywhere in the core PG distribution. Perhaps someday we could
deprecate/remove them. But cleaning up the crufty bits of the SPI
API is a task for a different patch.
Per bug #16040 from Jeremy Smith. This is unfortunately too invasive to
consider back-patching. Patch by me; thanks to Hamid Akhtar for review.
Discussion: https://postgr.es/m/16040-eaacad11fecfb198@postgresql.org
Includes some manual cleanup of places that pgindent messed up,
most of which weren't per project style anyway.
Notably, it seems some people didn't absorb the style rules of
commit c9d297751, because there were a bunch of new occurrences
of function calls with a newline just after the left paren, all
with faulty expectations about how the rest of the call would get
indented.
In commit 33e05f89c5, we have added the option to display WAL usage
statistics in Explain and auto_explain. The display format used two spaces
between each field which is inconsistent with Buffer usage statistics which
is using one space between each field. Change the format to make WAL usage
statistics consistent with Buffer usage statistics.
This commit also changed the usage of "full page writes" to
"full page images" for WAL usage statistics to make it consistent with
other parts of code and docs.
Author: Julien Rouhaud, Amit Kapila
Reviewed-by: Justin Pryzby, Kyotaro Horiguchi and Amit Kapila
Discussion: https://postgr.es/m/CAB-hujrP8ZfUkvL5OYETipQwA=e3n7oqHFU=4ZLxWS_Cza3kQQ@mail.gmail.com
Before discarding the old hash table in ExecReScanHashJoin, capture
its statistics, ensuring that we report the maximum hashtable size
across repeated rescans of the hash input relation. We can repurpose
the existing code for reporting hashtable size in parallel workers
to help with this, making the patch pretty small. This also ensures
that if rescans happen within parallel workers, we get the correct
maximums across all instances.
Konstantin Knizhnik and Tom Lane, per diagnosis by Thomas Munro
of a trouble report from Alvaro Herrera.
Discussion: https://postgr.es/m/20200323165059.GA24950@alvherre.pgsql
If the memory context's maxBlockSize is too big, a single block
allocation can suddenly exceed work_mem. For Hash Aggregation, this
can mean spilling to disk too early or reporting a confusing memory
usage number for EXPLAN ANALYZE.
Introduce CreateWorkExprContext(), which is like CreateExprContext(),
except that it creates the AllocSet with a maxBlockSize that is
reasonable in proportion to work_mem.
Right now, CreateWorkExprContext() is only used by Hash Aggregation,
but it may be generally useful in the future.
Discussion: https://postgr.es/m/412a3fbf306f84d8d78c4009e11791867e62b87c.camel@j-davis.com
Incremental Sort is an optimized variant of multikey sort for cases when
the input is already sorted by a prefix of the requested sort keys. For
example when the relation is already sorted by (key1, key2) and we need
to sort it by (key1, key2, key3) we can simply split the input rows into
groups having equal values in (key1, key2), and only sort/compare the
remaining column key3.
This has a number of benefits:
- Reduced memory consumption, because only a single group (determined by
values in the sorted prefix) needs to be kept in memory. This may also
eliminate the need to spill to disk.
- Lower startup cost, because Incremental Sort produce results after each
prefix group, which is beneficial for plans where startup cost matters
(like for example queries with LIMIT clause).
We consider both Sort and Incremental Sort, and decide based on costing.
The implemented algorithm operates in two different modes:
- Fetching a minimum number of tuples without check of equality on the
prefix keys, and sorting on all columns when safe.
- Fetching all tuples for a single prefix group and then sorting by
comparing only the remaining (non-prefix) keys.
We always start in the first mode, and employ a heuristic to switch into
the second mode if we believe it's beneficial - the goal is to minimize
the number of unnecessary comparions while keeping memory consumption
below work_mem.
This is a very old patch series. The idea was originally proposed by
Alexander Korotkov back in 2013, and then revived in 2017. In 2018 the
patch was taken over by James Coleman, who wrote and rewrote most of the
current code.
There were many reviewers/contributors since 2013 - I've done my best to
pick the most active ones, and listed them in this commit message.
Author: James Coleman, Alexander Korotkov
Reviewed-by: Tomas Vondra, Andreas Karlsson, Marti Raudsepp, Peter Geoghegan, Robert Haas, Thomas Munro, Antonin Houska, Andres Freund, Alexander Kuzmenkov
Discussion: https://postgr.es/m/CAPpHfdscOX5an71nHd8WSUH6GNOCf=V7wgDaTXdDd9=goN-gfA@mail.gmail.com
Discussion: https://postgr.es/m/CAPpHfds1waRZ=NOmueYq0sx1ZSCnt+5QJvizT8ndT2=etZEeAQ@mail.gmail.com
This allows gathering the WAL generation statistics for each statement
execution. The three statistics that we collect are the number of WAL
records, the number of full page writes and the amount of WAL bytes
generated.
This helps the users who have write-intensive workload to see the impact
of I/O due to WAL. This further enables us to see approximately what
percentage of overall WAL is due to full page writes.
In the future, we can extend this functionality to allow us to compute the
the exact amount of WAL data due to full page writes.
This patch in itself is just an infrastructure to compute WAL usage data.
The upcoming patches will expose this data via explain, auto_explain,
pg_stat_statements and verbose (auto)vacuum output.
Author: Kirill Bychik, Julien Rouhaud
Reviewed-by: Dilip Kumar, Fujii Masao and Amit Kapila
Discussion: https://postgr.es/m/CAB-hujrP8ZfUkvL5OYETipQwA=e3n7oqHFU=4ZLxWS_Cza3kQQ@mail.gmail.com
Don't try to be precise about it, just use a constant 16 bytes of
chunk overhead. Being smarter would require knowing the memory context
where the chunk will be allocated, which is not known by all callers.
Discussion: https://postgr.es/m/20200325220936.il3ni2fj2j2b45y5@alap3.anarazel.de
Previously pg_stat_statements calculated the difference of buffer counters
by its own code even while BufferUsageAccumDiff() had the same code.
This commit expose BufferUsageAccumDiff() and makes pg_stat_statements
use it for the calculation, in order to simply the code.
This change also would be useful for the upcoming patch for the planning
counters in pg_stat_statements because the patch will add one more code
for the calculation of difference of buffer counters and that can easily be
done by using BufferUsageAccumDiff().
Author: Julien Rouhaud
Reviewed-by: Fujii Masao
Discussion: https://postgr.es/m/bdfee4e0-a304-2498-8da5-3cb52c0a193e@oss.nttdata.com
This reverts the parts of commit 17a28b0364
that changed ereport's auxiliary functions from returning dummy integer
values to returning void. It turns out that a minority of compilers
complain (not entirely unreasonably) about constructs such as
(condition) ? errdetail(...) : 0
if errdetail() returns void rather than int. We could update those
call sites to say "(void) 0" perhaps, but the expectation for this
patch set was that ereport callers would not have to change anything.
And this aspect of the patch set was already the most invasive and
least compelling part of it, so let's just drop it.
Per buildfarm.
Discussion: https://postgr.es/m/CA+fd4k6N8EjNvZpM8nme+y+05mz-SM8Z_BgkixzkA34R+ej0Kw@mail.gmail.com
Change all the auxiliary error-reporting routines to return void,
now that we no longer need to pretend they are passing something
useful to errfinish(). While this probably doesn't save anything
significant at the machine-code level, it allows detection of some
additional types of mistakes.
Pass the error location details (__FILE__, __LINE__, PG_FUNCNAME_MACRO)
to errfinish not errstart. This shaves a few cycles off the case where
errstart decides we're not going to emit anything.
Re-implement elog() as a trivial wrapper around ereport(), removing
the separate support infrastructure it used to have. Aside from
getting rid of some now-surplus code, this means that elog() now
really does have exactly the same semantics as ereport(), in particular
that it can skip evaluation work if the message is not to be emitted.
Andres Freund and Tom Lane
Discussion: https://postgr.es/m/CA+fd4k6N8EjNvZpM8nme+y+05mz-SM8Z_BgkixzkA34R+ej0Kw@mail.gmail.com
While performing hash aggregation, track memory usage when adding new
groups to a hash table. If the memory usage exceeds work_mem, enter
"spill mode".
In spill mode, new groups are not created in the hash table(s), but
existing groups continue to be advanced if input tuples match. Tuples
that would cause a new group to be created are instead spilled to a
logical tape to be processed later.
The tuples are spilled in a partitioned fashion. When all tuples from
the outer plan are processed (either by advancing the group or
spilling the tuple), finalize and emit the groups from the hash
table. Then, create new batches of work from the spilled partitions,
and select one of the saved batches and process it (possibly spilling
recursively).
Author: Jeff Davis
Reviewed-by: Tomas Vondra, Adam Lee, Justin Pryzby, Taylor Vesely, Melanie Plageman
Discussion: https://postgr.es/m/507ac540ec7c20136364b5272acbcd4574aa76ef.camel@j-davis.com
Optionally push a step to check for a NULL pointer to the pergroup
state.
This will be important for disk-based hash aggregation in combination
with grouping sets. When memory limits are reached, a given tuple may
find its per-group state for some grouping sets but not others. For
the former, it advances the per-group state as normal; for the latter,
it skips evaluation and the calling code will have to spill the tuple
and reprocess it in a later batch.
Add the NULL check as a separate expression step because in some
common cases it's not needed.
Discussion: https://postgr.es/m/20200221202212.ssb2qpmdgrnx52sj%40alap3.anarazel.de
Do so by combining the various steps that are part of aggregate
transition function invocation into one larger step. As some of the
current steps are only necessary for some aggregates, have one variant
of the aggregate transition step for each possible combination.
To avoid further manual copies of code in the different transition
step implementations, move most of the code into helper functions
marked as "always inline".
The benefit of this change is an increase in performance when
aggregating lots of rows. This comes in part due to the reduced number
of indirect jumps due to the reduced number of steps, and in part by
reducing redundant setup code across steps. This mainly benefits
interpreted execution, but the code generated by JIT is also improved
a bit.
As a nice side-effect it also ends up making the code a bit simpler.
A small additional optimization is removing the need to set
aggstate->curaggcontext before calling ExecAggInitGroup, choosing to
instead passign curaggcontext as an argument. It was, in contrast to
other aggregate related functions, only needed to fetch a memory
context to copy the transition value into.
Author: Andres Freund
Discussion:
https://postgr.es/m/20191023163849.sosqbfs5yenocez3@alap3.anarazel.dehttps://postgr.es/m/5c371df7cee903e8cd4c685f90c6c72086d3a2dc.camel@j-davis.com
When updating a table row with generated columns, only recompute those
generated columns whose base columns have changed in this update and
keep the rest unchanged. This can result in a significant performance
benefit. The required information was already kept in
RangeTblEntry.extraUpdatedCols; we just have to make use of it.
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/b05e781a-fa16-6b52-6738-761181204567@2ndquadrant.com
Commit 4eaea3db introduced TupleHashTableHash(), but the signature
didn't match the other exposed functions. Separate it into internal
and external versions. The external version hides the details behind
an API more consistent with the other external functions, and the
internal version is still suitable for simplehash.
Expose two new entry points: one for only calculating the hash value
of a tuple, and another for looking up a hash entry when the hash
value is already known. This will be useful for disk-based Hash
Aggregation to avoid recomputing the hash value for the same tuple
after saving and restoring it from disk.
Discussion: https://postgr.es/m/37091115219dd522fd9ed67333ee8ed1b7e09443.camel%40j-davis.com
It's already tracked via ExprState->parent, so we don't need to also
include it in ExprEvalStep. When that code originally was written
ExprState->parent didn't exist, but it since has been introduced in
6719b238e8.
Author: Andres Freund
Discussion: https://postgr.es/m/20191023163849.sosqbfs5yenocez3@alap3.anarazel.de
Use the parser's standard type coercion machinery to convert the
output column(s) of a SQL function's final SELECT or RETURNING
to the type(s) they should have according to the function's declared
result type. We'll allow any case where an assignment-level
coercion is available. Previously, we failed unless the required
coercion was a binary-compatible one (and the documentation ignored
this, falsely claiming that the types must match exactly).
Notably, the coercion now accounts for typmods, so that cases where
a SQL function is declared to return a composite type whose columns
are typmod-constrained now behave as one would expect. Arguably
this aspect is a bug fix, but the overall behavioral change here
seems too large to consider back-patching.
A nice side-effect is that functions can now be inlined in a
few cases where we previously failed to do so because of type
mismatches.
Discussion: https://postgr.es/m/18929.1574895430@sss.pgh.pa.us
This follows multiple complains from Peter Geoghegan, Andres Freund and
Alvaro Herrera that this issue ought to be dug more before actually
happening, if it happens.
Discussion: https://postgr.es/m/20191226144606.GA5659@alvherre.pgsql
The following renaming is done so as source files related to index
access methods are more consistent with table access methods (the
original names used for index AMs ware too generic, and could be
confused as including features related to table AMs):
- amapi.h -> indexam.h.
- amapi.c -> indexamapi.c. Here we have an equivalent with
backend/access/table/tableamapi.c.
- amvalidate.c -> indexamvalidate.c.
- amvalidate.h -> indexamvalidate.h.
- genam.c -> indexgenam.c.
- genam.h -> indexgenam.h.
This has been discussed during the development of v12 when table AM was
worked on, but the renaming never happened.
Author: Michael Paquier
Reviewed-by: Fabien Coelho, Julien Rouhaud
Discussion: https://postgr.es/m/20191223053434.GF34339@paquier.xyz
Remove a duplicated word. Add "of" or "# of" in a couple places
for clarity and consistency. Start comments with a lower case
letter as we do elsewhere in this file.
Rafia Sabih
Avoid creating transiently-inconsistent slot states where possible,
by not setting TTS_FLAG_SHOULDFREE until after the slot actually has
a free'able tuple pointer, and by making sure that we reset tts_nvalid
and related derived state before we replace the tuple contents. This
would only matter if something were to examine the slot after we'd
suffered some kind of error (e.g. out of memory) while manipulating
the slot. We typically don't do that, so these changes might just be
cosmetic --- but even if so, it seems like good future-proofing.
Also remove some redundant Asserts, and add a couple for consistency.
Back-patch to v12 where all this code was rewritten.
Discussion: https://postgr.es/m/16095-c3ff2e5283b8dba5@postgresql.org
When ExecBRUpdateTriggers()'s GetTupleForTrigger() follows an EPQ
chain the former needs to run the result tuple through the junkfilter
again, and update the slot containing the new version of the tuple to
contain that new version. The input tuple may already be in the
junkfilter's output slot, which used to be OK - we don't need the
previous version anymore. Unfortunately ff11e7f4b9 started to use
ExecCopySlot() to update newslot, and ExecCopySlot() doesn't support
copying a slot into itself, leading to a slot in a corrupt
state, which then can cause crashes or other symptoms.
Fix this by skipping the ExecCopySlot() when copying into itself.
While we could have easily made ExecCopySlot() handle that case, it
seems better to add an assert forbidding doing so instead. As the goal
of copying might be to make the contents of one slot independent from
another, it seems failure prone to handle doing so silently.
A follow-up commit will add tests for the obviously under-covered
combination of EPQ and triggers. Done as a separate commit as it might
make sense to backpatch them further than this bug.
Also remove confusion with confusing variable names for slots in
ExecBRDeleteTriggers() and ExecBRUpdateTriggers().
Bug: #16036
Reported-By: Антон Власов
Author: Andres Freund
Discussion: https://postgr.es/m/16036-28184c90d952fb7f@postgresql.org
Backpatch: 12-, where ff11e7f4b9 was merged
In ad0bda5d24 I changed the EvalPlanQual machinery to store
substitution tuples in slot, instead of using plain HeapTuples. The
main motivation for that was that using HeapTuples will be inefficient
for future tableams. But it turns out that that conversion was buggy
for non-locking rowmarks - the wrong tuple descriptor was used to
create the slot.
As a secondary issue 5db6df0c0 changed ExecLockRows() to begin EPQ
earlier, to allow to fetch the locked rows directly into the EPQ
slots, instead of having to copy tuples around. Unfortunately, as Tom
complained, that forces some expensive initialization to happen
earlier.
As a third issue, the test coverage for EPQ was clearly insufficient.
Fixing the first issue is unfortunately not trivial: Non-locked row
marks were fetched at the start of EPQ, and we don't have the type
information for the rowmarks available at that point. While we could
change that, it's not easy. It might be worthwhile to change that at
some point, but to fix this bug, it seems better to delay fetching
non-locking rowmarks when they're actually needed, rather than
eagerly. They're referenced at most once, and in cases where EPQ
fails, might never be referenced. Fetching them when needed also
increases locality a bit.
To be able to fetch rowmarks during execution, rather than
initialization, we need to be able to access the active EPQState, as
that contains necessary data. To do so move EPQ related data from
EState to EPQState, and, only for EStates creates as part of EPQ,
reference the associated EPQState from EState.
To fix the second issue, change EPQ initialization to allow use of
EvalPlanQualSlot() to be used before EvalPlanQualBegin() (but
obviously still requiring EvalPlanQualInit() to have been done).
As these changes made struct EState harder to understand, e.g. by
adding multiple EStates, significantly reorder the members, and add a
lot more comments.
Also add a few more EPQ tests, including one that fails for the first
issue above. More is needed.
Reported-By: yi huang
Author: Andres Freund
Reviewed-By: Tom Lane
Discussion:
https://postgr.es/m/CAHU7rYZo_C4ULsAx_LAj8az9zqgrD8WDd4hTegDTMM1LMqrBsg@mail.gmail.comhttps://postgr.es/m/24530.1562686693@sss.pgh.pa.us
Backpatch: 12-, where the EPQ changes were introduced
Now that list_nth is O(1), there's no good reason to maintain a
separate array of RTE pointers rather than indexing into
estate->es_range_table. Deleting the array doesn't save all that
much either; but just on cleanliness grounds, it's better not to
have duplicate representations of the identical information.
Discussion: https://postgr.es/m/14960.1565384592@sss.pgh.pa.us
Now that commit fec0778c8 drew a clear line between public and private
fields in SPITupleTable, it seems pretty silly that the count of valid
tuples isn't on the public side of that line. The reason why not was
that there wasn't such a count. For reasons lost in the mists of time,
spi.c preferred to keep a count of remaining free entries in the array.
But that seems pretty pointless: it's unlike the way we handle similar
code everywhere else, and it involves extra subtractions that surely
outweigh having to do a comparison rather than test-for-zero to check
for array-full.
Hence, rearrange so that this code does the expansible array logic
the same as everywhere else, with a count of valid entries alongside
the allocated array length. And document the count as public.
I looked for core-code callers where it would make sense to start
relying on tuptable->numvals rather than the separate SPI_processed
variable. Right now there don't seem to be places where it'd be
a win to do so without more code restructuring than I care to
undertake today. In principle, though, having SPITupleTables be
fully self-contained should be helpful down the line.
Discussion: https://postgr.es/m/16852.1563395722@sss.pgh.pa.us
The fields that we consider public are "tupdesc" and "vals", which
historically are in the middle of the struct. Move them to the front
(this should be perfectly safe to do in HEAD) and add comments to make
it quite clear which fields are public or not.
Also adjust spi.sgml's documentation of the struct to match.
That doc had bit-rotted somewhat, as it was missing some fields.
(Arguably we should just remove all the private fields from the docs,
but for now I refrained.)
Daniel Gustafsson, reviewed by Fabien Coelho
Discussion: https://postgr.es/m/0D19F836-B743-4340-B6A2-F148CA3DD1F0@yesql.se
This addresses a couple of issues in the code:
- Typos and inconsistencies in comments and function declarations.
- Removal of unreferenced function declarations.
- Removal of unnecessary compile flags.
- A cleanup error in regressplans.sh.
Author: Alexander Lakhin
Discussion: https://postgr.es/m/0c991fdf-2670-1997-c027-772a420c4604@gmail.com
