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
There were a number of issues in the recent commits which include typos,
code and comments mismatch, leftover function declarations. Fix them.
Reported-by: Alexander Lakhin
Author: Alexander Lakhin, Amit Kapila and Amit Langote
Reviewed-by: Amit Kapila
Discussion: https://postgr.es/m/ef0c0232-0c1d-3a35-63d4-0ebd06e31387@gmail.com
This is still using the 2.0 version of pg_bsd_indent.
I thought it would be good to commit this separately,
so as to document the differences between 2.0 and 2.1 behavior.
Discussion: https://postgr.es/m/16296.1558103386@sss.pgh.pa.us
Previously, gen_partprune_steps() always built executor pruning steps
using all suitable clauses, including those containing PARAM_EXEC
Params. This meant that the pruning steps were only completely safe
for executor run-time (scan start) pruning. To prune at executor
startup, we had to ignore the steps involving exec Params. But this
doesn't really work in general, since there may be logic changes
needed as well --- for example, pruning according to the last operator's
btree strategy is the wrong thing if we're not applying that operator.
The rules embodied in gen_partprune_steps() and its minions are
sufficiently complicated that tracking their incremental effects in
other logic seems quite impractical.
Short of a complete redesign, the only safe fix seems to be to run
gen_partprune_steps() twice, once to create executor startup pruning
steps and then again for run-time pruning steps. We can save a few
cycles however by noting during the first scan whether we rejected
any clauses because they involved exec Params --- if not, we don't
need to do the second scan.
In support of this, refactor the internal APIs in partprune.c to make
more use of passing information in the GeneratePruningStepsContext
struct, rather than as separate arguments.
This is, I hope, the last piece of our response to a bug report from
Alan Jackson. Back-patch to v11 where this code came in.
Discussion: https://postgr.es/m/FAD28A83-AC73-489E-A058-2681FA31D648@tvsquared.com
As reported by Tom, when ExecStoreMinimalTuple() had to perform a
conversion to store the minimal tuple in the slot, it forgot to
respect the shouldFree flag, and leaked the tuple into the current
memory context if true. Fix that by freeing the tuple in that case.
Looking at the relevant code made me (Andres) realize that not having
the shouldFree parameter to ExecForceStoreHeapTuple() was a bad
idea. Some callers had to locally implement the necessary logic, and
in one case it was missing, creating a potential per-group leak in
non-hashed aggregation.
The choice to not free the tuple in ExecComputeStoredGenerated() is
not pretty, but not introduced by this commit - I'll start a separate
discussion about it.
Reported-By: Tom Lane
Discussion: https://postgr.es/m/366.1555382816@sss.pgh.pa.us
This is an SQL-standard feature that allows creating columns that are
computed from expressions rather than assigned, similar to a view or
materialized view but on a column basis.
This implements one kind of generated column: stored (computed on
write). Another kind, virtual (computed on read), is planned for the
future, and some room is left for it.
Reviewed-by: Michael Paquier <michael@paquier.xyz>
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/b151f851-4019-bdb1-699e-ebab07d2f40a@2ndquadrant.com
Add command variants COMMIT AND CHAIN and ROLLBACK AND CHAIN, which
start new transactions with the same transaction characteristics as the
just finished one, per SQL standard.
Support for transaction chaining in PL/pgSQL is also added. This
functionality is especially useful when running COMMIT in a loop in
PL/pgSQL.
Reviewed-by: Fabien COELHO <coelho@cri.ensmp.fr>
Discussion: https://www.postgresql.org/message-id/flat/28536681-324b-10dc-ade8-ab46f7645a5a@2ndquadrant.com
This adds new, required, table AM callbacks for insert/delete/update
and lock_tuple. To be able to reasonably use those, the EvalPlanQual
mechanism had to be adapted, moving more logic into the AM.
Previously both delete/update/lock call-sites and the EPQ mechanism had
to have awareness of the specific tuple format to be able to fetch the
latest version of a tuple. Obviously that needs to be abstracted
away. To do so, move the logic that find the latest row version into
the AM. lock_tuple has a new flag argument,
TUPLE_LOCK_FLAG_FIND_LAST_VERSION, that forces it to lock the last
version, rather than the current one. It'd have been possible to do
so via a separate callback as well, but finding the last version
usually also necessitates locking the newest version, making it
sensible to combine the two. This replaces the previous use of
EvalPlanQualFetch(). Additionally HeapTupleUpdated, which previously
signaled either a concurrent update or delete, is now split into two,
to avoid callers needing AM specific knowledge to differentiate.
The move of finding the latest row version into tuple_lock means that
encountering a row concurrently moved into another partition will now
raise an error about "tuple to be locked" rather than "tuple to be
updated/deleted" - which is accurate, as that always happens when
locking rows. While possible slightly less helpful for users, it seems
like an acceptable trade-off.
As part of this commit HTSU_Result has been renamed to TM_Result, and
its members been expanded to differentiated between updating and
deleting. HeapUpdateFailureData has been renamed to TM_FailureData.
The interface to speculative insertion is changed so nodeModifyTable.c
does not have to set the speculative token itself anymore. Instead
there's a version of tuple_insert, tuple_insert_speculative, that
performs the speculative insertion (without requiring a flag to signal
that fact), and the speculative insertion is either made permanent
with table_complete_speculative(succeeded = true) or aborted with
succeeded = false).
Note that multi_insert is not yet routed through tableam, nor is
COPY. Changing multi_insert requires changes to copy.c that are large
enough to better be done separately.
Similarly, although simpler, CREATE TABLE AS and CREATE MATERIALIZED
VIEW are also only going to be adjusted in a later commit.
Author: Andres Freund and Haribabu Kommi
Discussion:
https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.dehttps://postgr.es/m/20190313003903.nwvrxi7rw3ywhdel@alap3.anarazel.dehttps://postgr.es/m/20160812231527.GA690404@alvherre.pgsql
This adds a flag "deterministic" to collations. If that is false,
such a collation disables various optimizations that assume that
strings are equal only if they are byte-wise equal. That then allows
use cases such as case-insensitive or accent-insensitive comparisons
or handling of strings with different Unicode normal forms.
This functionality is only supported with the ICU provider. At least
glibc doesn't appear to have any locales that work in a
nondeterministic way, so it's not worth supporting this for the libc
provider.
The term "deterministic comparison" in this context is from Unicode
Technical Standard #10
(https://unicode.org/reports/tr10/#Deterministic_Comparison).
This patch makes changes in three areas:
- CREATE COLLATION DDL changes and system catalog changes to support
this new flag.
- Many executor nodes and auxiliary code are extended to track
collations. Previously, this code would just throw away collation
information, because the eventually-called user-defined functions
didn't use it since they only cared about equality, which didn't
need collation information.
- String data type functions that do equality comparisons and hashing
are changed to take the (non-)deterministic flag into account. For
comparison, this just means skipping various shortcuts and tie
breakers that use byte-wise comparison. For hashing, we first need
to convert the input string to a canonical "sort key" using the ICU
analogue of strxfrm().
Reviewed-by: Daniel Verite <daniel@manitou-mail.org>
Reviewed-by: Peter Geoghegan <pg@bowt.ie>
Discussion: https://www.postgresql.org/message-id/flat/1ccc668f-4cbc-0bef-af67-450b47cdfee7@2ndquadrant.com
We still require AccessExclusiveLock on the partition itself, because
otherwise an insert that violates the newly-imposed partition
constraint could be in progress at the same time that we're changing
that constraint; only the lock level on the parent relation is
weakened.
To make this safe, we have to cope with (at least) three separate
problems. First, relevant DDL might commit while we're in the process
of building a PartitionDesc. If so, find_inheritance_children() might
see a new partition while the RELOID system cache still has the old
partition bound cached, and even before invalidation messages have
been queued. To fix that, if we see that the pg_class tuple seems to
be missing or to have a null relpartbound, refetch the value directly
from the table. We can't get the wrong value, because DETACH PARTITION
still requires AccessExclusiveLock throughout; if we ever want to
change that, this will need more thought. In testing, I found it quite
difficult to hit even the null-relpartbound case; the race condition
is extremely tight, but the theoretical risk is there.
Second, successive calls to RelationGetPartitionDesc might not return
the same answer. The query planner will get confused if lookup up the
PartitionDesc for a particular relation does not return a consistent
answer for the entire duration of query planning. Likewise, query
execution will get confused if the same relation seems to have a
different PartitionDesc at different times. Invent a new
PartitionDirectory concept and use it to ensure consistency. This
ensures that a single invocation of either the planner or the executor
sees the same view of the PartitionDesc from beginning to end, but it
does not guarantee that the planner and the executor see the same
view. Since this allows pointers to old PartitionDesc entries to
survive even after a relcache rebuild, also postpone removing the old
PartitionDesc entry until we're certain no one is using it.
For the most part, it seems to be OK for the planner and executor to
have different views of the PartitionDesc, because the executor will
just ignore any concurrently added partitions which were unknown at
plan time; those partitions won't be part of the inheritance
expansion, but invalidation messages will trigger replanning at some
point. Normally, this happens by the time the very next command is
executed, but if the next command acquires no locks and executes a
prepared query, it can manage not to notice until a new transaction is
started. We might want to tighten that up, but it's material for a
separate patch. There would still be a small window where a query
that started just after an ATTACH PARTITION command committed might
fail to notice its results -- but only if the command starts before
the commit has been acknowledged to the user. All in all, the warts
here around serializability seem small enough to be worth accepting
for the considerable advantage of being able to add partitions without
a full table lock.
Although in general the consequences of new partitions showing up
between planning and execution are limited to the query not noticing
the new partitions, run-time partition pruning will get confused in
that case, so that's the third problem that this patch fixes.
Run-time partition pruning assumes that indexes into the PartitionDesc
are stable between planning and execution. So, add code so that if
new partitions are added between plan time and execution time, the
indexes stored in the subplan_map[] and subpart_map[] arrays within
the plan's PartitionedRelPruneInfo get adjusted accordingly. There
does not seem to be a simple way to generalize this scheme to cope
with partitions that are removed, mostly because they could then get
added back again with different bounds, but it works OK for added
partitions.
This code does not try to ensure that every backend participating in
a parallel query sees the same view of the PartitionDesc. That
currently doesn't matter, because we never pass PartitionDesc
indexes between backends. Each backend will ignore the concurrently
added partitions which it notices, and it doesn't matter if different
backends are ignoring different sets of concurrently added partitions.
If in the future that matters, for example because we allow writes in
parallel query and want all participants to do tuple routing to the same
set of partitions, the PartitionDirectory concept could be improved to
share PartitionDescs across backends. There is a draft patch to
serialize and restore PartitionDescs on the thread where this patch
was discussed, which may be a useful place to start.
Patch by me. Thanks to Alvaro Herrera, David Rowley, Simon Riggs,
Amit Langote, and Michael Paquier for discussion, and to Alvaro
Herrera for some review.
Discussion: http://postgr.es/m/CA+Tgmobt2upbSocvvDej3yzokd7AkiT+PvgFH+a9-5VV1oJNSQ@mail.gmail.com
Discussion: http://postgr.es/m/CA+TgmoZE0r9-cyA-aY6f8WFEROaDLLL7Vf81kZ8MtFCkxpeQSw@mail.gmail.com
Discussion: http://postgr.es/m/CA+TgmoY13KQZF-=HNTrt9UYWYx3_oYOQpu9ioNT49jGgiDpUEA@mail.gmail.com
For the upcoming pluggable table access methods it's quite
inconvenient to store tuples as HeapTuples, as that'd require
converting tuples from a their native format into HeapTuples. Instead
use slots to manage epq tuples.
To fit into that scheme, change the foreign data wrapper callback
RefetchForeignRow, to store the tuple in a slot. Insist on using the
caller provided slot, so it conveniently can be stored in the
corresponding EPQ slot. As there is no in core user of
RefetchForeignRow, that change was done blindly, but we plan to test
that soon.
To avoid duplicating that work for row locks, move row locks to just
directly use the EPQ slots - it previously temporarily stored tuples
in LockRowsState.lr_curtuples, but that doesn't seem beneficial, given
we'd possibly end up with a significant number of additional slots.
The behaviour of es_epqTupleSet[rti -1] is now checked by
es_epqTupleSlot[rti -1] != NULL, as that is distinguishable from a
slot containing an empty tuple.
Author: Andres Freund, Haribabu Kommi, Ashutosh Bapat
Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de
In preparation for abstracting table storage, convert trigger.c to
track tuples in slots. Which also happens to make code calling
triggers simpler.
As the calling interface for triggers themselves is not changed in
this patch, HeapTuples still are extracted from the slot at that
time. But that's handled solely inside trigger.c, not visible to
callers. It's quite likely that we'll want to revise the external
trigger interface, but that's a separate large project.
As part of this work the slots used for old/new/return tuples are
moved from EState into ResultRelInfo, as different updated tables
might need different slots. The slots are now also now created
on-demand, which is good both from an efficiency POV, but also makes
the modifying code simpler.
Author: Andres Freund, Amit Khandekar and Ashutosh Bapat
Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de
After the introduction of tuple table slots all table AMs need to
support returning the table oid of the tuple stored in a slot created
by said AM. It does not make sense to re-implement that in every AM,
therefore move handling of table OIDs into the TupleTableSlot
structure itself. It's possible that we, at a later date, might want
to get rid of HeapTupleData.t_tableOid entirely, but doing so before
the abstractions for table AMs are integrated turns out to be too
hard, so delay that for now.
Similarly, every AM needs to support the concept of a tuple
identifier (tid / item pointer) for its tuples. It's quite possible
that we'll generalize the exact form of a tid at a future point (to
allow for things like index organized tables), but for now many parts
of the code know about tids, so there's not much point in abstracting
tids away. Therefore also move into slot (rather than providing API to
set/get the tid associated with the tuple in a slot).
Once table AM includes insert/updating/deleting tuples, the
responsibility to set the correct tid after such an action will move
into that. After that change, code doing such modifications, should
not have to deal with HeapTuples directly anymore.
Author: Andres Freund, Haribabu Kommi and Ashutosh Bapat
Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de
That avoids having to care about the lifetime of the
HeapTupleHeaderData passed to ExecStore[Buffer]HeapTuple(). That
doesn't make a huge difference for a plain HeapTupleTableSlot, but for
BufferHeapTupleTableSlot it can be a significant advantage, avoiding
the need to materialize slots where it's inconvenient to provide a
HeapTupleData with appropriate lifetime to point to the on-disk tuple.
It's quite possible that we'll want to add support functions for
constructing HeapTuples using that embedded HeapTupleData, but for now
callers do so themselves.
Author: Andres Freund
Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de
This allows to avoid an unnecessary pin/unpin cycle when storing a
tuple in an already pinned buffer into a slot, when the pin isn't
further needed at the call site.
Only a single caller for now (to ensure coverage), but upcoming
patches will increase use of the new function.
Author: Andres Freund
Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de
This has the advantage that the comparator expression, the table's
slot, etc do not have to be rebuilt. Additionally the simplehash.h
hashtable within the tuple hashtable now keeps its previous size and
doesn't need to be reallocated. That both reduces allocator overhead,
and improves performance in cases where the input estimation was off
by a significant factor.
To avoid an API/ABI break, the new parameter is exposed via the new
BuildTupleHashTableExt(), and BuildTupleHashTable() now is a wrapper
around the former, that continues to allocate the table itself in the
tablecxt.
Using this fixes performance issues discovered in the two bugs
referenced. This commit however has not converted the callers, that's
done in a separate commit.
Bug: #15592#15486
Reported-By: Jakub Janeček, Dmitry Marakasov
Author: Andres Freund
Discussion:
https://postgr.es/m/15486-05850f065da42931@postgresql.orghttps://postgr.es/m/20190114180423.ywhdg2iagzvh43we@alap3.anarazel.de
Backpatch: 11, this is a prerequisite for other fixes
The old name of this file was never a very good indication of what it
was for. Now that there's also access/relation.h, we have a potential
confusion hazard as well, so let's rename it to something more apropos.
Per discussion, "pathnodes.h" is reasonable, since a good fraction of
the file is Path node definitions.
While at it, tweak a couple of other headers that were gratuitously
importing relation.h into modules that don't need it.
Discussion: https://postgr.es/m/7719.1548688728@sss.pgh.pa.us
Before this change FunctionCallInfoData, the struct arguments etc for
V1 function calls are stored in, always had space for
FUNC_MAX_ARGS/100 arguments, storing datums and their nullness in two
arrays. For nearly every function call 100 arguments is far more than
needed, therefore wasting memory. Arg and argnull being two separate
arrays also guarantees that to access a single argument, two
cachelines have to be touched.
Change the layout so there's a single variable-length array with pairs
of value / isnull. That drastically reduces memory consumption for
most function calls (on x86-64 a two argument function now uses
64bytes, previously 936 bytes), and makes it very likely that argument
value and its nullness are on the same cacheline.
Arguments are stored in a new NullableDatum struct, which, due to
padding, needs more memory per argument than before. But as usually
far fewer arguments are stored, and individual arguments are cheaper
to access, that's still a clear win. It's likely that there's other
places where conversion to NullableDatum arrays would make sense,
e.g. TupleTableSlots, but that's for another commit.
Because the function call information is now variable-length
allocations have to take the number of arguments into account. For
heap allocations that can be done with SizeForFunctionCallInfoData(),
for on-stack allocations there's a new LOCAL_FCINFO(name, nargs) macro
that helps to allocate an appropriately sized and aligned variable.
Some places with stack allocation function call information don't know
the number of arguments at compile time, and currently variably sized
stack allocations aren't allowed in postgres. Therefore allow for
FUNC_MAX_ARGS space in these cases. They're not that common, so for
now that seems acceptable.
Because of the need to allocate FunctionCallInfo of the appropriate
size, older extensions may need to update their code. To avoid subtle
breakages, the FunctionCallInfoData struct has been renamed to
FunctionCallInfoBaseData. Most code only references FunctionCallInfo,
so that shouldn't cause much collateral damage.
This change is also a prerequisite for more efficient expression JIT
compilation (by allocating the function call information on the stack,
allowing LLVM to optimize it away); previously the size of the call
information caused problems inside LLVM's optimizer.
Author: Andres Freund
Reviewed-By: Tom Lane
Discussion: https://postgr.es/m/20180605172952.x34m5uz6ju6enaem@alap3.anarazel.de
This is the genam.h equivalent of 4c850ecec6 (which removed
heapam.h from a lot of other headers). There's still a few header
includes of genam.h, but not from central headers anymore.
As a few headers are not indirectly included anymore, execnodes.h and
relscan.h need a few additional includes. Some of the depended on
types were replacable by using the underlying structs, but e.g. for
Snapshot in execnodes.h that'd have gotten more invasive than
reasonable in this commit.
Like the aforementioned commit 4c850ecec6, this requires adding new
genam.h includes to a number of backend files, which likely is also
required in a few external projects.
Author: Andres Freund
Discussion: https://postgr.es/m/20190114000701.y4ttcb74jpskkcfb@alap3.anarazel.de
heapam.h previously was included in a number of widely used
headers (e.g. execnodes.h, indirectly in executor.h, ...). That's
problematic on its own, as heapam.h contains a lot of low-level
details that don't need to be exposed that widely, but becomes more
problematic with the upcoming introduction of pluggable table storage
- it seems inappropriate for heapam.h to be included that widely
afterwards.
heapam.h was largely only included in other headers to get the
HeapScanDesc typedef (which was defined in heapam.h, even though
HeapScanDescData is defined in relscan.h). The better solution here
seems to be to just use the underlying struct (forward declared where
necessary). Similar for BulkInsertState.
Another problem was that LockTupleMode was used in executor.h - parts
of the file tried to cope without heapam.h, but due to the fact that
it indirectly included it, several subsequent violations of that goal
were not not noticed. We could just reuse the approach of declaring
parameters as int, but it seems nicer to move LockTupleMode to
lockoptions.h - that's not a perfect location, but also doesn't seem
bad.
As a number of files relied on implicitly included heapam.h, a
significant number of files grew an explicit include. It's quite
probably that a few external projects will need to do the same.
Author: Andres Freund
Reviewed-By: Alvaro Herrera
Discussion: https://postgr.es/m/20190114000701.y4ttcb74jpskkcfb@alap3.anarazel.de
Previously tables declared WITH OIDS, including a significant fraction
of the catalog tables, stored the oid column not as a normal column,
but as part of the tuple header.
This special column was not shown by default, which was somewhat odd,
as it's often (consider e.g. pg_class.oid) one of the more important
parts of a row. Neither pg_dump nor COPY included the contents of the
oid column by default.
The fact that the oid column was not an ordinary column necessitated a
significant amount of special case code to support oid columns. That
already was painful for the existing, but upcoming work aiming to make
table storage pluggable, would have required expanding and duplicating
that "specialness" significantly.
WITH OIDS has been deprecated since 2005 (commit ff02d0a05280e0).
Remove it.
Removing includes:
- CREATE TABLE and ALTER TABLE syntax for declaring the table to be
WITH OIDS has been removed (WITH (oids[ = true]) will error out)
- pg_dump does not support dumping tables declared WITH OIDS and will
issue a warning when dumping one (and ignore the oid column).
- restoring an pg_dump archive with pg_restore will warn when
restoring a table with oid contents (and ignore the oid column)
- COPY will refuse to load binary dump that includes oids.
- pg_upgrade will error out when encountering tables declared WITH
OIDS, they have to be altered to remove the oid column first.
- Functionality to access the oid of the last inserted row (like
plpgsql's RESULT_OID, spi's SPI_lastoid, ...) has been removed.
The syntax for declaring a table WITHOUT OIDS (or WITH (oids = false)
for CREATE TABLE) is still supported. While that requires a bit of
support code, it seems unnecessary to break applications / dumps that
do not use oids, and are explicit about not using them.
The biggest user of WITH OID columns was postgres' catalog. This
commit changes all 'magic' oid columns to be columns that are normally
declared and stored. To reduce unnecessary query breakage all the
newly added columns are still named 'oid', even if a table's column
naming scheme would indicate 'reloid' or such. This obviously
requires adapting a lot code, mostly replacing oid access via
HeapTupleGetOid() with access to the underlying Form_pg_*->oid column.
The bootstrap process now assigns oids for all oid columns in
genbki.pl that do not have an explicit value (starting at the largest
oid previously used), only oids assigned later by oids will be above
FirstBootstrapObjectId. As the oid column now is a normal column the
special bootstrap syntax for oids has been removed.
Oids are not automatically assigned during insertion anymore, all
backend code explicitly assigns oids with GetNewOidWithIndex(). For
the rare case that insertions into the catalog via SQL are called for
the new pg_nextoid() function can be used (which only works on catalog
tables).
The fact that oid columns on system tables are now normal columns
means that they will be included in the set of columns expanded
by * (i.e. SELECT * FROM pg_class will now include the table's oid,
previously it did not). It'd not technically be hard to hide oid
column by default, but that'd mean confusing behavior would either
have to be carried forward forever, or it'd cause breakage down the
line.
While it's not unlikely that further adjustments are needed, the
scope/invasiveness of the patch makes it worthwhile to get merge this
now. It's painful to maintain externally, too complicated to commit
after the code code freeze, and a dependency of a number of other
patches.
Catversion bump, for obvious reasons.
Author: Andres Freund, with contributions by John Naylor
Discussion: https://postgr.es/m/20180930034810.ywp2c7awz7opzcfr@alap3.anarazel.de
This commit completes the work prepared in 1a0586de36, splitting the
old TupleTableSlot implementation (which could store buffer, heap,
minimal and virtual slots) into four different slot types. As
described in the aforementioned commit, this is done with the goal of
making tuple table slots extensible, to allow for pluggable table
access methods.
To achieve runtime extensibility for TupleTableSlots, operations on
slots that can differ between types of slots are performed using the
TupleTableSlotOps struct provided at slot creation time. That
includes information from the size of TupleTableSlot struct to be
allocated, initialization, deforming etc. See the struct's definition
for more detailed information about callbacks TupleTableSlotOps.
I decided to rename TTSOpsBufferTuple to TTSOpsBufferHeapTuple and
ExecCopySlotTuple to ExecCopySlotHeapTuple, as that seems more
consistent with other naming introduced in recent patches.
There's plenty optimization potential in the slot implementation, but
according to benchmarking the state after this commit has similar
performance characteristics to before this set of changes, which seems
sufficient.
There's a few changes in execReplication.c that currently need to poke
through the slot abstraction, that'll be repaired once the pluggable
storage patchset provides the necessary infrastructure.
Author: Andres Freund and Ashutosh Bapat, with changes by Amit Khandekar
Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
This speeds up write operations (INSERT, UPDATE, DELETE, COPY, as well
as the future MERGE) on partitioned tables.
This changes the setup for tuple routing so that it does far less work
during the initial setup and pushes more work out to when partitions
receive tuples. PartitionDispatchData structs for sub-partitioned
tables are only created when a tuple gets routed through it. The
possibly large arrays in the PartitionTupleRouting struct have largely
been removed. The partitions[] array remains but now never contains any
NULL gaps. Previously the NULLs had to be skipped during
ExecCleanupTupleRouting(), which could add a large overhead to the
cleanup when the number of partitions was large. The partitions[] array
is allocated small to start with and only enlarged when we route tuples
to enough partitions that it runs out of space. This allows us to keep
simple single-row partition INSERTs running quickly. Redesign
The arrays in PartitionTupleRouting which stored the tuple translation maps
have now been removed. These have been moved out into a
PartitionRoutingInfo struct which is an additional field in ResultRelInfo.
The find_all_inheritors() call still remains by far the slowest part of
ExecSetupPartitionTupleRouting(). This commit just removes the other slow
parts.
In passing also rename the tuple translation maps from being ParentToChild
and ChildToParent to being RootToPartition and PartitionToRoot. The old
names mislead you into thinking that a partition of some sub-partitioned
table would translate to the rowtype of the sub-partitioned table rather
than the root partitioned table.
Authors: David Rowley and Amit Langote, heavily revised by Álvaro Herrera
Testing help from Jesper Pedersen and Kato Sho.
Discussion: https://postgr.es/m/CAKJS1f_1RJyFquuCKRFHTdcXqoPX-PYqAd7nz=GVBwvGh4a6xA@mail.gmail.com
Previously this information was computed when JIT compiling an
expression. But the information is useful for assertions in the
non-JIT case too (for assertions), therefore it makes sense to move
it.
This will, in a followup commit, allow to treat different slot types
differently. E.g. for virtual slots there's no need to generate a JIT
function to deform the slot.
Author: Andres Freund
Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
Upcoming work intends to allow pluggable ways to introduce new ways of
storing table data. Accessing those table access methods from the
executor requires TupleTableSlots to be carry tuples in the native
format of such storage methods; otherwise there'll be a significant
conversion overhead.
Different access methods will require different data to store tuples
efficiently (just like virtual, minimal, heap already require fields
in TupleTableSlot). To allow that without requiring additional pointer
indirections, we want to have different structs (embedding
TupleTableSlot) for different types of slots. Thus different types of
slots are needed, which requires adapting creators of slots.
The slot that most efficiently can represent a type of tuple in an
executor node will often depend on the type of slot a child node
uses. Therefore we need to track the type of slot is returned by
nodes, so parent slots can create slots based on that.
Relatedly, JIT compilation of tuple deforming needs to know which type
of slot a certain expression refers to, so it can create an
appropriate deforming function for the type of tuple in the slot.
But not all nodes will only return one type of slot, e.g. an append
node will potentially return different types of slots for each of its
subplans.
Therefore add function that allows to query the type of a node's
result slot, and whether it'll always be the same type (whether it's
fixed). This can be queried using ExecGetResultSlotOps().
The scan, result, inner, outer type of slots are automatically
inferred from ExecInitScanTupleSlot(), ExecInitResultSlot(),
left/right subtrees respectively. If that's not correct for a node,
that can be overwritten using new fields in PlanState.
This commit does not introduce the actually abstracted implementation
of different kind of TupleTableSlots, that will be left for a followup
commit. The different types of slots introduced will, for now, still
use the same backing implementation.
While this already partially invalidates the big comment in
tuptable.h, it seems to make more sense to update it later, when the
different TupleTableSlot implementations actually exist.
Author: Ashutosh Bapat and Andres Freund, with changes by Amit Khandekar
Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
Previously materializing a slot always returned a HeapTuple. As
current work aims to reduce the reliance on HeapTuples (so other
storage systems can work efficiently), that needs to change. Thus
split the tasks of materializing a slot (i.e. making it independent
from the underlying storage / other memory contexts) from fetching a
HeapTuple from the slot. For brevity, allow to fetch a HeapTuple from
a slot and materializing the slot at the same time, controlled by a
parameter.
For now some callers of ExecFetchSlotHeapTuple, with materialize =
true, expect that changes to the heap tuple will be reflected in the
underlying slot. Those places will be adapted in due course, so while
not pretty, that's OK for now.
Also rename ExecFetchSlotTuple to ExecFetchSlotHeapTupleDatum and
ExecFetchSlotTupleDatum to ExecFetchSlotHeapTupleDatum, as it's likely
that future storage methods will need similar methods. There already
is ExecFetchSlotMinimalTuple, so the new names make the naming scheme
more coherent.
Author: Ashutosh Bapat and Andres Freund, with changes by Amit Khandekar
Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
In a lot of nodes the return slot is not required. That can either be
because the node doesn't do any projection (say an Append node), or
because the node does perform projections but the projection is
optimized away because the projection would yield an identical row.
Slots aren't that small, especially for wide rows, so it's worthwhile
to avoid creating them. It's not possible to just skip creating the
slot - it's currently used to determine the tuple descriptor returned
by ExecGetResultType(). So separate the determination of the result
type from the slot creation. The work previously done internally
ExecInitResultTupleSlotTL() can now also be done separately with
ExecInitResultTypeTL() and ExecInitResultSlot(). That way nodes that
aren't guaranteed to need a result slot, can use
ExecInitResultTypeTL() to determine the result type of the node, and
ExecAssignScanProjectionInfo() (via
ExecConditionalAssignProjectionInfo()) determines that a result slot
is needed, it is created with ExecInitResultSlot().
Besides the advantage of avoiding to create slots that then are
unused, this is necessary preparation for later patches around tuple
table slot abstraction. In particular separating the return descriptor
and slot is a prerequisite to allow JITing of tuple deforming with
knowledge of the underlying tuple format, and to avoid unnecessarily
creating JITed tuple deforming for virtual slots.
This commit removes a redundant argument from
ExecInitResultTupleSlotTL(). While this commit touches a lot of the
relevant lines anyway, it'd normally still not worthwhile to cause
breakage, except that aforementioned later commits will touch *all*
ExecInitResultTupleSlotTL() callers anyway (but fits worse
thematically).
Author: Andres Freund
Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
This mainly de-duplicates code. As evaluating a system variable isn't
the hottest path and the current inline implementation ends up calling
out to an external function anyway, this is OK from a performance POV.
The main motivation for de-duplicating is the upcoming slot
abstraction work, after which there's not guaranteed to be a HeapTuple
backing the slot.
Author: Andres Freund, Amit Khandekar
Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
There's several reasons for this change:
1) It reduces the total size of TupleTableSlot / reduces alignment
padding, making the commonly accessed members fit into a single
cacheline (but we currently do not force proper alignment, so
that's not yet guaranteed to be helpful)
2) Combining the booleans into a flag allows to combine read/writes
from memory.
3) With the upcoming slot abstraction changes, it allows to have core
and extended flags, in a memory efficient way.
Author: Ashutosh Bapat and Andres Freund
Discussion: https://postgr.es/m/20180220224318.gw4oe5jadhpmcdnm@alap3.anarazel.de
heaptuple.c was never a particular good fit for slot_getattr(),
slot_getsomeattrs() and slot_getmissingattrs(), but in upcoming
changes slots will be made more abstract (allowing slots that contain
different types of tuples), making it clearly the wrong place.
Note that slot_deform_tuple() remains in it's current place, as it
clearly deals with a HeapTuple. getmissingattrs() also remains, but
it's less clear that that's correct - but execTuples.c wouldn't be the
right place.
Author: Ashutosh Bapat.
Discussion: https://postgr.es/m/20180220224318.gw4oe5jadhpmcdnm@alap3.anarazel.de
We already have appropriate locks on every relation listed in the
query's rangetable before we reach the executor. Take the next step
in exploiting that knowledge by removing code that worries about
taking locks on non-leaf result relations in a partitioned table.
In particular, get rid of ExecLockNonLeafAppendTables and a stanza in
InitPlan that asserts we already have locks on certain such tables.
In passing, clean up some now-obsolete comments in InitPlan.
Amit Langote, reviewed by David Rowley and Jesper Pedersen,
and whacked around a bit more by me
Discussion: https://postgr.es/m/468c85d9-540e-66a2-1dde-fec2b741e688@lab.ntt.co.jp
Instead of doing a lot of list_nth() accesses to es_range_table,
create a flattened pointer array during executor startup and index
into that to get at individual RangeTblEntrys.
This eliminates one source of O(N^2) behavior with lots of partitions.
(I'm not exactly convinced that it's the most important source, but
it's an easy one to fix.)
Amit Langote and David Rowley
Discussion: https://postgr.es/m/468c85d9-540e-66a2-1dde-fec2b741e688@lab.ntt.co.jp
Create an array estate->es_relations[] paralleling the es_range_table,
and store references to Relations (relcache entries) there, so that any
given RT entry is opened and closed just once per executor run. Scan
nodes typically still call ExecOpenScanRelation, but ExecCloseScanRelation
is no more; relation closing is now done centrally in ExecEndPlan.
This is slightly more complex than one would expect because of the
interactions with relcache references held in ResultRelInfo nodes.
The general convention is now that ResultRelInfo->ri_RelationDesc does
not represent a separate relcache reference and so does not need to be
explicitly closed; but there is an exception for ResultRelInfos in the
es_trig_target_relations list, which are manufactured by
ExecGetTriggerResultRel and have to be cleaned up by
ExecCleanUpTriggerState. (That much was true all along, but these
ResultRelInfos are now more different from others than they used to be.)
To allow the partition pruning logic to make use of es_relations[] rather
than having its own relcache references, adjust PartitionedRelPruneInfo
to store an RT index rather than a relation OID.
Amit Langote, reviewed by David Rowley and Jesper Pedersen,
some mods by me
Discussion: https://postgr.es/m/468c85d9-540e-66a2-1dde-fec2b741e688@lab.ntt.co.jp
It's inefficient to use a single slot for mapping between tuple
descriptors for multiple tuples, as previously done when using
ConvertPartitionTupleSlot(), as that means the slot's tuple descriptors
change for every tuple.
Previously we also, via ConvertPartitionTupleSlot(), built new tuples
after the mapping even in cases where we, immediately afterwards,
access individual columns again.
Refactor the code so one slot, on demand, is used for each
partition. That avoids having to change the descriptor (and allows to
use the more efficient "fixed" tuple slots). Then use slot->slot
mapping, to avoid unnecessarily forming a tuple.
As the naming between the tuple and slot mapping functions wasn't
consistent, rename them to execute_attr_map_{tuple,slot}. It's likely
that we'll also rename convert_tuples_by_* to denote that these
functions "only" build a map, but that's left for later.
Author: Amit Khandekar and Amit Langote, editorialized by me
Reviewed-By: Amit Langote, Amit Khandekar, Andres Freund
Discussion:
https://postgr.es/m/CAJ3gD9fR0wRNeAE8VqffNTyONS_UfFPRpqxhnD9Q42vZB+Jvpg@mail.gmail.comhttps://postgr.es/m/e4f9d743-cd4b-efb0-7574-da21d86a7f36%40lab.ntt.co.jp
Backpatch: -
Upcoming changes introduce further types of tuple table slots, in
preparation of making table storage pluggable. New storage methods
will have different representation of tuples, therefore the slot
accessor should refer explicitly to heap tuples.
Instead of just renaming the functions, split it into one function
that accepts heap tuples not residing in buffers, and one accepting
ones in buffers. Previously one function was used for both, but that
was a bit awkward already, and splitting will allow us to represent
slot types for tuples in buffers and normal memory separately.
This is split out from the patch introducing abstract slots, as this
largely consists out of mechanical changes.
Author: Ashutosh Bapat
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/20180220224318.gw4oe5jadhpmcdnm@alap3.anarazel.de
Previously it was an int / 4 bytes. The maximum number of attributes
in a tuple is restricted by the maximum value Var->varattno, which is
an AttrNumber/int16. Hence use the same data type for
TupleTableSlot->tts_nvalid.
Author: Ashutosh Bapat
Discussion: https://postgr.es/m/20180220224318.gw4oe5jadhpmcdnm@alap3.anarazel.de
Previously, when using parallel query, EXPLAIN (ANALYZE)'s JIT
compilation timings did not include the overhead from doing so on the
workers. Fix that.
We do so by simply aggregating the cost of doing JIT compilation on
workers and the leader together. Arguably that's not quite accurate,
because the total time spend doing so is spent in parallel - but it's
hard to do much better. For additional detail, when VERBOSE is
specified, the stats for workers are displayed separately.
Author: Amit Khandekar and Andres Freund
Discussion: https://postgr.es/m/CAJ3gD9eLrz51RK_gTkod+71iDcjpB_N8eC6vU2AW-VicsAERpQ@mail.gmail.com
Backpatch: 11-
The EvalPlanQual machinery assumes that any initplans (that is,
uncorrelated sub-selects) used during an EPQ recheck would have already
been evaluated during the main query; this is implicit in the fact that
execPlan pointers are not copied into the EPQ estate's es_param_exec_vals.
But it's possible for that assumption to fail, if the initplan is only
reached conditionally. For example, a sub-select inside a CASE expression
could be reached during a recheck when it had not been previously, if the
CASE test depends on a column that was just updated.
This bug is old, appearing to date back to my rewrite of EvalPlanQual in
commit 9f2ee8f28, but was not detected until Kyle Samson reported a case.
To fix, force all not-yet-evaluated initplans used within the EPQ plan
subtree to be evaluated at the start of the recheck, before entering the
EPQ environment. This could be inefficient, if such an initplan is
expensive and goes unused again during the recheck --- but that's piling
one layer of improbability atop another. It doesn't seem worth adding
more complexity to prevent that, at least not in the back branches.
It was convenient to use the new-in-v11 ExecEvalParamExecParams function
to implement this, but I didn't like either its name or the specifics of
its API, so revise that.
Back-patch all the way. Rather than rewrite the patch to avoid depending
on bms_next_member() in the oldest branches, I chose to back-patch that
function into 9.4 and 9.3. (This isn't the first time back-patches have
needed that, and it exhausted my patience.) I also chose to back-patch
some test cases added by commits 71404af2a and 342a1ffa2 into 9.4 and 9.3,
so that the 9.x versions of eval-plan-qual.spec are all the same.
Andrew Gierth diagnosed the problem and contributed the added test cases,
though the actual code changes are by me.
Discussion: https://postgr.es/m/A033A40A-B234-4324-BE37-272279F7B627@tripadvisor.com
For some reason pg_waldump is including tuptable.h, and the recent
addition of a static inline function to it is causing problems on
older buildfarm members that fail to optimize such functions away
completely. I wonder if this situation doesn't mean that some header
refactoring is called for ... but as a band-aid, wrap the static
function in "#ifndef FRONTEND".
Discussion: https://postgr.es/m/20180824154237.mabsv6fsz5q37bma@alap3.anarazel.de
This patch removes two sources of interference between nominally
independent functions when one SPI-using function calls another,
perhaps without knowing that it does so.
Chapman Flack pointed out that xml.c's query_to_xml_internal() expects
SPI_tuptable and SPI_processed to stay valid across datatype output
function calls; but it's possible that such a call could involve
re-entrant use of SPI. It seems likely that there are similar hazards
elsewhere, if not in the core code then in third-party SPI users.
Previously SPI_finish() reset SPI's API globals to zeroes/nulls, which
would typically make for a crash in such a situation. Restoring them
to the values they had at SPI_connect() seems like a considerably more
useful behavior, and it still meets the design goal of not leaving any
dangling pointers to tuple tables of the function being exited.
Also, cause SPI_connect() to reset these variables to zeroes/nulls after
saving them. This prevents interference in the opposite direction: it's
possible that a SPI-using function that's only ever been tested standalone
contains assumptions that these variables start out as zeroes. That was
the case as long as you were the outermost SPI user, but not so much for
an inner user. Now it's consistent.
Report and fix suggestion by Chapman Flack, actual patch by me.
Back-patch to all supported branches.
Discussion: https://postgr.es/m/9fa25bef-2e4f-1c32-22a4-3ad0723c4a17@anastigmatix.net
Code in slot_getallattrs() is the same as if slot_getsomeattrs() is
called with number of attributes specified in the tuple
descriptor. Implement it that way instead of duplicating the code
between those two functions.
This is part of a patchseries abstracting TupleTableSlots so they can
store arbitrary forms of tuples, but is a nice enough cleanup on its
own.
Author: Ashutosh Bapat
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/20180220224318.gw4oe5jadhpmcdnm@alap3.anarazel.de
The previous coding here supposed that if run-time partitioning applied to
a particular Append/MergeAppend plan, then all child plans of that node
must be members of a single partitioning hierarchy. This is totally wrong,
since an Append could be formed from a UNION ALL: we could have multiple
hierarchies sharing the same Append, or child plans that aren't part of any
hierarchy.
To fix, restructure the related plan-time and execution-time data
structures so that we can have a separate list or array for each
partitioning hierarchy. Also track subplans that are not part of any
hierarchy, and make sure they don't get pruned.
Per reports from Phil Florent and others. Back-patch to v11, since
the bug originated there.
David Rowley, with a lot of cosmetic adjustments by me; thanks also
to Amit Langote for review.
Discussion: https://postgr.es/m/HE1PR03MB17068BB27404C90B5B788BCABA7B0@HE1PR03MB1706.eurprd03.prod.outlook.com
CopyFrom allows multi-inserts to be used for non-partitioned tables, but
this was disabled for partitioned tables. The reason for this appeared
to be that the tuple may not belong to the same partition as the
previous tuple did. Not allowing multi-inserts here greatly slowed down
imports into partitioned tables. These could take twice as long as a
copy to an equivalent non-partitioned table. It seems wise to do
something about this, so this change allows the multi-inserts by
flushing the so-far inserted tuples to the partition when the next tuple
does not belong to the same partition, or when the buffer fills. This
improves performance when the next tuple in the stream commonly belongs
to the same partition as the previous tuple.
In cases where the target partition changes on every tuple, using
multi-inserts slightly slows the performance. To get around this we
track the average size of the batches that have been inserted and
adaptively enable or disable multi-inserts based on the size of the
batch. Some testing was done and the regression only seems to exist
when the average size of the insert batch is close to 1, so let's just
enable multi-inserts when the average size is at least 1.3. More
performance testing might reveal a better number for, this, but since
the slowdown was only 1-2% it does not seem critical enough to spend too
much time calculating it. In any case it may depend on other factors
rather than just the size of the batch.
Allowing multi-inserts for partitions required a bit of work around the
per-tuple memory contexts as we must flush the tuples when the next
tuple does not belong the same partition. In which case there is no
good time to reset the per-tuple context, as we've already built the new
tuple by this time. In order to work around this we maintain two
per-tuple contexts and just switch between them every time the partition
changes and reset the old one. This does mean that the first of each
batch of tuples is not allocated in the same memory context as the
others, but that does not matter since we only reset the context once
the previous batch has been inserted.
Author: David Rowley <david.rowley@2ndquadrant.com>
Reviewed-by: Melanie Plageman <melanieplageman@gmail.com>
The previous coding saved pointers into the partitioned table's relcache
entry, but then closed the relcache entry, causing those pointers to
nominally become dangling. Actual trouble would be seen in the field
only if a relcache flush occurred mid-query, but that's hardly out of
the question.
While we could fix this by copying all the data in question at query
start, it seems better to just hold the relcache entry open for the
whole query.
While at it, improve the handling of support-function lookups: do that
once per query not once per pruning test. There's still something to be
desired here, in that we fail to exploit the possibility of caching data
across queries in the fn_extra fields of the relcache's FmgrInfo structs,
which could happen if we just used those structs in-place rather than
copying them. However, combining that with the possibility of per-query
lookups of cross-type comparison functions seems to require changes in the
APIs of a lot of the pruning support functions, so it's too invasive to
consider as part of this patch. A win would ensue only for complex
partition key data types (e.g. arrays), so it may not be worth the
trouble.
David Rowley and Tom Lane
Discussion: https://postgr.es/m/17850.1528755844@sss.pgh.pa.us
Starting with commit f0e44751d7, ExecConstraints was in charge of
running the partition constraint; commit 19c47e7c82 modified that so
that caller could request to skip that checking depending on some
conditions, but that commit and 15ce775faa together introduced a small
bug there which caused ExecInsert to request skipping the constraint
check but have this not be honored -- in effect doing the check twice.
This could have been fixed in a very small patch, but on further
analysis of the involved function and its callsites, it turns out to be
simpler to give the responsibility of checking the partition constraint
fully to the caller, and return ExecConstraints to its original
(pre-partitioning) shape where it only checked tuple descriptor-related
constraints. Each caller must do partition constraint checking on its
own schedule, which is more convenient after commit 2f17844104 anyway.
Reported-by: David Rowley
Author: David Rowley, Álvaro Herrera
Reviewed-by: Amit Langote, Amit Khandekar, Simon Riggs
Discussion: https://postgr.es/m/CAKJS1f8w8+awsxgea8wt7_UX8qzOQ=Tm1LD+U1fHqBAkXxkW2w@mail.gmail.com
The initial coding of the run-time-pruning feature only coped with cases
where the partition key(s) are compared to Params. That is a bit silly;
we can allow it to work with any non-Var-containing stable expression, as
long as we take special care with expressions containing PARAM_EXEC Params.
The code is hardly any longer this way, and it's considerably clearer
(IMO at least). Per gripe from Pavel Stehule.
David Rowley, whacked around a bit by me
Discussion: https://postgr.es/m/CAFj8pRBjrufA3ocDm8o4LPGNye9Y+pm1b9kCwode4X04CULG3g@mail.gmail.com
Since the SPI stack has been moved from TopTransactionContext to
TopMemoryContext, setting _SPI_stack to NULL in AtEOXact_SPI() leaks
memory. In fact, we don't need to do that anymore: We just leave the
allocated stack around for the next SPI use.
Also, refactor the SPI cleanup so that it is run both at transaction end
and when returning to the main loop on an exception. The latter is
necessary when a procedure calls a COMMIT or ROLLBACK command that
itself causes an error.
This reverts commits d204ef6377,
83454e3c2b and a few more commits thereafter
(complete list at the end) related to MERGE feature.
While the feature was fully functional, with sufficient test coverage and
necessary documentation, it was felt that some parts of the executor and
parse-analyzer can use a different design and it wasn't possible to do that in
the available time. So it was decided to revert the patch for PG11 and retry
again in the future.
Thanks again to all reviewers and bug reporters.
List of commits reverted, in reverse chronological order:
f1464c5380 Improve parse representation for MERGE
ddb4158579 MERGE syntax diagram correction
530e69e59b Allow cpluspluscheck to pass by renaming variable
01b88b4df5 MERGE minor errata
3af7b2b0d4 MERGE fix variable warning in non-assert builds
a5d86181ec MERGE INSERT allows only one VALUES clause
4b2d44031f MERGE post-commit review
4923550c20 Tab completion for MERGE
aa3faa3c7a WITH support in MERGE
83454e3c2b New files for MERGE
d204ef6377 MERGE SQL Command following SQL:2016
Author: Pavan Deolasee
Reviewed-by: Michael Paquier
The HeapFetches counter was using a simple value in IndexOnlyScanState,
which fails to propagate values from parallel workers; so the counts are
wrong when IndexOnlyScan runs in parallel. Move it to Instrumentation,
like all the other counters.
While at it, change INSERT ON CONFLICT conflicting tuple counter to use
the new ntuples2 instead of nfiltered2, which is a blatant misuse.
Discussion: https://postgr.es/m/20180409215851.idwc75ct2bzi6tea@alvherre.pgsql
Existing partition pruning is only able to work at plan time, for query
quals that appear in the parsed query. This is good but limiting, as
there can be parameters that appear later that can be usefully used to
further prune partitions.
This commit adds support for pruning subnodes of Append which cannot
possibly contain any matching tuples, during execution, by evaluating
Params to determine the minimum set of subnodes that can possibly match.
We support more than just simple Params in WHERE clauses. Support
additionally includes:
1. Parameterized Nested Loop Joins: The parameter from the outer side of the
join can be used to determine the minimum set of inner side partitions to
scan.
2. Initplans: Once an initplan has been executed we can then determine which
partitions match the value from the initplan.
Partition pruning is performed in two ways. When Params external to the plan
are found to match the partition key we attempt to prune away unneeded Append
subplans during the initialization of the executor. This allows us to bypass
the initialization of non-matching subplans meaning they won't appear in the
EXPLAIN or EXPLAIN ANALYZE output.
For parameters whose value is only known during the actual execution
then the pruning of these subplans must wait. Subplans which are
eliminated during this stage of pruning are still visible in the EXPLAIN
output. In order to determine if pruning has actually taken place, the
EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never
executed due to the elimination of the partition then the execution
timing area will state "(never executed)". Whereas, if, for example in
the case of parameterized nested loops, the number of loops stated in
the EXPLAIN ANALYZE output for certain subplans may appear lower than
others due to the subplan having been scanned fewer times. This is due
to the list of matching subnodes having to be evaluated whenever a
parameter which was found to match the partition key changes.
This commit required some additional infrastructure that permits the
building of a data structure which is able to perform the translation of
the matching partition IDs, as returned by get_matching_partitions, into
the list index of a subpaths list, as exist in node types such as
Append, MergeAppend and ModifyTable. This allows us to translate a list
of clauses into a Bitmapset of all the subpath indexes which must be
included to satisfy the clause list.
Author: David Rowley, based on an earlier effort by Beena Emerson
Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi,
Jesper Pedersen
Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
When an update moves a row between partitions (supported since
2f17844104), our normal logic for following update chains in READ
COMMITTED mode doesn't work anymore. Cross partition updates are
modeled as an delete from the old and insert into the new
partition. No ctid chain exists across partitions, and there's no
convenient space to introduce that link.
Not throwing an error in a partitioned context when one would have
been thrown without partitioning is obviously problematic. This commit
introduces infrastructure to detect when a tuple has been moved, not
just plainly deleted. That allows to throw an error when encountering
a deletion that's actually a move, while attempting to following a
ctid chain.
The row deleted as part of a cross partition update is marked by
pointing it's t_ctid to an invalid block, instead of self as a normal
update would. That was deemed to be the least invasive and most
future proof way to represent the knowledge, given how few infomask
bits are there to be recycled (there's also some locking issues with
using infomask bits).
External code following ctid chains should be updated to check for
moved tuples. The most likely consequence of not doing so is a missed
error.
Author: Amul Sul, editorialized by me
Reviewed-By: Amit Kapila, Pavan Deolasee, Andres Freund, Robert Haas
Discussion: http://postgr.es/m/CAAJ_b95PkwojoYfz0bzXU8OokcTVGzN6vYGCNVUukeUDrnF3dw@mail.gmail.com
Also enable this for postgres_fdw.
Etsuro Fujita, based on an earlier patch by Amit Langote. The larger
patch series of which this is a part has been reviewed by Amit
Langote, David Fetter, Maksim Milyutin, Álvaro Herrera, Stephen Frost,
and me. Minor documentation changes to the final version by me.
Discussion: http://postgr.es/m/29906a26-da12-8c86-4fb9-d8f88442f2b9@lab.ntt.co.jp
Review comments from Andres Freund
* Consolidate code into AfterTriggerGetTransitionTable()
* Rename nodeMerge.c to execMerge.c
* Rename nodeMerge.h to execMerge.h
* Move MERGE handling in ExecInitModifyTable()
into a execMerge.c ExecInitMerge()
* Move mt_merge_subcommands flags into execMerge.h
* Rename opt_and_condition to opt_merge_when_and_condition
* Wordsmith various comments
Author: Pavan Deolasee
Reviewer: Simon Riggs
MERGE performs actions that modify rows in the target table
using a source table or query. MERGE provides a single SQL
statement that can conditionally INSERT/UPDATE/DELETE rows
a task that would other require multiple PL statements.
e.g.
MERGE INTO target AS t
USING source AS s
ON t.tid = s.sid
WHEN MATCHED AND t.balance > s.delta THEN
UPDATE SET balance = t.balance - s.delta
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED AND s.delta > 0 THEN
INSERT VALUES (s.sid, s.delta)
WHEN NOT MATCHED THEN
DO NOTHING;
MERGE works with regular and partitioned tables, including
column and row security enforcement, as well as support for
row, statement and transition triggers.
MERGE is optimized for OLTP and is parameterizable, though
also useful for large scale ETL/ELT. MERGE is not intended
to be used in preference to existing single SQL commands
for INSERT, UPDATE or DELETE since there is some overhead.
MERGE can be used statically from PL/pgSQL.
MERGE does not yet support inheritance, write rules,
RETURNING clauses, updatable views or foreign tables.
MERGE follows SQL Standard per the most recent SQL:2016.
Includes full tests and documentation, including full
isolation tests to demonstrate the concurrent behavior.
This version written from scratch in 2017 by Simon Riggs,
using docs and tests originally written in 2009. Later work
from Pavan Deolasee has been both complex and deep, leaving
the lead author credit now in his hands.
Extensive discussion of concurrency from Peter Geoghegan,
with thanks for the time and effort contributed.
Various issues reported via sqlsmith by Andreas Seltenreich
Authors: Pavan Deolasee, Simon Riggs
Reviewer: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs
Discussion:
https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.comhttps://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
MERGE performs actions that modify rows in the target table
using a source table or query. MERGE provides a single SQL
statement that can conditionally INSERT/UPDATE/DELETE rows
a task that would other require multiple PL statements.
e.g.
MERGE INTO target AS t
USING source AS s
ON t.tid = s.sid
WHEN MATCHED AND t.balance > s.delta THEN
UPDATE SET balance = t.balance - s.delta
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED AND s.delta > 0 THEN
INSERT VALUES (s.sid, s.delta)
WHEN NOT MATCHED THEN
DO NOTHING;
MERGE works with regular and partitioned tables, including
column and row security enforcement, as well as support for
row, statement and transition triggers.
MERGE is optimized for OLTP and is parameterizable, though
also useful for large scale ETL/ELT. MERGE is not intended
to be used in preference to existing single SQL commands
for INSERT, UPDATE or DELETE since there is some overhead.
MERGE can be used statically from PL/pgSQL.
MERGE does not yet support inheritance, write rules,
RETURNING clauses, updatable views or foreign tables.
MERGE follows SQL Standard per the most recent SQL:2016.
Includes full tests and documentation, including full
isolation tests to demonstrate the concurrent behavior.
This version written from scratch in 2017 by Simon Riggs,
using docs and tests originally written in 2009. Later work
from Pavan Deolasee has been both complex and deep, leaving
the lead author credit now in his hands.
Extensive discussion of concurrency from Peter Geoghegan,
with thanks for the time and effort contributed.
Various issues reported via sqlsmith by Andreas Seltenreich
Authors: Pavan Deolasee, Simon Riggs
Reviewers: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs
Discussion:
https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.comhttps://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
So far, a nested CALL or DO in PL/pgSQL would not establish a context
where transaction control statements were allowed. This fixes that by
handling CALL and DO specially in PL/pgSQL, passing the atomic/nonatomic
execution context through and doing the required management around
transaction boundaries.
Reviewed-by: Tomas Vondra <tomas.vondra@2ndquadrant.com>
Instead using memset to set tts_isnull, call the new
slot_getmissingattrs().
Also fix a bug (= instead of >=) in the code generation. Normally = is
correct, but when repeatedly deforming fields not in a
tuple (e.g. deform up to natts + 1 and then natts + 2) >= is needed.
Discussion: https://postgr.es/m/20180328010053.i2qvsuuusst4lgmc@alap3.anarazel.de
Performing JIT compilation for deforming gains performance benefits
over unJITed deforming from compile-time knowledge of the tuple
descriptor. Fixed column widths, NOT NULLness, etc can be taken
advantage of.
Right now the JITed deforming is only used when deforming tuples as
part of expression evaluation (and obviously only if the descriptor is
known). It's likely to be beneficial in other cases, too.
By default tuple deforming is JITed whenever an expression is JIT
compiled. There's a separate boolean GUC controlling it, but that's
expected to be primarily useful for development and benchmarking.
Docs will follow in a later commit containing docs for the whole JIT
feature.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
For any interesting JIT target, fields inside structs need to be
accessed. b96d550e contains infrastructure for syncing the definition
of types between postgres C code and runtime code generation with
LLVM. But that doesn't sync the number or names of fields inside
structs, just the types (including padding etc).
One option would be to hardcode the offset numbers in the JIT code,
but that'd be hard to keep in sync. Instead add macros indicating the
field offset to the fields that need to be accessed. Not pretty, but
manageable.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
"UPDATE/DELETE WHERE CURRENT OF cursor_name" failed, with an error message
like "cannot extract system attribute from virtual tuple", if the cursor
was using a index-only scan for the target table. Fix it by digging the
current TID out of the indexscan state.
It seems likely that the same failure could occur for CustomScan plans
and perhaps some FDW plan types, so that leaving this to be treated as an
internal error with an obscure message isn't as good an idea as it first
seemed. Hence, add a bit of heaptuple.c infrastructure to let us deliver
a more on-topic message. I chose to make the message match what you get
for the case where execCurrentOf can't identify the target scan node at
all, "cursor "foo" is not a simply updatable scan of table "bar"".
Perhaps it should be different, but we can always adjust that later.
In the future, it might be nice to provide hooks that would let custom
scan providers and/or FDWs deal with this in other ways; but that's
not a suitable topic for a back-patchable bug fix.
It's been like this all along, so back-patch to all supported branches.
Yugo Nagata and Tom Lane
Discussion: https://postgr.es/m/20180201013349.937dfc5f.nagata@sraoss.co.jp
In a top-level CALL, the values of INOUT arguments will be returned as a
result row. In PL/pgSQL, the values are assigned back to the input
arguments. In other languages, the same convention as for return a
record from a function is used. That does not require any code changes
in the PL implementations.
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
It's not necessary to fully initialize the executor data structures
for partitions to which no tuples are ever routed. Consider, for
example, an INSERT statement that inserts only one row: it only cares
about the partition to which that one row is routed. The new function
ExecInitPartitionInfo performs the initialization in question only
when a particular partition is about to receive a tuple. This includes
creating, validating, and saving a pointer to the ResultRelInfo,
setting up for speculative insertions, translating WCOs and
initializing the resulting expressions, translating returning lists
and building the appropriate projection information, and setting up a
tuple conversion map.
One thing that's not deferred is locking the child partitions; that
seems desirable but would need more thought. Still, testing shows
that this makes single-row inserts significantly faster on a table
with many partitions without harming the bulk-insert case.
Amit Langote, reviewed by Etsuro Fujita, with a few changes by me
Discussion: http://postgr.es/m/8975331d-d961-cbdd-f862-fdd3d97dc2d0@lab.ntt.co.jp
Previously tts_off was, for unknown reasons, of type long. For one
that's unnecessary as tuples are restricted in length, for another
long would be a bad choice of type even if that weren't the case, as
it's not reliably wider than an int. Also HeapTupleHeader->t_len is a
uint32.
This is split off from a larger patch implementing JITed tuple
deforming. Seems like an independent improvement, as tiny as it is.
Author: Andres Freund
The reason for doing so is that it will allow expression evaluation to
optimize based on the underlying tupledesc. In particular it will
allow to JIT tuple deforming together with the expression itself.
For that expression initialization needs to be moved after the
relevant slots are initialized - mostly unproblematic, except in the
case of nodeWorktablescan.c.
After doing so there's no need for ExecAssignResultType() and
ExecAssignResultTypeFromTL() anymore, as all former callers have been
converted to create a slot with a fixed descriptor.
When creating a slot with a fixed descriptor, tts_values/isnull can be
allocated together with the main slot, reducing allocation overhead
and increasing cache density a bit.
Author: Andres Freund
Discussion: https://postgr.es/m/20171206093717.vqdxe5icqttpxs3p@alap3.anarazel.de
This has a performance benefit on own, although not hugely so. The
primary benefit is that it will allow for to JIT tuple deforming and
comparator invocations.
Large parts of this were previously committed (773aec7aa), but the
commit contained an omission around cross-type comparisons and was
thus reverted.
Author: Andres Freund
Discussion: https://postgr.es/m/20171129080934.amqqkke2zjtekd4t@alap3.anarazel.de
This reverts commit 773aec7aa9.
There's an unresolved issue in the reverted commit: It only creates
one comparator function, but in for the nodeSubplan.c case we need
more (c.f. FindTupleHashEntry vs LookupTupleHashEntry calls in
nodeSubplan.c).
This isn't too difficult to fix, but it's not entirely trivial
either. The fact that the issue only causes breakage on 32bit systems
shows that the current test coverage isn't that great. To avoid
turning half the buildfarm red till those two issues are addressed,
revert.
It's a common task to evaluate a qual and reset the corresponding
expression context. Currently that requires storing the result of the
qual eval, resetting the context, and then reacting on the result. As
that's awkward several places only reset the context next time through
a node. That's not great, so introduce a helper that evaluates and
resets.
It's a bit ugly that it currently uses MemoryContextReset() instead of
ResetExprContext(), but that seems easier than reordering all of
executor.h.
Author: Andres Freund
Discussion: https://postgr.es/m/20180109222544.f7loxrunqh3xjl5f@alap3.anarazel.de
In each of the supplied procedural languages (PL/pgSQL, PL/Perl,
PL/Python, PL/Tcl), add language-specific commit and rollback
functions/commands to control transactions in procedures in that
language. Add similar underlying functions to SPI. Some additional
cleanup so that transaction commit or abort doesn't blow away data
structures still used by the procedure call. Add execution context
tracking to CALL and DO statements so that transaction control commands
can only be issued in top-level procedure and block calls, not function
calls or other procedure or block calls.
- SPI
Add a new function SPI_connect_ext() that is like SPI_connect() but
allows passing option flags. The only option flag right now is
SPI_OPT_NONATOMIC. A nonatomic SPI connection can execute transaction
control commands, otherwise it's not allowed. This is meant to be
passed down from CALL and DO statements which themselves know in which
context they are called. A nonatomic SPI connection uses different
memory management. A normal SPI connection allocates its memory in
TopTransactionContext. For nonatomic connections we use PortalContext
instead. As the comment in SPI_connect_ext() (previously SPI_connect())
indicates, one could potentially use PortalContext in all cases, but it
seems safest to leave the existing uses alone, because this stuff is
complicated enough already.
SPI also gets new functions SPI_start_transaction(), SPI_commit(), and
SPI_rollback(), which can be used by PLs to implement their transaction
control logic.
- portalmem.c
Some adjustments were made in the code that cleans up portals at
transaction abort. The portal code could already handle a command
*committing* a transaction and continuing (e.g., VACUUM), but it was not
quite prepared for a command *aborting* a transaction and continuing.
In AtAbort_Portals(), remove the code that marks an active portal as
failed. As the comment there already predicted, this doesn't work if
the running command wants to keep running after transaction abort. And
it's actually not necessary, because pquery.c is careful to run all
portal code in a PG_TRY block and explicitly runs MarkPortalFailed() if
there is an exception. So the code in AtAbort_Portals() is never used
anyway.
In AtAbort_Portals() and AtCleanup_Portals(), we need to be careful not
to clean up active portals too much. This mirrors similar code in
PreCommit_Portals().
- PL/Perl
Gets new functions spi_commit() and spi_rollback()
- PL/pgSQL
Gets new commands COMMIT and ROLLBACK.
Update the PL/SQL porting example in the documentation to reflect that
transactions are now possible in procedures.
- PL/Python
Gets new functions plpy.commit and plpy.rollback.
- PL/Tcl
Gets new commands commit and rollback.
Reviewed-by: Andrew Dunstan <andrew.dunstan@2ndquadrant.com>
When an UPDATE causes a row to no longer match the partition
constraint, try to move it to a different partition where it does
match the partition constraint. In essence, the UPDATE is split into
a DELETE from the old partition and an INSERT into the new one. This
can lead to surprising behavior in concurrency scenarios because
EvalPlanQual rechecks won't work as they normally did; the known
problems are documented. (There is a pending patch to improve the
situation further, but it needs more review.)
Amit Khandekar, reviewed and tested by Amit Langote, David Rowley,
Rajkumar Raghuwanshi, Dilip Kumar, Amul Sul, Thomas Munro, Álvaro
Herrera, Amit Kapila, and me. A few final revisions by me.
Discussion: http://postgr.es/m/CAJ3gD9do9o2ccQ7j7+tSgiE1REY65XRiMb=yJO3u3QhyP8EEPQ@mail.gmail.com
Previously aggregate transition and combination functions were invoked
by special case code in nodeAgg.c, evaluating input and filters
separately using the expression evaluation machinery. That turns out
to not be great for performance for several reasons:
- repeated expression evaluations have some cost
- the transition functions invocations are poorly predicted, as
commonly there are multiple aggregates in a query, resulting in the
same call-stack invoking different functions.
- filter and input computation had to be done separately
- the special case code made it hard to implement JITing of the whole
transition function invocation
Address this by building one large expression that computes input,
evaluates filters, and invokes transition functions.
This leads to moderate speedups in queries bottlenecked by aggregate
computations, and enables large speedups for similar cases once JITing
is done.
There's potential for further improvement:
- It'd be nice if we could simplify the somewhat expensive
aggstate->all_pergroups lookups.
- right now there's still an advance_transition_function invocation in
nodeAgg.c, leading to some code duplication.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
At present, we always raise an ERROR if the partition constraint
is violated, but a pending patch for UPDATE tuple routing will
consider instead moving the tuple to the correct partition.
Refactor to make that simpler.
Amit Khandekar, reviewed by Amit Langote, David Rowley, and me.
Discussion: http://postgr.es/m/CAJ3gD9cue54GbEzfV-61nyGpijvjZgCcghvLsB0_nL8Nm8HzCA@mail.gmail.com
Instead of having ExecSetupPartitionTupleRouting return multiple out
parameters, have it return a pointer to a structure containing all of
those different things. Also, provide and use a cleanup function,
ExecCleanupTupleRouting, instead of cleaning up all of the resources
allocated by ExecSetupPartitionTupleRouting individually.
Amit Khandekar, reviewed by Amit Langote, David Rowley, and me
Discussion: http://postgr.es/m/CAJ3gD9fWfxgKC+PfJZF3hkgAcNOy-LpfPxVYitDEXKHjeieWQQ@mail.gmail.com
The previous coding relied (without any documentation) on the data[]
member of HashMemoryChunkData being at a MAXALIGN'ed offset. If it
was not, the tuples would not be maxaligned either, leading to failures
on alignment-picky machines. While there seems to be no live bug on any
platform we support, this is clearly pretty fragile: any addition to or
rearrangement of the fields in HashMemoryChunkData could break it.
Let's remove the hazard by getting rid of the data[] member and instead
using pointer arithmetic with an explicitly maxalign'ed offset.
Discussion: https://postgr.es/m/14483.1514938129@sss.pgh.pa.us
In a race case, EXPLAIN ANALYZE could fail to display correct nbatch
and size information. Refactor so that participants report only on
batches they worked on rather than trying to report on all of them,
and teach explain.c to consider the HashInstrumentation object from
all participants instead of picking the first one it can find. This
should fix an occasional build farm failure in the "join" regression
test.
Author: Thomas Munro
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/30219.1514428346%40sss.pgh.pa.us
This reduces code duplication a bit, but the primary benefit that it
makes JITing expression evaluation easier. When doing so we can't, as
previously done in the interpreted case, really change opcode without
recompiling. Nor dow we just carry around unnecessary branches to
avoid re-checking over and over.
As a minor side-effect this makes ExecEvalStepOp() O(log(N)) rather
than O(N).
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
This patch does three interrelated things:
* Create a new expression execution step type EEOP_PARAM_CALLBACK
and add the infrastructure needed for add-on modules to generate that.
As discussed, the best control mechanism for that seems to be to add
another hook function to ParamListInfo, which will be called by
ExecInitExpr if it's supplied and a PARAM_EXTERN Param is found.
For stand-alone expressions, we add a new entry point to allow the
ParamListInfo to be specified directly, since it can't be retrieved
from the parent plan node's EState.
* Redesign the API for the ParamListInfo paramFetch hook so that the
ParamExternData array can be entirely virtual. This also lets us get rid
of ParamListInfo.paramMask, instead leaving it to the paramFetch hook to
decide which param IDs should be accessible or not. plpgsql_param_fetch
was already doing the identical masking check, so having callers do it too
seemed redundant. While I was at it, I added a "speculative" flag to
paramFetch that the planner can specify as TRUE to avoid unwanted failures.
This solves an ancient problem for plpgsql that it couldn't provide values
of non-DTYPE_VAR variables to the planner for fear of triggering premature
"record not assigned yet" or "field not found" errors during planning.
* Rework plpgsql to get rid of the need for "unshared" parameter lists,
by dint of turning the single ParamListInfo per estate into a nearly
read-only data structure that doesn't instantiate any per-variable data.
Instead, the paramFetch hook controls access to per-variable data and can
make the right decisions on the fly, replacing the cases that we used to
need multiple ParamListInfos for. This might perhaps have been a
performance loss on its own, but by using a paramCompile hook we can
bypass plpgsql_param_fetch entirely during normal query execution.
(It's now only called when, eg, we copy the ParamListInfo into a cursor
portal. copyParamList() or SerializeParamList() effectively instantiate
the virtual parameter array as a simple physical array without a
paramFetch hook, which is what we want in those cases.) This allows
reverting most of commit 6c82d8d1f, though I kept the cosmetic
code-consolidation aspects of that (eg the assign_simple_var function).
Performance testing shows this to be at worst a break-even change,
and it can provide wins ranging up to 20% in test cases involving
accesses to fields of "record" variables. The fact that values of
such variables can now be exposed to the planner might produce wins
in some situations, too, but I've not pursued that angle.
In passing, remove the "parent" pointer from the arguments to
ExecInitExprRec and related functions, instead storing that pointer in a
transient field in ExprState. The ParamListInfo pointer for a stand-alone
expression is handled the same way; we'd otherwise have had to add
yet another recursively-passed-down argument in expression compilation.
Discussion: https://postgr.es/m/32589.1513706441@sss.pgh.pa.us
Introduce parallel-aware hash joins that appear in EXPLAIN plans as Parallel
Hash Join with Parallel Hash. While hash joins could already appear in
parallel queries, they were previously always parallel-oblivious and had a
partial subplan only on the outer side, meaning that the work of the inner
subplan was duplicated in every worker.
After this commit, the planner will consider using a partial subplan on the
inner side too, using the Parallel Hash node to divide the work over the
available CPU cores and combine its results in shared memory. If the join
needs to be split into multiple batches in order to respect work_mem, then
workers process different batches as much as possible and then work together
on the remaining batches.
The advantages of a parallel-aware hash join over a parallel-oblivious hash
join used in a parallel query are that it:
* avoids wasting memory on duplicated hash tables
* avoids wasting disk space on duplicated batch files
* divides the work of building the hash table over the CPUs
One disadvantage is that there is some communication between the participating
CPUs which might outweigh the benefits of parallelism in the case of small
hash tables. This is avoided by the planner's existing reluctance to supply
partial plans for small scans, but it may be necessary to estimate
synchronization costs in future if that situation changes. Another is that
outer batch 0 must be written to disk if multiple batches are required.
A potential future advantage of parallel-aware hash joins is that right and
full outer joins could be supported, since there is a single set of matched
bits for each hashtable, but that is not yet implemented.
A new GUC enable_parallel_hash is defined to control the feature, defaulting
to on.
Author: Thomas Munro
Reviewed-By: Andres Freund, Robert Haas
Tested-By: Rafia Sabih, Prabhat Sahu
Discussion:
https://postgr.es/m/CAEepm=2W=cOkiZxcg6qiFQP-dHUe09aqTrEMM7yJDrHMhDv_RA@mail.gmail.comhttps://postgr.es/m/CAEepm=37HKyJ4U6XOLi=JgfSHM3o6B-GaeO-6hkOmneTDkH+Uw@mail.gmail.com
When a Gather or Gather Merge node is started and stopped multiple
times, accumulate instrumentation data only once, at the end, instead
of after each execution, to avoid recording inflated totals.
Commit 778e78ae9f, the previous attempt
at a fix, instead reset the state after every execution, which worked
for the general instrumentation data but had problems for the additional
instrumentation specific to Sort and Hash nodes.
Report by hubert depesz lubaczewski. Analysis and fix by Amit Kapila,
following a design proposal from Thomas Munro, with a comment tweak
by me.
Discussion: http://postgr.es/m/20171127175631.GA405@depesz.com
In order for executor nodes to be able to change their ExecProcNode function
after ExecInitNode() has finished, provide ExecSetExecProcNode(). This allows
any wrappers functions that only execProcnode.c knows about to be reinstalled.
The motivation for wanting to change ExecProcNode after ExecInitNode() has
finished is that it is not known until later whether parallel query is
available, so if a parallel variant is to be installed then ExecInitNode()
is too soon to decide.
Author: Thomas Munro
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/CAEepm=09rr65VN+cAV5FgyM_z=D77Xy8Fuc9CDDDYbq3pQUezg@mail.gmail.com
When we create an Append node, we can spread out the workers over the
subplans instead of piling on to each subplan one at a time, which
should typically be a bit more efficient, both because the startup
cost of any plan executed entirely by one worker is paid only once and
also because of reduced contention. We can also construct Append
plans using a mix of partial and non-partial subplans, which may allow
for parallelism in places that otherwise couldn't support it.
Unfortunately, this patch doesn't handle the important case of
parallelizing UNION ALL by running each branch in a separate worker;
the executor infrastructure is added here, but more planner work is
needed.
Amit Khandekar, Robert Haas, Amul Sul, reviewed and tested by
Ashutosh Bapat, Amit Langote, Rafia Sabih, Amit Kapila, and
Rajkumar Raghuwanshi.
Discussion: http://postgr.es/m/CAJ3gD9dy0K_E8r727heqXoBmWZ83HwLFwdcaSSmBQ1+S+vRuUQ@mail.gmail.com
If a hash join appears in a parallel query, there may be no hash table
available for explain.c to inspect even though a hash table may have
been built in other processes. This could happen either because
parallel_leader_participation was set to off or because the leader
happened to hit the end of the outer relation immediately (even though
the complete relation is not empty) and decided not to build the hash
table.
Commit bf11e7ee introduced a way for workers to exchange
instrumentation via the DSM segment for Sort nodes even though they
are not parallel-aware. This commit does the same for Hash nodes, so
that explain.c has a way to find instrumentation data from an
arbitrary participant that actually built the hash table.
Author: Thomas Munro
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/CAEepm%3D3DUQC2-z252N55eOcZBer6DPdM%3DFzrxH9dZc5vYLsjaA%40mail.gmail.com
It's most often the case that the target list for the Gather (Merge)
node matches the target list supplied by the underlying plan node;
when this is so, we can avoid the overhead of projecting.
This depends on commit f455e1125e for
proper functioning.
Idea by Andres Freund. Patch by me. Review by Amit Kapila.
Discussion: http://postgr.es/m/CA+TgmoZ0ZL=cesZFq8c9NnfK6bqy-wwUd3_74iYGodYrSoQ7Fw@mail.gmail.com
Previously, executor nodes running in parallel worker processes didn't
have access to the dsm_segment object used for parallel execution. In
order to support resource management based on DSM segment lifetime,
they need that. So create a ParallelWorkerContext object to hold it
and pass it to all InitializeWorker functions.
Author: Thomas Munro
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/CAEepm=2W=cOkiZxcg6qiFQP-dHUe09aqTrEMM7yJDrHMhDv_RA@mail.gmail.com
If a PARAM_EXEC parameter is used below a Gather (Merge) but the InitPlan
that computes it is attached to or above the Gather (Merge), force the
value to be computed before starting parallelism and pass it down to all
workers. This allows us to use parallelism in cases where it previously
would have had to be rejected as unsafe. We do - in this case - lose the
optimization that the value is only computed if it's actually used. An
alternative strategy would be to have the first worker that needs the value
compute it, but one downside of that approach is that we'd then need to
select a parallel-safe path to compute the parameter value; it couldn't for
example contain a Gather (Merge) node. At some point in the future, we
might want to consider both approaches.
Independent of that consideration, there is a great deal more work that
could be done to make more kinds of PARAM_EXEC parameters parallel-safe.
This infrastructure could be used to allow a Gather (Merge) on the inner
side of a nested loop (although that's not a very appealing plan) and
cases where the InitPlan is attached below the Gather (Merge) could be
addressed as well using various techniques. But this is a good start.
Amit Kapila, reviewed and revised by me. Reviewing and testing from
Kuntal Ghosh, Haribabu Kommi, and Tushar Ahuja.
Discussion: http://postgr.es/m/CAA4eK1LV0Y1AUV4cUCdC+sYOx0Z0-8NAJ2Pd9=UKsbQ5Sr7+JQ@mail.gmail.com
Some code is moved from partition.c, which has grown very quickly lately;
splitting the executor parts out might help to keep it from getting
totally out of control. Other code is moved from execMain.c. All is
moved to a new file execPartition.c. get_partition_for_tuple now has
a new interface that more clearly separates executor concerns from
generic concerns.
Amit Langote. A slight comment tweak by me.
Discussion: http://postgr.es/m/1f0985f8-3b61-8bc4-4350-baa6d804cb6d@lab.ntt.co.jp
The lower case spellings are C and C++ standard and are used in most
parts of the PostgreSQL sources. The upper case spellings are only used
in some files/modules. So standardize on the standard spellings.
The APIs for ICU, Perl, and Windows define their own TRUE and FALSE, so
those are left as is when using those APIs.
In code comments, we use the lower-case spelling for the C concepts and
keep the upper-case spelling for the SQL concepts.
Reviewed-by: Michael Paquier <michael.paquier@gmail.com>
The previous convention doesn't lend itself to creating ResultRelInfos
lazily, as we already do in ExecGetTriggerResultRel. This patch
doesn't make anything lazier than before, but the pending patch for
UPDATE tuple routing proposes to do so (and there might be other
opportunities as well).
Amit Khandekar with some adjustments by me.
Discussion: http://postgr.es/m/CA+TgmoYPVP9Lyf6vUFA5DwxS4c--x6LOj2y36BsJaYtp62eXPQ@mail.gmail.com
Previously nodeProjectSet only released memory once per input tuple,
rather than once per returned tuple. If the computation of an
individual returned tuple requires a lot of memory, that can lead to
problems.
Instead change things so that the expression context can be reset once
per output tuple, which requires a new memory context to store SRF
arguments in.
This is a longstanding issue, but was hard to fix before 9.6, due to
the way tSRFs where evaluated. But it's fairly easy to fix now. We
could backpatch this into 10, but given there've been fewc omplaints
that doesn't seem worth the risk so far.
Reported-By: Lucas Fairchild
Author: Andres Freund, per discussion with Tom Lane
Discussion: https://postgr.es/m/4514.1507318623@sss.pgh.pa.us
The logical decoding functions do BeginInternalSubTransaction and
RollbackAndReleaseCurrentSubTransaction to clean up after themselves.
It turns out that AtEOSubXact_SPI has an unrecognized assumption that
we always need to cancel the active SPI operation in the SPI context
that surrounds the subtransaction (if there is one). That's true
when the RollbackAndReleaseCurrentSubTransaction call is coming from
the SPI-using function itself, but not when it's happening inside
some unrelated function invoked by a SPI query. In practice the
affected callers are the various PLs.
To fix, record the current subtransaction ID when we begin a SPI
operation, and clean up only if that ID is the subtransaction being
canceled.
Also, remove AtEOSubXact_SPI's assertion that it must have cleaned
up the surrounding SPI context's active tuptable. That's proven
wrong by the same test case.
Also clarify (or, if you prefer, reinterpret) the calling conventions
for _SPI_begin_call and _SPI_end_call. The memory context cleanup
in the latter means that these have always had the flavor of a matched
resource-management pair, but they weren't documented that way before.
Per report from Ben Chobot.
Back-patch to 9.4 where logical decoding came in. In principle,
the SPI changes should go all the way back, since the problem dates
back to commit 7ec1c5a86. But given the lack of field complaints
it seems few people are using internal subtransactions in this way.
So I don't feel a need to take any risks in 9.2/9.3.
Discussion: https://postgr.es/m/73FBA179-C68C-4540-9473-71E865408B15@silentmedia.com
Allowing arrays with a domain type as their element type was left un-done
in the original domain patch, but not for any very good reason. This
omission leads to such surprising results as array_agg() not working on
a domain column, because the parser can't identify a suitable output type
for the polymorphic aggregate.
In order to fix this, first clean up the APIs of coerce_to_domain() and
some internal functions in parse_coerce.c so that we consistently pass
around a CoercionContext along with CoercionForm. Previously, we sometimes
passed an "isExplicit" boolean flag instead, which is strictly less
information; and coerce_to_domain() didn't even get that, but instead had
to reverse-engineer isExplicit from CoercionForm. That's contrary to the
documentation in primnodes.h that says that CoercionForm only affects
display and not semantics. I don't think this change fixes any live bugs,
but it makes things more consistent. The main reason for doing it though
is that now build_coercion_expression() receives ccontext, which it needs
in order to be able to recursively invoke coerce_to_target_type().
Next, reimplement ArrayCoerceExpr so that the node does not directly know
any details of what has to be done to the individual array elements while
performing the array coercion. Instead, the per-element processing is
represented by a sub-expression whose input is a source array element and
whose output is a target array element. This simplifies life in
parse_coerce.c, because it can build that sub-expression by a recursive
invocation of coerce_to_target_type(). The executor now handles the
per-element processing as a compiled expression instead of hard-wired code.
The main advantage of this is that we can use a single ArrayCoerceExpr to
handle as many as three successive steps per element: base type conversion,
typmod coercion, and domain constraint checking. The old code used two
stacked ArrayCoerceExprs to handle type + typmod coercion, which was pretty
inefficient, and adding yet another array deconstruction to do domain
constraint checking seemed very unappetizing.
In the case where we just need a single, very simple coercion function,
doing this straightforwardly leads to a noticeable increase in the
per-array-element runtime cost. Hence, add an additional shortcut evalfunc
in execExprInterp.c that skips unnecessary overhead for that specific form
of expression. The runtime speed of simple cases is within 1% or so of
where it was before, while cases that previously required two levels of
array processing are significantly faster.
Finally, create an implicit array type for every domain type, as we do for
base types, enums, etc. Everything except the array-coercion case seems
to just work without further effort.
Tom Lane, reviewed by Andrew Dunstan
Discussion: https://postgr.es/m/9852.1499791473@sss.pgh.pa.us
It is equivalent in ANSI C to write (*funcptr) () and funcptr(). These
two styles have been applied inconsistently. After discussion, we'll
use the more verbose style for plain function pointer variables, to make
it clear that it's a variable, and the shorter style when the function
pointer is in a struct (s.func() or s->func()), because then it's clear
that it's not a plain function name, and otherwise the excessive
punctuation makes some of those invocations hard to read.
Discussion: https://www.postgresql.org/message-id/f52c16db-14ed-757d-4b48-7ef360b1631d@2ndquadrant.com
This doesn't allow routing tuple to the foreign partitions themselves,
but it permits tuples to be routed to regular partitions despite the
presence of foreign partitions in the same inheritance hierarchy.
Etsuro Fujita, reviewed by Amit Langote and by me.
Discussion: http://postgr.es/m/bc3db4c1-1693-3b8a-559f-33ad2b50b7ad@lab.ntt.co.jp
Move the responsibility for creating/destroying TupleQueueReaders into
execParallel.c, to avoid duplicative coding in nodeGather.c and
nodeGatherMerge.c. Also, instead of having DestroyTupleQueueReader do
shm_mq_detach, do it in the caller (which is now only ExecParallelFinish).
This means execParallel.c does both the attaching and detaching of the
tuple-queue-reader shm_mqs, which seems less weird than the previous
arrangement.
These changes also eliminate a vestigial memory leak (of the pei->tqueue
array). It's now demonstrable that rescans of Gather or GatherMerge don't
leak memory.
Discussion: https://postgr.es/m/8670.1504192177@sss.pgh.pa.us
Previously, the parallel executor logic did reinitialization of shared
state within the ExecReScan code for parallel-aware scan nodes. This is
problematic, because it means that the ExecReScan call has to occur
synchronously (ie, during the parent Gather node's ReScan call). That is
swimming very much against the tide so far as the ExecReScan machinery is
concerned; the fact that it works at all today depends on a lot of fragile
assumptions, such as that no plan node between Gather and a parallel-aware
scan node is parameterized. Another objection is that because ExecReScan
might be called in workers as well as the leader, hacky extra tests are
needed in some places to prevent unwanted shared-state resets.
Hence, let's separate this code into two functions, a ReInitializeDSM
call and the ReScan call proper. ReInitializeDSM is called only in
the leader and is guaranteed to run before we start new workers.
ReScan is returned to its traditional function of resetting only local
state, which means that ExecReScan's usual habits of delaying or
eliminating child rescan calls are safe again.
As with the preceding commit 7df2c1f8d, it doesn't seem to be necessary
to make these changes in 9.6, which is a good thing because the FDW and
CustomScan APIs are impacted.
Discussion: https://postgr.es/m/CAA4eK1JkByysFJNh9M349u_nNjqETuEnY_y1VUc_kJiU0bxtaQ@mail.gmail.com
Up until now, when parallel query was used, no details about the
sort method or space used by the workers were available; details
were shown only for any sorting done by the leader. Fix that.
Commit 1177ab1dab forced the test case
added by commit 1f6d515a67 to run
without parallelism; now that we have this infrastructure, allow
that again, with a little tweaking to make it pass with and without
force_parallel_mode.
Robert Haas and Tom Lane
Discussion: http://postgr.es/m/CA+Tgmoa2VBZW6S8AAXfhpHczb=Rf6RqQ2br+zJvEgwJ0uoD_tQ@mail.gmail.com
