Previously, it was pg_stat_activity.queryid to match the
pg_stat_statements queryid column. This is an adjustment to patch
4f0b0966c8. This also adjusts some of the internal function calls to
match. Catversion bumped.
Reported-by: Álvaro Herrera, Julien Rouhaud
Discussion: https://postgr.es/m/20210408032704.GA7498@alvherre.pgsql
This reverts commit b3ee4c503872f3d0a5d6a7cbde48815f555af15b.
We don't need it in the wake of the preceding commit, which
added an upstream check that the querystring isn't null.
Discussion: https://postgr.es/m/2197698.1617984583@sss.pgh.pa.us
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
Ignore parallel workers in pg_stat_statements
Oversight in 4f0b0966c8 which exposed queryid in parallel workers.
Counters are aggregated by the main backend process so parallel workers
would report duplicated activity, and could also report activity for the
wrong entry as they are only aware of the top level queryid.
Fix thinko in pg_stat_get_activity when retrieving the queryid.
Remove unnecessary call to pgstat_report_queryid().
Reported-by: Amit Kapila, Andres Freund, Thomas Munro
Discussion: https://postgr.es/m/20210408051735.lfbdzun5zdlax5gd@alap3.anarazel.dep634GTSOqnDW86Owrn6qDAVosC5dJjXjp7BMfc5Gz1Q@mail.gmail.com
Author: Julien Rouhaud
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
It's far from clear that this is the right approach - but a good
portion of the buildfarm has been red for a few hours, on the last day
of the CF. And this fixes at least the obvious crash. So let's go with
that for now.
Discussion: https://postgr.es/m/20210407225806.majgznh4lk34hjvu%40alap3.anarazel.de
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
Use the in-core query id computation for pg_stat_activity,
log_line_prefix, and EXPLAIN VERBOSE.
Similar to other fields in pg_stat_activity, only the queryid from the
top level statements are exposed, and if the backends status isn't
active then the queryid from the last executed statements is displayed.
Add a %Q placeholder to include the queryid in log_line_prefix, which
will also only expose top level statements.
For EXPLAIN VERBOSE, if a query identifier has been computed, either by
enabling compute_query_id or using a third-party module, display it.
Bump catalog version.
Discussion: https://postgr.es/m/20210407125726.tkvjdbw76hxnpwfi@nol
Author: Julien Rouhaud
Reviewed-by: Alvaro Herrera, Nitin Jadhav, Zhihong Yu
Delay creation of the projections for INSERT and UPDATE tuples
until they're needed. This saves a pretty fair amount of work
when only some of the partitions are actually touched.
The logic associated with identifying junk columns in UPDATE/DELETE
is moved to another loop, allowing removal of one loop over the
target relations; but it didn't actually change at all.
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
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
Andrew Gierth reported that it's possible to crash the backend if no
pg_attrdef record is found to match an attribute that has atthasdef set.
AttrDefaultFetch warns about this situation, but then leaves behind
a relation tupdesc that has null "adbin" pointer(s), which most places
don't guard against.
We considered promoting the warning to an error, but throwing errors
during relcache load is pretty drastic: it effectively locks one out
of using the relation at all. What seems better is to leave the
load-time behavior as a warning, but then throw an error in any code
path that wants to use a default and can't find it. This confines
the error to a subset of INSERT/UPDATE operations on the table, and
in particular will at least allow a pg_dump to succeed.
Also, we should fix AttrDefaultFetch to not leave any null pointers
in the tupdesc, because that just creates an untested bug hazard.
While at it, apply the same philosophy of "warn at load, throw error
only upon use of the known-missing info" to CHECK constraints.
CheckConstraintFetch is very nearly the same logic as AttrDefaultFetch,
but for reasons lost in the mists of time, it was throwing ERROR for
the same cases that AttrDefaultFetch treats as WARNING. Make the two
functions more nearly alike.
In passing, get rid of potentially-O(N^2) loops in equalTupleDesc
by making AttrDefaultFetch sort the entries after fetching them,
so that equalTupleDesc can assume that entries in two equal tupdescs
must be in matching order. (CheckConstraintFetch already was sorting
CHECK constraints, but equalTupleDesc hadn't been told about it.)
There's some argument for back-patching this, but with such a small
number of field reports, I'm content to fix it in HEAD.
Discussion: https://postgr.es/m/87pmzaq4gx.fsf@news-spur.riddles.org.uk
Adjust the number of events given to WaitEventSetWait() so that it
doesn't exceed the maximum number of events in the WaitEventSet given
to that function (set->nevents_space) in hopes of making the buildfarm
green.
Per valgrind failure report from Tom Lane and the buildfarm.
Author: Etsuro Fujita
Discussion: https://postgr.es/m/3411577.1617289776%40sss.pgh.pa.us
Testing if an unsigned variable is >= 0 is pretty pointless.
There's likely enough code in remove_cache_entry() to verify the cache
memory accounting is correct in assert enabled builds. These Asserts
were not adding much extra cover, even if they had been checking >= 0 on a
signed variable.
Reported-by: Andres Freund
Discussion: https://postgr.es/m/20210402204734.6mo3nfacnljlicgn@alap3.anarazel.de
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
Allow a partition be detached from its partitioned table without
blocking concurrent queries, by running in two transactions and only
requiring ShareUpdateExclusive in the partitioned table.
Because it runs in two transactions, it cannot be used in a transaction
block. This is the main reason to use dedicated syntax: so that users
can choose to use the original mode if they need it. But also, it
doesn't work when a default partition exists (because an exclusive lock
would still need to be obtained on it, in order to change its partition
constraint.)
In case the second transaction is cancelled or a crash occurs, there's
ALTER TABLE .. DETACH PARTITION .. FINALIZE, which executes the final
steps.
The main trick to make this work is the addition of column
pg_inherits.inhdetachpending, initially false; can only be set true in
the first part of this command. Once that is committed, concurrent
transactions that use a PartitionDirectory will include or ignore
partitions so marked: in optimizer they are ignored if the row is marked
committed for the snapshot; in executor they are always included. As a
result, and because of the way PartitionDirectory caches partition
descriptors, queries that were planned before the detach will see the
rows in the detached partition and queries that are planned after the
detach, won't.
A CHECK constraint is created that duplicates the partition constraint.
This is probably not strictly necessary, and some users will prefer to
remove it afterwards, but if the partition is re-attached to a
partitioned table, the constraint needn't be rechecked.
Author: Álvaro Herrera <alvherre@alvh.no-ip.org>
Reviewed-by: Amit Langote <amitlangote09@gmail.com>
Reviewed-by: Justin Pryzby <pryzby@telsasoft.com>
Discussion: https://postgr.es/m/20200803234854.GA24158@alvherre.pgsql
To allow inserts in parallel-mode this feature has to ensure that all the
constraints, triggers, etc. are parallel-safe for the partition hierarchy
which is costly and we need to find a better way to do that. Additionally,
we could have used existing cached information in some cases like indexes,
domains, etc. to determine the parallel-safety.
List of commits reverted, in reverse chronological order:
ed62d3737c Doc: Update description for parallel insert reloption.
c8f78b6161 Add a new GUC and a reloption to enable inserts in parallel-mode.
c5be48f092 Improve FK trigger parallel-safety check added by 05c8482f7f.
e2cda3c20a Fix use of relcache TriggerDesc field introduced by commit 05c8482f7f.
e4e87a32cc Fix valgrind issue in commit 05c8482f7f.
05c8482f7f Enable parallel SELECT for "INSERT INTO ... SELECT ...".
Discussion: https://postgr.es/m/E1lMiB9-0001c3-SY@gemulon.postgresql.org
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
Parallel SELECT can't be utilized for INSERT in the following cases:
- INSERT statement uses the ON CONFLICT DO UPDATE clause
- Target table has a parallel-unsafe: trigger, index expression or
predicate, column default expression or check constraint
- Target table has a parallel-unsafe domain constraint on any column
- Target table is a partitioned table with a parallel-unsafe partition key
expression or support function
The planner is updated to perform additional parallel-safety checks for
the cases listed above, for determining whether it is safe to run INSERT
in parallel-mode with an underlying parallel SELECT. The planner will
consider using parallel SELECT for "INSERT INTO ... SELECT ...", provided
nothing unsafe is found from the additional parallel-safety checks, or
from the existing parallel-safety checks for SELECT.
While checking parallel-safety, we need to check it for all the partitions
on the table which can be costly especially when we decide not to use a
parallel plan. So, in a separate patch, we will introduce a GUC and or a
reloption to enable/disable parallelism for Insert statements.
Prior to entering parallel-mode for the execution of INSERT with parallel
SELECT, a TransactionId is acquired and assigned to the current
transaction state. This is necessary to prevent the INSERT from attempting
to assign the TransactionId whilst in parallel-mode, which is not allowed.
This approach has a disadvantage in that if the underlying SELECT does not
return any rows, then the TransactionId is not used, however that
shouldn't happen in practice in many cases.
Author: Greg Nancarrow, Amit Langote, Amit Kapila
Reviewed-by: Amit Langote, Hou Zhijie, Takayuki Tsunakawa, Antonin Houska, Bharath Rupireddy, Dilip Kumar, Vignesh C, Zhihong Yu, Amit Kapila
Tested-by: Tang, Haiying
Discussion: https://postgr.es/m/CAJcOf-cXnB5cnMKqWEp2E2z7Mvcd04iLVmV=qpFJrR3AcrTS3g@mail.gmail.com
Discussion: https://postgr.es/m/CAJcOf-fAdj=nDKMsRhQzndm-O13NY4dL6xGcEvdX5Xvbbi0V7g@mail.gmail.com
Throw a "function protocol violation" error if a function in FROM
tries to return a set though it wasn't marked proretset. Although
such cases work at the moment, it doesn't seem like something we
want to guarantee will keep working. Besides, there are other
negative consequences of not setting the proretset flag, such as
potentially bad plans.
No back-patch, since if there is any third-party code violating
this expectation, people wouldn't appreciate us breaking it in
a minor release.
Discussion: https://postgr.es/m/1636062.1615141782@sss.pgh.pa.us
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
A cross-partition update on a partitioned table is implemented as a
delete followed by an insert. With foreign partitions, this was however
causing issues, because the FDW and core may disagree on when to enable
batching. postgres_fdw was only allowing batching for plain inserts
(CMD_INSERT) while core was trying to batch the insert component of the
cross-partition update. Fix by restricting core to apply batching only
to plain CMD_INSERT queries.
It's possible to allow batching for cross-partition updates, but that
will require more extensive changes, so better to leave that for a
separate patch.
Author: Amit Langote
Reviewed-by: Tomas Vondra, Takayuki Tsunakawa
Discussion: https://postgr.es/m/20200628151002.7x5laxwpgvkyiu3q@development
The inner loop in switchToPresortedPrefixMode() can be implemented
as a conventional integer-counter for() loop, removing a couple of
redundant boolean state variables. The old logic here was a remnant
of earlier development, but as things now stand there's no reason
for extra complexity.
Also, annotate the test case added by 82e0e2930 to explain why it
manages to hit the corner case fixed in that commit, and add an
EXPLAIN to verify that it's creating an incremental-sort plan.
Back-patch to v13, like the previous patch.
James Coleman and Tom Lane
Discussion: https://postgr.es/m/16846-ae49f51ac379a4cb@postgresql.org
If ExecGetInsertedCols(), ExecGetUpdatedCols() or ExecGetExtraUpdatedCols()
were called with a ResultRelInfo that's not in the range table and isn't a
partition routing target, the functions would dereference a NULL pointer,
relinfo->ri_RootResultRelInfo. Such ResultRelInfos are created when firing
RI triggers in tables that are not modified directly. None of the current
callers of these functions pass such relations, so this isn't a live bug,
but let's make them more robust.
Also update comment in ResultRelInfo; after commit 6214e2b228,
ri_RangeTableIndex is zero for ResultRelInfos created for partition tuple
routing.
Noted by Coverity. Backpatch down to v11, like commit 6214e2b228.
Reviewed-by: Tom Lane, Amit Langote
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
Commit 230230223 taught nodeAgg.c that, when spilling tuples from
memory in an oversized hash aggregation, it only needed to spill
input columns referenced in the node's tlist and quals. Unfortunately,
that's wrong: we also have to save the grouping columns. The error
is masked in common cases because the grouping columns also appear
in the tlist, but that's not necessarily true. The main category
of plans where it's not true seem to come from semijoins ("WHERE
outercol IN (SELECT innercol FROM innertable)") where the innercol
needs an implicit promotion to make it comparable to the outercol.
The grouping column will be "innercol::promotedtype", but that
expression appears nowhere in the Agg node's own tlist and quals;
only the bare "innercol" is found in the tlist.
I spent quite a bit of time looking for a suitable regression test
case for this, without much success. If the number of distinct
values of the innercol is large enough to make spilling happen,
the planner tends to prefer a non-HashAgg plan, at least for
problem sizes that are reasonable to use in the regression tests.
So, no new regression test. However, this patch does demonstrably
fix the originally-reported test case.
Per report from s.p.e (at) gmx-topmail.de. Backpatch to v13
where the troublesome code came in.
Discussion: https://postgr.es/m/trinity-1c565d44-159f-488b-a518-caf13883134f-1611835701633@3c-app-gmx-bap78
switchToPresortedPrefixMode() did the wrong thing if it detected
a batch boundary just at the last tuple of a fullsort group.
The initially-reported symptom was a "retrieved too many tuples in a
bounded sort" error, but the test case added here just silently gives
the wrong answer without this patch.
I (tgl) am not really happy about committing this patch without review
from the incremental-sort authors, but they seem AWOL and we are hard
against a release deadline. This does demonstrably make some cases
better, anyway.
Per bug #16846 from Yoran Heling. Back-patch to v13 where incremental
sort was introduced.
Neil Chen
Discussion: https://postgr.es/m/16846-ae49f51ac379a4cb@postgresql.org
perform_pruning_combine_step() was not taught about the number of
partition indexes used in hash partitioning; more embarrassingly,
get_matching_hash_bounds() also had it wrong. These errors are masked
in the common case where all the partitions have the same modulus
and no partition is missing. However, with missing or unequal-size
partitions, we could erroneously prune some partitions that need
to be scanned, leading to silently wrong query answers.
While a minimal-footprint fix for this could be to export
get_partition_bound_num_indexes and make the incorrect functions use it,
I'm of the opinion that that function should never have existed in the
first place. It's not reasonable data structure design that
PartitionBoundInfoData lacks any explicit record of the length of
its indexes[] array. Perhaps that was all right when it could always
be assumed equal to ndatums, but something should have been done about
it as soon as that stopped being true. Putting in an explicit
"nindexes" field makes both partition_bounds_equal() and
partition_bounds_copy() simpler, safer, and faster than before,
and removes explicit knowledge of the number-of-partition-indexes
rules from some other places too.
This change also makes get_hash_partition_greatest_modulus obsolete.
I left that in place in case any external code uses it, but no core
code does anymore.
Per bug #16840 from Michał Albrycht. Back-patch to v11 where the
hash partitioning code came in. (In the back branches, add the new
field at the end of PartitionBoundInfoData to minimize ABI risks.)
Discussion: https://postgr.es/m/16840-571a22976f829ad4@postgresql.org
When building aggregate expression steps, strict checks need a bailout
jump for when a null value is encountered, so there is a list of steps
that require later adjustment. Adding entries to that list for steps
that aren't actually strict would be harmless, except that there is an
Assert which catches them. This leads to spurious errors on asserts
builds, for data sets that trigger parallel aggregation of an
aggregate with a non-strict deserialization function (no such
aggregates exist in the core system).
Repair by not adding the adjustment entry when it's not needed.
Backpatch back to 11 where the code was introduced.
Per a report from Darafei (Komzpa) of the PostGIS project; analysis
and patch by me.
Discussion: https://postgr.es/m/87mty7peb3.fsf@news-spur.riddles.org.uk
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
ExecInitModifyTable has to initialize batching for all result relations,
not just the first one. Furthermore, when junk filters were necessary,
the pointer pointed past the mtstate->resultRelInfo array.
Per reports from multiple non-x86 animals (florican, locust, ...).
Discussion: https://postgr.es/m/20200628151002.7x5laxwpgvkyiu3q@development
Extends the FDW API to allow batching inserts into foreign tables. That
is usually much more efficient than inserting individual rows, due to
high latency for each round-trip to the foreign server.
It was possible to implement something similar in the regular FDW API,
but it was inconvenient and there were issues with reporting the number
of actually inserted rows etc. This extends the FDW API with two new
functions:
* GetForeignModifyBatchSize - allows the FDW picking optimal batch size
* ExecForeignBatchInsert - inserts a batch of rows at once
Currently, only INSERT queries support batching. Support for DELETE and
UPDATE may be added in the future.
This also implements batching for postgres_fdw. The batch size may be
specified using "batch_size" option both at the server and table level.
The initial patch version was written by me, but it was rewritten and
improved in many ways by Takayuki Tsunakawa.
Author: Takayuki Tsunakawa
Reviewed-by: Tomas Vondra, Amit Langote
Discussion: https://postgr.es/m/20200628151002.7x5laxwpgvkyiu3q@development
Somebody extended search_plan_tree() to treat MergeAppend exactly
like Append, which is 100% wrong, because unlike Append we can't
assume that only one input node is actively returning tuples.
Hence a cursor using a MergeAppend across a UNION ALL or inheritance
tree could falsely match a WHERE CURRENT OF query at a row that
isn't actually the cursor's current output row, but coincidentally
has the same TID (in a different table) as the current output row.
Delete the faulty code; this means that such a case will now return
an error like 'cursor "foo" is not a simply updatable scan of table
"bar"', instead of silently misbehaving. Users should not find that
surprising though, as the same cursor query could have failed that way
already depending on the chosen plan. (It would fail like that if the
sort were done with an explicit Sort node instead of MergeAppend.)
Expand the clearly-inadequate commentary to be more explicit about
what this code is doing, in hopes of forestalling future mistakes.
It's been like this for awhile, so back-patch to all supported
branches.
Discussion: https://postgr.es/m/482865.1611075182@sss.pgh.pa.us
execCurrent.c's search_plan_tree() assumed that ForeignScanStates
and CustomScanStates necessarily have a valid ss_currentRelation.
This is demonstrably untrue for postgres_fdw's remote join and
remote aggregation plans, and non-leaf custom scans might not have
an identifiable scan relation either. Avoid crashing by ignoring
such nodes when the field is null.
This solution will lead to errors like 'cursor "foo" is not a
simply updatable scan of table "bar"' in cases where maybe we
could have allowed WHERE CURRENT OF to work. That's not an issue
for postgres_fdw's usages, since joins or aggregations would render
WHERE CURRENT OF invalid anyway. But an otherwise-transparent
upper level custom scan node might find this annoying. When and if
someone cares to expend work on such a scenario, we could invent a
custom-scan-provider callback to determine what's safe.
Report and patch by David Geier, commentary by me. It's been like
this for awhile, so back-patch to all supported branches.
Discussion: https://postgr.es/m/0253344d-9bdd-11c4-7f0d-d88c02cd7991@swarm64.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
Invent new RawParseModes that allow the core grammar to handle
pl/pgsql expressions and assignments directly, and thereby get rid
of a lot of hackery in pl/pgsql's parser. This moves a good deal
of knowledge about pl/pgsql into the core code: notably, we have to
invent a CoercionContext that matches pl/pgsql's (rather dubious)
historical behavior for assignment coercions. That's getting away
from the original idea of pl/pgsql as an arm's-length extension of
the core, but really we crossed that bridge a long time ago.
The main advantage of doing this is that we can now use the core
parser to generate FieldStore and/or SubscriptingRef nodes to handle
assignments to pl/pgsql variables that are records or arrays. That
fixes a number of cases that had never been implemented in pl/pgsql
assignment, such as nested records and array slicing, and it allows
pl/pgsql assignment to support the datatype-specific subscripting
behaviors introduced in commit c7aba7c14.
There are cosmetic benefits too: when a syntax error occurs in a
pl/pgsql expression, the error report no longer includes the confusing
"SELECT" keyword that used to get prefixed to the expression text.
Also, there seem to be some small speed gains.
Discussion: https://postgr.es/m/4165684.1607707277@sss.pgh.pa.us
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
