These fields can be set by executor nodes to record how many parallel
workers were planned to be launched and how many of them have been
actually launched within the number initially planned. This data is
able to give an approximation of the parallel worker draught a system
is facing, making easier the tuning of related configuration parameters.
These fields will be used by some follow-up patches to populate other
parts of the system with their data.
Author: Guillaume Lelarge, Benoit Lobréau
Discussion: https://postgr.es/m/783bc7f7-659a-42fa-99dd-ee0565644e25@dalibo.com
Discussion: https://postgr.es/m/CAECtzeWtTGOK0UgKXdDGpfTVSa5bd_VbUt6K6xn8P7X+_dZqKw@mail.gmail.com
This is a continuation of work like 11c34b342bd7, done to reduce the
bloat of pg_stat_statements by applying more normalization to query
entries. This commit is able to detect and normalize values in
VariableSetStmt, resulting in:
SET conf_param = $1
Compared to other parse nodes, VariableSetStmt is embedded in much more
places in the parser, impacting many query patterns in
pg_stat_statements. A custom jumble function is used, with an extra
field in the node to decide if arguments should be included in the
jumbling or not, a location field being not enough for this purpose.
This approach allows for a finer tuning.
Clauses relying on one or more keywords are not normalized, for example:
* DEFAULT
* FROM CURRENT
* List of keywords. SET SESSION CHARACTERISTICS AS TRANSACTION,
where it is critical to differentiate different sets of options, is a
good example of why normalization should not happen.
Some queries use VariableSetStmt for some subclauses with SET, that also
have their values normalized:
- ALTER DATABASE
- ALTER ROLE
- ALTER SYSTEM
- CREATE/ALTER FUNCTION
ba90eac7a995 has added test coverage for most of the existing SET
patterns. The expected output of these tests shows the difference this
commit creates. Normalization could be perhaps applied to more portions
of the grammar but what is done here is conservative, and good enough as
a starting point.
Author: Greg Sabino Mullane, Michael Paquier
Discussion: https://postgr.es/m/36e5bffe-e989-194f-85c8-06e7bc88e6f7@amazon.com
Discussion: https://postgr.es/m/B44FA29D-EBD0-4DD9-ABC2-16F1CB087074@amazon.com
Discussion: https://postgr.es/m/CAKAnmmJtJY2jzQN91=2QAD2eAJAA-Per61eyO48-TyxEg-q0Rg@mail.gmail.com
The previous commit fixed some ways of losing an inplace update. It
remained possible to lose one when a backend working toward a
heap_update() copied a tuple into memory just before inplace update of
that tuple. In catalogs eligible for inplace update, use LOCKTAG_TUPLE
to govern admission to the steps of copying an old tuple, modifying it,
and issuing heap_update(). This includes MERGE commands. To avoid
changing most of the pg_class DDL, don't require LOCKTAG_TUPLE when
holding a relation lock sufficient to exclude inplace updaters.
Back-patch to v12 (all supported versions). In v13 and v12, "UPDATE
pg_class" or "UPDATE pg_database" can still lose an inplace update. The
v14+ UPDATE fix needs commit 86dc90056dfdbd9d1b891718d2e5614e3e432f35,
and it wasn't worth reimplementing that fix without such infrastructure.
Reviewed by Nitin Motiani and (in earlier versions) Heikki Linnakangas.
Discussion: https://postgr.es/m/20231027214946.79.nmisch@google.com
Add PERIOD clause to foreign key constraint definitions. This is
supported for range and multirange types. Temporal foreign keys check
for range containment instead of equality.
This feature matches the behavior of the SQL standard temporal foreign
keys, but it works on PostgreSQL's native ranges instead of SQL's
"periods", which don't exist in PostgreSQL (yet).
Reference actions ON {UPDATE,DELETE} {CASCADE,SET NULL,SET DEFAULT}
are not supported yet.
(previously committed as 34768ee3616, reverted by 8aee330af55; this is
essentially unchanged from those)
Author: Paul A. Jungwirth <pj@illuminatedcomputing.com>
Reviewed-by: Peter Eisentraut <peter@eisentraut.org>
Reviewed-by: jian he <jian.universality@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/CA+renyUApHgSZF9-nd-a0+OPGharLQLO=mDHcY4_qQ0+noCUVg@mail.gmail.com
Add WITHOUT OVERLAPS clause to PRIMARY KEY and UNIQUE constraints.
These are backed by GiST indexes instead of B-tree indexes, since they
are essentially exclusion constraints with = for the scalar parts of
the key and && for the temporal part.
(previously committed as 46a0cd4cefb, reverted by 46a0cd4cefb; the new
part is this:)
Because 'empty' && 'empty' is false, the temporal PK/UQ constraint
allowed duplicates, which is confusing to users and breaks internal
expectations. For instance, when GROUP BY checks functional
dependencies on the PK, it allows selecting other columns from the
table, but in the presence of duplicate keys you could get the value
from any of their rows. So we need to forbid empties.
This all means that at the moment we can only support ranges and
multiranges for temporal PK/UQs, unlike the original patch (above).
Documentation and tests for this are added. But this could
conceivably be extended by introducing some more general support for
the notion of "empty" for other types.
Author: Paul A. Jungwirth <pj@illuminatedcomputing.com>
Reviewed-by: Peter Eisentraut <peter@eisentraut.org>
Reviewed-by: jian he <jian.universality@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/CA+renyUApHgSZF9-nd-a0+OPGharLQLO=mDHcY4_qQ0+noCUVg@mail.gmail.com
If there are subqueries in the grouping expressions, each of these
subqueries in the targetlist and HAVING clause is expanded into
distinct SubPlan nodes. As a result, only one of these SubPlan nodes
would be converted to reference to the grouping key column output by
the Agg node; others would have to get evaluated afresh. This is not
efficient, and with grouping sets this can cause wrong results issues
in cases where they should go to NULL because they are from the wrong
grouping set. Furthermore, during re-evaluation, these SubPlan nodes
might use nulled column values from grouping sets, which is not
correct.
This issue is not limited to subqueries. For other types of
expressions that are part of grouping items, if they are transformed
into another form during preprocessing, they may fail to match lower
target items. This can also lead to wrong results with grouping sets.
To fix this issue, we introduce a new kind of RTE representing the
output of the grouping step, with columns that are the Vars or
expressions being grouped on. In the parser, we replace the grouping
expressions in the targetlist and HAVING clause with Vars referencing
this new RTE, so that the output of the parser directly expresses the
semantic requirement that the grouping expressions be gotten from the
grouping output rather than computed some other way. In the planner,
we first preprocess all the columns of this new RTE and then replace
any Vars in the targetlist and HAVING clause that reference this new
RTE with the underlying grouping expressions, so that we will have
only one instance of a SubPlan node for each subquery contained in the
grouping expressions.
Bump catversion because this changes the querytree produced by the
parser.
Thanks to Tom Lane for the idea to invent a new kind of RTE.
Per reports from Geoff Winkless, Tobias Wendorff, Richard Guo from
various threads.
Author: Richard Guo
Reviewed-by: Ashutosh Bapat, Sutou Kouhei
Discussion: https://postgr.es/m/CAMbWs4_dp7e7oTwaiZeBX8+P1rXw4ThkZxh1QG81rhu9Z47VsQ@mail.gmail.com
When WindowAgg finished one partition of a PARTITION BY, it previously
would call tuplestore_end() to purge all the stored tuples before again
calling tuplestore_begin_heap() and carefully setting up all of the
tuplestore read pointers exactly as required for the given frameOptions.
Since the frameOptions don't change between partitions, this part does
not make much sense. For queries that had very few rows per partition,
the overhead of this was very large.
It seems much better to create the tuplestore and the read pointers once
and simply call tuplestore_clear() at the end of each partition.
tuplestore_clear() moves all of the read pointers back to the start
position and deletes all the previously stored tuples.
A simple test query with 1 million partitions and 1 tuple per partition
has been shown to run around 40% faster than without this change. The
additional effort seems to have mostly been spent in malloc/free.
Making this work required adding a new bool field to WindowAggState
which had the unfortunate effect of being the 9th bool field in a group
resulting in the struct being enlarged. Here we shuffle the fields
around a little so that the two bool fields for runcondition relating
stuff fit into existing padding. Also, move the "runcondition" field to
be near those. This frees up enough space with the other bool fields so
that the newly added one fits into the padding bytes. This was done to
address a very small but apparent performance regression with queries
containing a large number of rows per partition.
Reviewed-by: Ashutosh Bapat <ashutosh.bapat.oss@gmail.com>
Reviewed-by: Tatsuo Ishii <ishii@postgresql.org>
Discussion: https://postgr.es/m/CAHoyFK9n-QCXKTUWT_xxtXninSMEv%2BgbJN66-y6prM3f4WkEHw%40mail.gmail.com
This commit reverts 1adf16b8fb, 87c21bb941, and subsequent fixes and
improvements including df64c81ca9, c99ef1811a, 9dfcac8e15, 885742b9f8,
842c9b2705, fcf80c5d5f, 96c7381c4c, f4fc7cb54b, 60ae37a8bc, 259c96fa8f,
449cdcd486, 3ca43dbbb6, 2a679ae94e, 3a82c689fd, fbd4321fd5, d53a4286d7,
c086896625, 4e5d6c4091, 04158e7fa3.
The reason for reverting is security issues related to repeatable name lookups
(CVE-2014-0062). Even though 04158e7fa3 solved part of the problem, there
are still remaining issues, which aren't feasible to even carefully analyze
before the RC deadline.
Reported-by: Noah Misch, Robert Haas
Discussion: https://postgr.es/m/20240808171351.a9.nmisch%40google.com
Backpatch-through: 17
Currently, createPartitionTable() opens newly created table using its name.
This approach is prone to privilege escalation attack, because we might end
up opening another table than we just created.
This commit address the issue above by opening newly created table by its
OID. It appears to be tricky to get a relation OID out of ProcessUtility().
We have to extend TableLikeClause with new newRelationOid field, which is
filled within ProcessUtility() to be further accessed by caller.
Security: CVE-2014-0062
Reported-by: Noah Misch
Discussion: https://postgr.es/m/20240808171351.a9.nmisch%40google.com
Reviewed-by: Pavel Borisov, Dmitry Koval
Now that disable_cost is not included in the cost estimate, there's
no visible sign in EXPLAIN output of which plan nodes are disabled.
Fix that by propagating the number of disabled nodes from Path to
Plan, and then showing it in the EXPLAIN output.
There is some question about whether this is a desirable change.
While I personally believe that it is, it seems best to make it a
separate commit, in case we decide to back out just this part, or
rework it.
Reviewed by Andres Freund, Heikki Linnakangas, and David Rowley.
Discussion: http://postgr.es/m/CA+TgmoZ_+MS+o6NeGK2xyBv-xM+w1AfFVuHE4f_aq6ekHv7YSQ@mail.gmail.com
Previously, when a path type was disabled by e.g. enable_seqscan=false,
we either avoided generating that path type in the first place, or
more commonly, we added a large constant, called disable_cost, to the
estimated startup cost of that path. This latter approach can distort
planning. For instance, an extremely expensive non-disabled path
could seem to be worse than a disabled path, especially if the full
cost of that path node need not be paid (e.g. due to a Limit).
Or, as in the regression test whose expected output changes with this
commit, the addition of disable_cost can make two paths that would
normally be distinguishible in cost seem to have fuzzily the same cost.
To fix that, we now count the number of disabled path nodes and
consider that a high-order component of both the startup cost and the
total cost. Hence, the path list is now sorted by disabled_nodes and
then by total_cost, instead of just by the latter, and likewise for
the partial path list. It is important that this number is a count
and not simply a Boolean; else, as soon as we're unable to respect
disabled path types in all portions of the path, we stop trying to
avoid them where we can.
Because the path list is now sorted by the number of disabled nodes,
the join prechecks must compute the count of disabled nodes during
the initial cost phase instead of postponing it to final cost time.
Counts of disabled nodes do not cross subquery levels; at present,
there is no reason for them to do so, since the we do not postpone
path selection across subquery boundaries (see make_subplan).
Reviewed by Andres Freund, Heikki Linnakangas, and David Rowley.
Discussion: http://postgr.es/m/CA+TgmoZ_+MS+o6NeGK2xyBv-xM+w1AfFVuHE4f_aq6ekHv7YSQ@mail.gmail.com
Here we add ExprState support for obtaining a 32-bit hash value from a
list of expressions. This allows both faster hashing and also JIT
compilation of these expressions. This is especially useful when hash
joins have multiple join keys as the previous code called ExecEvalExpr on
each hash join key individually and that was inefficient as tuple
deformation would have only taken into account one key at a time, which
could lead to walking the tuple once for each join key. With the new
code, we'll determine the maximum attribute required and deform the tuple
to that point only once.
Some performance tests done with this change have shown up to a 20%
performance increase of a query containing a Hash Join without JIT
compilation and up to a 26% performance increase when JIT is enabled and
optimization and inlining were performed by the JIT compiler. The
performance increase with 1 join column was less with a 14% increase
with and without JIT. This test was done using a fairly small hash
table and a large number of hash probes. The increase will likely be
less with large tables, especially ones larger than L3 cache as memory
pressure is more likely to be the limiting factor there.
This commit only addresses Hash Joins, but lays expression evaluation
and JIT compilation infrastructure for other hashing needs such as Hash
Aggregate.
Author: David Rowley
Reviewed-by: Alexey Dvoichenkov <alexey@hyperplane.net>
Reviewed-by: Tels <nospam-pg-abuse@bloodgate.com>
Discussion: https://postgr.es/m/CAApHDvoexAxgQFNQD_GRkr2O_eJUD1-wUGm%3Dm0L%2BGc%3DT%3DkEa4g%40mail.gmail.com
This converts
COPY_PARSE_PLAN_TREES
WRITE_READ_PARSE_PLAN_TREES
RAW_EXPRESSION_COVERAGE_TEST
into run-time parameters
debug_copy_parse_plan_trees
debug_write_read_parse_plan_trees
debug_raw_expression_coverage_test
They can be activated for tests using PG_TEST_INITDB_EXTRA_OPTS.
The compile-time symbols are kept for build farm compatibility, but
they now just determine the default value of the run-time settings.
Furthermore, support for these settings is not compiled in at all
unless assertions are enabled, or the new symbol
DEBUG_NODE_TESTS_ENABLED is defined at compile time, or any of the
legacy compile-time setting symbols are defined. So there is no
run-time overhead in production builds. (This is similar to the
handling of DISCARD_CACHES_ENABLED.)
Discussion: https://www.postgresql.org/message-id/flat/30747bd8-f51e-4e0c-a310-a6e2c37ec8aa%40eisentraut.org
Until now we generated an ExprState for each parameter to a SubPlan and
evaluated them one-by-one ExecScanSubPlan. That's sub-optimal as creating lots
of small ExprStates
a) makes JIT compilation more expensive
b) wastes memory
c) is a bit slower to execute
This commit arranges to evaluate parameters to a SubPlan as part of the
ExprState referencing a SubPlan, using the new EEOP_PARAM_SET expression
step. We emit one EEOP_PARAM_SET for each argument to a subplan, just before
the EEOP_SUBPLAN step.
It likely is worth using EEOP_PARAM_SET in other places as well, e.g. for
SubPlan outputs, nestloop parameters and - more ambitiously - to get rid of
ExprContext->domainValue/caseValue/ecxt_agg*. But that's for later.
Author: Andres Freund <andres@anarazel.de>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Alena Rybakina <lena.ribackina@yandex.ru>
Discussion: https://postgr.es/m/20230225214401.346ancgjqc3zmvek@awork3.anarazel.de
"path" provides a reliable method of determining the parent/child
relationships between memory contexts. Previously this could be done in
a non-reliable way by writing a recursive query and joining the "parent"
and "name" columns. This wasn't reliable as the names were not unique,
which could result in joining to the wrong parent.
To make this reliable, "path" stores an array of numerical identifiers
starting with the identifier for TopLevelMemoryContext. It contains an
element for each intermediate parent between that and the current context.
Incompatibility: Here we also adjust the "level" column to make it
1-based rather than 0-based. A 1-based level provides a convenient way
to access elements in the "path" array. e.g. path[level] gives the
identifier for the current context.
Identifiers are not stable across multiple evaluations of the view. In
an attempt to make these more stable for ad-hoc queries, the identifiers
are assigned breadth-first. Contexts closer to TopLevelMemoryContext
are less likely to change between queries and during queries.
Author: Melih Mutlu <m.melihmutlu@gmail.com>
Discussion: https://postgr.es/m/CAGPVpCThLyOsj3e_gYEvLoHkr5w=tadDiN_=z2OwsK3VJppeBA@mail.gmail.com
Reviewed-by: Andres Freund, Stephen Frost, Atsushi Torikoshi,
Reviewed-by: Michael Paquier, Robert Haas, David Rowley
Both of these counters were using the "long" data type. On MSVC that's
a 32-bit type. On modern hardware, I was able to demonstrate that we can
wrap those counters with a query that only takes 15 minutes to run.
This issue may manifest itself either by not showing the values of the
counters because they've wrapped and are less than zero, resulting in
them being filtered by the > 0 checks in show_tidbitmap_info(), or bogus
numbers being displayed which are modulus 2^32 of the actual number.
Widen these counters to uint64.
Discussion: https://postgr.es/m/CAApHDvpS_97TU+jWPc=T83WPp7vJa1dTw3mojEtAVEZOWh9bjQ@mail.gmail.com
Hash joins can support semijoin with the LHS input on the right, using
the existing logic for inner join, combined with the assurance that only
the first match for each inner tuple is considered, which can be
achieved by leveraging the HEAP_TUPLE_HAS_MATCH flag. This can be very
useful in some cases since we may now have the option to hash the
smaller table instead of the larger.
Merge join could likely support "Right Semi Join" too. However, the
benefit of swapping inputs tends to be small here, so we do not address
that in this patch.
Note that this patch also modifies a test query in join.sql to ensure it
continues testing as intended. With this patch the original query would
result in a right-semi-join rather than semi-join, compromising its
original purpose of testing the fix for neqjoinsel's behavior for
semi-joins.
Author: Richard Guo
Reviewed-by: wenhui qiu, Alena Rybakina, Japin Li
Discussion: https://postgr.es/m/CAMbWs4_X1mN=ic+SxcyymUqFx9bB8pqSLTGJ-F=MHy4PW3eRXw@mail.gmail.com
Instead of looking up casts at parse time for converting the result
of JsonPath* query functions to the specified or the default
RETURNING type, always perform the conversion at runtime using either
the target type's input function or the function
json_populate_type().
There are two motivations for this change:
1. json_populate_type() coerces to types with typmod such that any
string values that exceed length limit cause an error instead of
silent truncation, which is necessary to be standard-conforming.
2. It was possible to end up with a cast expression that doesn't
support soft handling of errors causing bugs in the of handling
ON ERROR clause.
JsonExpr.coercion_expr which would store the cast expression is no
longer necessary, so remove.
Bump catversion because stored rules change because of the above
removal.
Reported-by: Alvaro Herrera <alvherre@alvh.no-ip.org>
Reviewed-by: Jian He <jian.universality@gmail.com>
Discussion: Discussion: https://postgr.es/m/202405271326.5a5rprki64aw%40alvherre.pgsql
0452b461bc made optimizer explore alternative orderings of group-by pathkeys.
It eliminated preprocess_groupclause(), which was intended to match items
between GROUP BY and ORDER BY. Instead, get_useful_group_keys_orderings()
function generates orderings of GROUP BY elements at the time of grouping
paths generation. The get_useful_group_keys_orderings() function takes into
account 3 orderings of GROUP BY pathkeys and clauses: original order as written
in GROUP BY, matching ORDER BY clauses as much as possible, and matching the
input path as much as possible. Given that even before 0452b461b,
preprocess_groupclause() could change the original order of GROUP BY clauses
we don't need to consider it apart from ordering matching ORDER BY clauses.
This commit restores preprocess_groupclause() to provide an ordering of
GROUP BY elements matching ORDER BY before generation of paths. The new
version of preprocess_groupclause() takes into account an incremental sort.
The get_useful_group_keys_orderings() function now takes into 2 orderings of
GROUP BY elements: the order generated preprocess_groupclause() and the order
matching the input path as much as possible.
Discussion: https://postgr.es/m/CAPpHfdvyWLMGwvxaf%3D7KAp-z-4mxbSH8ti2f6mNOQv5metZFzg%40mail.gmail.com
Author: Alexander Korotkov
Reviewed-by: Andrei Lepikhov, Pavel Borisov
0452b461bc made optimizer explore alternative orderings of group-by pathkeys.
The PathKeyInfo data structure was used to store the particular ordering of
group-by pathkeys and corresponding clauses. It turns out that PathKeyInfo
is not the best name for that purpose. This commit renames this data structure
to GroupByOrdering, and revises its comment.
Discussion: https://postgr.es/m/db0fc3a4-966c-4cec-a136-94024d39212d%40postgrespro.ru
Reported-by: Tom Lane
Author: Andrei Lepikhov
Reviewed-by: Alexander Korotkov, Pavel Borisov
This reverts commit 7204f35919b7e021e8d1bc9f2d76fd6bfcdd2070,
thus restoring 66c0185a3 (Allow planner to use Merge Append to
efficiently implement UNION) as well as the follow-on commits
d5d2205c8, 3b1a7eb28, 7487044d6.
Per further discussion on pgsql-release, we wish to ship beta1 with
this feature, and patch the bug that was found just before wrap,
rather than shipping beta1 with the feature reverted.
This reverts 66c0185a3 (Allow planner to use Merge Append to
efficiently implement UNION) as well as the follow-on commits
d5d2205c8, 3b1a7eb28, 7487044d6. In addition to those, 07746a8ef
had to be removed then re-applied in a different place, because
66c0185a3 moved the relevant code.
The reason for this last-minute thrashing is that depesz found a
case in which the patched code creates a completely wrong plan
that silently gives incorrect query results. It's unclear what
the cause is or how many cases are affected, but with beta1 wrap
staring us in the face, there's no time for closer investigation.
After we figure that out, we can decide whether to un-revert this
for beta2 or hold it for v18.
Discussion: https://postgr.es/m/Zktzf926vslR35Fv@depesz.com
(also some private discussion among pgsql-release)
This feature set did not handle empty ranges correctly, and it's now
too late for PostgreSQL 17 to fix it.
The following commits are reverted:
6db4598fcb8 Add stratnum GiST support function
46a0cd4cefb Add temporal PRIMARY KEY and UNIQUE constraints
86232a49a43 Fix comment on gist_stratnum_btree
030e10ff1a3 Rename pg_constraint.conwithoutoverlaps to conperiod
a88c800deb6 Use daterange and YMD in without_overlaps tests instead of tsrange.
5577a71fb0c Use half-open interval notation in without_overlaps tests
34768ee3616 Add temporal FOREIGN KEY contraints
482e108cd38 Add test for REPLICA IDENTITY with a temporal key
c3db1f30cba doc: clarify PERIOD and WITHOUT OVERLAPS in CREATE TABLE
144c2ce0cc7 Fix ON CONFLICT DO NOTHING/UPDATE for temporal indexes
Discussion: https://www.postgresql.org/message-id/d0b64a7a-dfe4-4b84-a906-c7dedfa40a3e@eisentraut.org
There are some problems with the new way to handle these constraints
that were detected at the last minute, and require fixes that appear too
invasive to be doing this late in the cycle. Revert this (again) for
now, we'll try again with these problems fixed.
The following commits are reverted:
b0e96f311985 Catalog not-null constraints
9b581c534186 Disallow changing NO INHERIT status of a not-null constraint
d0ec2ddbe088 Fix not-null constraint test
ac22a9545ca9 Move privilege check to the right place
b0f7dd915bca Check stack depth in new recursive functions
3af721794272 Update information_schema definition for not-null constraints
c3709100be73 Fix propagating attnotnull in multiple inheritance
d9f686a72ee9 Fix restore of not-null constraints with inheritance
d72d32f52d26 Don't try to assign smart names to constraints
0cd711271d42 Better handle indirect constraint drops
13daa33fa5a6 Disallow NO INHERIT not-null constraints on partitioned tables
d45597f72fe5 Disallow direct change of NO INHERIT of not-null constraints
21ac38f498b3 Fix inconsistencies in error messages
Discussion: https://postgr.es/m/202405110940.joxlqcx4dogd@alvherre.pgsql
This commit reverts d3d55ce5713 and subsequent fixes 2b26a694554, 93c85db3b5b,
b44a1708abe, b7f315c9d7d, 8a8ed916f73, b5fb6736ed3, 0a93f803f45, e0477837ce4,
a7928a57b9f, 5ef34a8fc38, 30b4955a466, 8c441c08279, 028b15405b4, fe093994db4,
489072ab7a9, and 466979ef031.
We are quite late in the release cycle and new bugs continue to appear. Even
though we have fixes for all known bugs, there is a risk of throwing many
bugs to end users.
The plan for self-join elimination would be to do more review and testing,
then re-commit in the early v18 cycle.
Reported-by: Tom Lane
Discussion: https://postgr.es/m/2422119.1714691974%40sss.pgh.pa.us
94985c210 added code to detect when WindowFuncs were monotonic and
allowed additional quals to be "pushed down" into the subquery to be
used as WindowClause runConditions in order to short-circuit execution
in nodeWindowAgg.c.
The Node representation of runConditions wasn't well selected and
because we do qual pushdown before planning the subquery, the planning
of the subquery could perform subquery pull-up of nested subqueries.
For WindowFuncs with args, the arguments could be changed after pushing
the qual down to the subquery.
This was made more difficult by the fact that the code duplicated the
WindowFunc inside an OpExpr to include in the WindowClauses runCondition
field. This could result in duplication of subqueries and a pull-up of
such a subquery could result in another initplan parameter being issued
for the 2nd version of the subplan. This could result in errors such as:
ERROR: WindowFunc not found in subplan target lists
To fix this, we change the node representation of these run conditions
and instead of storing an OpExpr containing the WindowFunc in a list
inside WindowClause, we now store a new node type named
WindowFuncRunCondition within a new field in the WindowFunc. These get
transformed into OpExprs later in planning once subquery pull-up has been
performed.
This problem did exist in v15 and v16, but that was fixed by 9d36b883b
and e5d20bbd.
Cat version bump due to new node type and modifying WindowFunc struct.
Bug: #18305
Reported-by: Zuming Jiang
Discussion: https://postgr.es/m/18305-33c49b4c830b37b3%40postgresql.org
As an optimization, we store "name" columns as cstrings in btree
indexes.
Here we modify it so that Index Only Scans convert these cstrings back
to names with NAMEDATALEN bytes rather than storing the cstring in the
tuple slot, as was happening previously.
Bug: #17855
Reported-by: Alexander Lakhin
Reviewed-by: Alexander Lakhin, Tom Lane
Discussion: https://postgr.es/m/17855-5f523e0f9769a566@postgresql.org
Backpatch-through: 12, all supported versions
This field is not used directly in the code, but it is important for
query jumbling to be able to make a difference between a named
DEALLOCATE and DEALLOCATE ALL (see bb45156f342c). This behavior is
tracked in the regression tests of pg_stat_statements, but the reason
why this field is important can be easily missed, as a recent discussion
has proved, so let's improve its comment to document the reason why it
needs to be around.
Wording has been suggested by Tom Lane
Discussion: https://postgr.es/m/Zih1ATt37YFda8_p@paquier.xyz
JsonExprState.input_finfo is only assigned to, never read, and
it's really fairly useless since the value can be gotten out of
the adjacent input_fcinfo field. Let's remove it before someone
starts to depend on it.
While here, also remove TidScanState.tss_htup and AggState.combinedproj,
which are referenced nowhere. Those should have been removed by the
commits that caused them to become disused, but were not.
I don't think a catversion bump is necessary here, since plan trees
are never stored on disk.
Matthias van de Meent
Discussion: https://postgr.es/m/CAEze2WjsY4d0TBymLNGK4zpttUcg_YZaTjyWz2VfDUV6YH8wXQ@mail.gmail.com
This improves some error messages emitted by SQL/JSON query functions
by mentioning column name when available, such as when they are
invoked as part of evaluating JSON_TABLE() columns. To do so, a new
field column_name is added to both JsonFuncExpr and JsonExpr that is
only populated when creating those nodes for transformed JSON_TABLE()
columns.
While at it, relevant error messages are reworded for clarity.
Reported-by: Jian He <jian.universality@gmail.com>
Suggested-by: Jian He <jian.universality@gmail.com>
Discussion: https://postgr.es/m/CACJufxG_e0QLCgaELrr2ZNz7AxPeGCNKAORe3fHtFCQLsH4J4Q@mail.gmail.com
b262ad440 added code to have the planner remove redundant IS NOT NULL
quals and eliminate needless scans for IS NULL quals on tables where the
qual's column has a NOT NULL constraint.
That commit failed to consider that an inheritance parent table could
have differing NOT NULL constraints between the parent and the child.
This caused issues as if we eliminated a qual on the parent, when
applying the quals to child tables in apply_child_basequals(), the qual
might not have been added to the parent's baserestrictinfo.
Here we fix this by not applying the optimization to remove redundant
quals to RelOptInfos belonging to inheritance parents and applying the
optimization again in apply_child_basequals(). Effectively, this means
that the parent and child are considered independently as the parent has
both an inh=true and inh=false RTE and we still apply the optimization
to the RelOptInfo corresponding to the inh=false RTE.
We're able to still apply the optimization in add_base_clause_to_rel()
for partitioned tables as the NULLability of partitions must match that
of their parent. And, if we ever expand restriction_is_always_false()
and restriction_is_always_true() to handle partition constraints then we
can apply the same logic as, even in multi-level partitioned tables,
there's no way to route values to a partition when the qual does not
match the partition qual of the partitioned table's parent partition.
The same is true for CHECK constraints as those must also match between
arent partitioned tables and their partitions.
Author: Richard Guo, David Rowley
Discussion: https://postgr.es/m/CAMbWs4930gQSZmjR7aANzEapdy61gCg6z8dT-kAEYD0sYWKPdQ@mail.gmail.com
Replace (expr op C1) OR (expr op C2) ... with expr op ANY(ARRAY[C1, C2, ...])
on the preliminary stage of optimization when we are still working with the
expression tree.
Here Cn is a n-th constant expression, 'expr' is non-constant expression, 'op'
is an operator which returns boolean result and has a commuter (for the case
of reverse order of constant and non-constant parts of the expression,
like 'Cn op expr').
Sometimes it can lead to not optimal plan. This is why there is a
or_to_any_transform_limit GUC. It specifies a threshold value of length of
arguments in an OR expression that triggers the OR-to-ANY transformation.
Generally, more groupable OR arguments mean that transformation will be more
likely to win than to lose.
Discussion: https://postgr.es/m/567ED6CA.2040504%40sigaev.ru
Author: Alena Rybakina <lena.ribackina@yandex.ru>
Author: Andrey Lepikhov <a.lepikhov@postgrespro.ru>
Reviewed-by: Peter Geoghegan <pg@bowt.ie>
Reviewed-by: Ranier Vilela <ranier.vf@gmail.com>
Reviewed-by: Alexander Korotkov <aekorotkov@gmail.com>
Reviewed-by: Robert Haas <robertmhaas@gmail.com>
Reviewed-by: Jian He <jian.universality@gmail.com>
This introduces a bump MemoryContext type. The bump context is best
suited for short-lived memory contexts which require only allocations
of memory and never a pfree or repalloc, which are unsupported.
Memory palloc'd into a bump context has no chunk header. This makes
bump a useful context type when lots of small allocations need to be
done without any need to pfree those allocations. Allocation sizes are
rounded up to the next MAXALIGN boundary, so with this and no chunk
header, allocations are very compact indeed.
Allocations are also very fast as bump does not check any freelists to
try and make use of previously free'd chunks. It just checks if there
is enough room on the current block, and if so it bumps the freeptr
beyond this chunk and returns the value that the freeptr was previously
pointing to. Simple and fast. A new block is malloc'd when there's not
enough space in the current block.
Code using the bump allocator must take care never to call any functions
which could try to call realloc() (or variants), pfree(),
GetMemoryChunkContext() or GetMemoryChunkSpace() on a bump allocated
chunk. Due to lack of chunk headers, these operations are unsupported.
To increase the chances of catching such issues, when compiled with
MEMORY_CONTEXT_CHECKING, bump allocated chunks are given a header and
any attempt to perform an unsupported operation will result in an ERROR.
Without MEMORY_CONTEXT_CHECKING, code attempting an unsupported
operation could result in a segfault.
A follow-on commit will implement the first user of bump.
Author: David Rowley
Reviewed-by: Nathan Bossart
Reviewed-by: Matthias van de Meent
Reviewed-by: Tomas Vondra
Reviewed-by: John Naylor
Discussion: https://postgr.es/m/CAApHDvqGSpCU95TmM=Bp=6xjL_nLys4zdZOpfNyWBk97Xrdj2w@mail.gmail.com
Commit 7c70996ebf0949b142 introduced an optimization to allow bitmap
scans to operate like index-only scans by not fetching a block from the
heap if none of the underlying data is needed and the block is marked
all visible in the visibility map.
With the introduction of table AMs, a FIXME was added to this code
indicating that the skip_fetch logic should be pushed into the table
AM-specific code, as not all table AMs may use a visibility map in the
same way.
This commit resolves this FIXME for the current block. The layering
violation is still present in BitmapHeapScans's prefetching code, which
uses the visibility map to decide whether or not to prefetch a block.
However, this can be addressed independently.
Author: Melanie Plageman
Reviewed-by: Andres Freund, Heikki Linnakangas, Tomas Vondra, Mark Dilger
Discussion: https://postgr.es/m/CAAKRu_ZwCwWFeL_H3ia26bP2e7HiKLWt0ZmGXPVwPO6uXq0vaA%40mail.gmail.com
This new DDL command splits a single partition into several parititions.
Just like ALTER TABLE ... MERGE PARTITIONS ... command, new patitions are
created using createPartitionTable() function with parent partition as the
template.
This commit comprises quite naive implementation which works in single process
and holds the ACCESS EXCLUSIVE LOCK on the parent table during all the
operations including the tuple routing. This is why this new DDL command
can't be recommended for large partitioned tables under a high load. However,
this implementation come in handy in certain cases even as is.
Also, it could be used as a foundation for future implementations with lesser
locking and possibly parallel.
Discussion: https://postgr.es/m/c73a1746-0cd0-6bdd-6b23-3ae0b7c0c582%40postgrespro.ru
Author: Dmitry Koval
Reviewed-by: Matthias van de Meent, Laurenz Albe, Zhihong Yu, Justin Pryzby
Reviewed-by: Alvaro Herrera, Robert Haas, Stephane Tachoires
This new DDL command merges several partitions into the one partition of the
target table. The target partition is created using new
createPartitionTable() function with parent partition as the template.
This commit comprises quite naive implementation which works in single process
and holds the ACCESS EXCLUSIVE LOCK on the parent table during all the
operations including the tuple routing. This is why this new DDL command
can't be recommended for large partitioned tables under a high load. However,
this implementation come in handy in certain cases even as is.
Also, it could be used as a foundation for future implementations with lesser
locking and possibly parallel.
Discussion: https://postgr.es/m/c73a1746-0cd0-6bdd-6b23-3ae0b7c0c582%40postgrespro.ru
Author: Dmitry Koval
Reviewed-by: Matthias van de Meent, Laurenz Albe, Zhihong Yu, Justin Pryzby
Reviewed-by: Alvaro Herrera, Robert Haas, Stephane Tachoires
JSON_TABLE() allows JSON data to be converted into a relational view
and thus used, for example, in a FROM clause, like other tabular
data. Data to show in the view is selected from a source JSON object
using a JSON path expression to get a sequence of JSON objects that's
called a "row pattern", which becomes the source to compute the
SQL/JSON values that populate the view's output columns. Column
values themselves are computed using JSON path expressions applied to
each of the JSON objects comprising the "row pattern", for which the
SQL/JSON query functions added in 6185c9737cf4 are used.
To implement JSON_TABLE() as a table function, this augments the
TableFunc and TableFuncScanState nodes that are currently used to
support XMLTABLE() with some JSON_TABLE()-specific fields.
Note that the JSON_TABLE() spec includes NESTED COLUMNS and PLAN
clauses, which are required to provide more flexibility to extract
data out of nested JSON objects, but they are not implemented here
to keep this commit of manageable size.
Author: Nikita Glukhov <n.gluhov@postgrespro.ru>
Author: Teodor Sigaev <teodor@sigaev.ru>
Author: Oleg Bartunov <obartunov@gmail.com>
Author: Alexander Korotkov <aekorotkov@gmail.com>
Author: Andrew Dunstan <andrew@dunslane.net>
Author: Amit Langote <amitlangote09@gmail.com>
Author: Jian He <jian.universality@gmail.com>
Reviewers have included (in no particular order):
Andres Freund, Alexander Korotkov, Pavel Stehule, Andrew Alsup,
Erik Rijkers, Zihong Yu, Himanshu Upadhyaya, Daniel Gustafsson,
Justin Pryzby, Álvaro Herrera, Jian He
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
Discussion: https://postgr.es/m/20220616233130.rparivafipt6doj3@alap3.anarazel.de
Discussion: https://postgr.es/m/abd9b83b-aa66-f230-3d6d-734817f0995d%40postgresql.org
Discussion: https://postgr.es/m/CA+HiwqE4XTdfb1nW=Ojoy_tQSRhYt-q_kb6i5d4xcKyrLC1Nbg@mail.gmail.com
This allows MERGE commands to include WHEN NOT MATCHED BY SOURCE
actions, which operate on rows that exist in the target relation, but
not in the data source. These actions can execute UPDATE, DELETE, or
DO NOTHING sub-commands.
This is in contrast to already-supported WHEN NOT MATCHED actions,
which operate on rows that exist in the data source, but not in the
target relation. To make this distinction clearer, such actions may
now be written as WHEN NOT MATCHED BY TARGET.
Writing WHEN NOT MATCHED without specifying BY SOURCE or BY TARGET is
equivalent to writing WHEN NOT MATCHED BY TARGET.
Dean Rasheed, reviewed by Alvaro Herrera, Ted Yu and Vik Fearing.
Discussion: https://postgr.es/m/CAEZATCWqnKGc57Y_JanUBHQXNKcXd7r=0R4NEZUVwP+syRkWbA@mail.gmail.com
