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The executor will dump core if it's asked to execute a seqscan on
a relation having no table AM, such as a view. While that shouldn't
really happen, it's possible to get there via catalog corruption,
such as a missing ON SELECT rule. It seems worth installing a defense
against that. There are multiple plausible places for such a defense,
but I picked the planner's get_relation_info().
Per discussion of bug #17646 from Kui Liu. Back-patch to v12 where
the tableam APIs were introduced; in older versions you won't get a
SIGSEGV, so it seems less pressing.
Discussion: https://postgr.es/m/17646-70c93cfa40365776@postgresql.org
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In a similar effort to f01592f91, here we mostly rename shadowed local
variables to remove the warnings produced when compiling with
-Wshadow=compatible-local.
This fixes 63 warnings and leaves just 5.
Author: Justin Pryzby, David Rowley
Reviewed-by: Justin Pryzby
Discussion https://postgr.es/m/20220817145434.GC26426%40telsasoft.com
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This reverts commit db0d67db2401eb6238ccc04c6407a4fd4f985832 and
several follow-on fixes. The idea of making a cost-based choice
of the order of the sorting columns is not fundamentally unsound,
but it requires cost information and data statistics that we don't
really have. For example, relying on procost to distinguish the
relative costs of different sort comparators is pretty pointless
so long as most such comparator functions are labeled with cost 1.0.
Moreover, estimating the number of comparisons done by Quicksort
requires more than just an estimate of the number of distinct values
in the input: you also need some idea of the sizes of the larger
groups, if you want an estimate that's good to better than a factor of
three or so. That's data that's often unknown or not very reliable.
Worse, to arrive at estimates of the number of calls made to the
lower-order-column comparison functions, the code needs to make
estimates of the numbers of distinct values of multiple columns,
which are necessarily even less trustworthy than per-column stats.
Even if all the inputs are perfectly reliable, the cost algorithm
as-implemented cannot offer useful information about how to order
sorting columns beyond the point at which the average group size
is estimated to drop to 1.
Close inspection of the code added by db0d67db2 shows that there
are also multiple small bugs. These could have been fixed, but
there's not much point if we don't trust the estimates to be
accurate in-principle.
Finally, the changes in cost_sort's behavior made for very large
changes (often a factor of 2 or so) in the cost estimates for all
sorting operations, not only those for multi-column GROUP BY.
That naturally changes plan choices in many situations, and there's
precious little evidence to show that the changes are for the better.
Given the above doubts about whether the new estimates are really
trustworthy, it's hard to summon much confidence that these changes
are better on the average.
Since we're hard up against the release deadline for v15, let's
revert these changes for now. We can always try again later.
Note: in v15, I left T_PathKeyInfo in place in nodes.h even though
it's unreferenced. Removing it would be an ABI break, and it seems
a bit late in the release cycle for that.
Discussion: https://postgr.es/m/TYAPR01MB586665EB5FB2C3807E893941F5579@TYAPR01MB5866.jpnprd01.prod.outlook.com
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Autoconf is showing its age, fewer and fewer contributors know how to wrangle
it. Recursive make has a lot of hard to resolve dependency issues and slow
incremental rebuilds. Our home-grown MSVC build system is hard to maintain for
developers not using Windows and runs tests serially. While these and other
issues could individually be addressed with incremental improvements, together
they seem best addressed by moving to a more modern build system.
After evaluating different build system choices, we chose to use meson, to a
good degree based on the adoption by other open source projects.
We decided that it's more realistic to commit a relatively early version of
the new build system and mature it in tree.
This commit adds an initial version of a meson based build system. It supports
building postgres on at least AIX, FreeBSD, Linux, macOS, NetBSD, OpenBSD,
Solaris and Windows (however only gcc is supported on aix, solaris). For
Windows/MSVC postgres can now be built with ninja (faster, particularly for
incremental builds) and msbuild (supporting the visual studio GUI, but
building slower).
Several aspects (e.g. Windows rc file generation, PGXS compatibility, LLVM
bitcode generation, documentation adjustments) are done in subsequent commits
requiring further review. Other aspects (e.g. not installing test-only
extensions) are not yet addressed.
When building on Windows with msbuild, builds are slower when using a visual
studio version older than 2019, because those versions do not support
MultiToolTask, required by meson for intra-target parallelism.
The plan is to remove the MSVC specific build system in src/tools/msvc soon
after reaching feature parity. However, we're not planning to remove the
autoconf/make build system in the near future. Likely we're going to keep at
least the parts required for PGXS to keep working around until all supported
versions build with meson.
Some initial help for postgres developers is at
https://wiki.postgresql.org/wiki/Meson
With contributions from Thomas Munro, John Naylor, Stone Tickle and others.
Author: Andres Freund <andres@anarazel.de>
Author: Nazir Bilal Yavuz <byavuz81@gmail.com>
Author: Peter Eisentraut <peter@eisentraut.org>
Reviewed-By: Peter Eisentraut <peter.eisentraut@enterprisedb.com>
Discussion: https://postgr.es/m/20211012083721.hvixq4pnh2pixr3j@alap3.anarazel.de
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Make sure that function declarations use names that exactly match the
corresponding names from function definitions in optimizer, parser,
utility, libpq, and "commands" code, as well as in remaining library
code. Do the same for all code related to frontend programs (with the
exception of pg_dump/pg_dumpall related code).
Like other recent commits that cleaned up function parameter names, this
commit was written with help from clang-tidy. Later commits will handle
ecpg and pg_dump/pg_dumpall.
Author: Peter Geoghegan <pg@bowt.ie>
Reviewed-By: David Rowley <dgrowleyml@gmail.com>
Discussion: https://postgr.es/m/CAH2-WznJt9CMM9KJTMjJh_zbL5hD9oX44qdJ4aqZtjFi-zA3Tg@mail.gmail.com
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In 29f45e299, we added support for optimizing the execution of NOT
IN(values) by using a hash table instead of a linear search over the
array. That commit neglected to update the header comment for
convert_saop_to_hashed_saop() to mention this fact. Here we fix that.
Author: James Coleman
Discussion: https://postgr.es/m/CAAaqYe99NUpAPcxgchGstgM23fmiGjqQPot8627YgkBgNt=BfA@mail.gmail.com
Backpatch-through: 15, where 29f45e299 was added.
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The reverts the following and makes some associated cleanups:
commit f79b803dc: Common SQL/JSON clauses
commit f4fb45d15: SQL/JSON constructors
commit 5f0adec25: Make STRING an unreserved_keyword.
commit 33a377608: IS JSON predicate
commit 1a36bc9db: SQL/JSON query functions
commit 606948b05: SQL JSON functions
commit 49082c2cc: RETURNING clause for JSON() and JSON_SCALAR()
commit 4e34747c8: JSON_TABLE
commit fadb48b00: PLAN clauses for JSON_TABLE
commit 2ef6f11b0: Reduce running time of jsonb_sqljson test
commit 14d3f24fa: Further improve jsonb_sqljson parallel test
commit a6baa4bad: Documentation for SQL/JSON features
commit b46bcf7a4: Improve readability of SQL/JSON documentation.
commit 112fdb352: Fix finalization for json_objectagg and friends
commit fcdb35c32: Fix transformJsonBehavior
commit 4cd8717af: Improve a couple of sql/json error messages
commit f7a605f63: Small cleanups in SQL/JSON code
commit 9c3d25e17: Fix JSON_OBJECTAGG uniquefying bug
commit a79153b7a: Claim SQL standard compliance for SQL/JSON features
commit a1e7616d6: Rework SQL/JSON documentation
commit 8d9f9634e: Fix errors in copyfuncs/equalfuncs support for JSON node types.
commit 3c633f32b: Only allow returning string types or bytea from json_serialize
commit 67b26703b: expression eval: Fix EEOP_JSON_CONSTRUCTOR and EEOP_JSONEXPR size.
The release notes are also adjusted.
Backpatch to release 15.
Discussion: https://postgr.es/m/40d2c882-bcac-19a9-754d-4299e1d87ac7@postgresql.org
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The present implementations of adjust_appendrel_attrs_multilevel and
its sibling adjust_child_relids_multilevel are very messy, because
they work by reconstructing the relids of the child's immediate
parent and then seeing if that's bms_equal to the relids of the
target parent. Aside from being quite inefficient, this will not
work with planned future changes to make joinrels' relid sets
contain outer-join relids in addition to baserels.
The whole thing can be solved at a stroke by adding explicit parent
and top_parent links to child RelOptInfos, and making these functions
work with RelOptInfo pointers instead of relids. Doing that is
simpler for most callers, too.
In my original version of this patch, I got rid of
RelOptInfo.top_parent_relids on the grounds that it was now redundant.
However, that adds a lot of code churn in places that otherwise would
not need changing, and arguably the extra indirection needed to fetch
top_parent->relids in those places costs something. So this version
leaves that field in place.
Discussion: https://postgr.es/m/553080.1657481916@sss.pgh.pa.us
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Make build_joinrel_tlist() responsible for adding PHVs that were
already computed in one or the other input relation, and therefore
change add_placeholders_to_joinrel() to only add PHVs that will be
newly computed in this joinrel's output. This makes the handling
of PHVs in build_joinrel_tlist() more like its handling of plain
Vars, which seems like a good thing on intelligibility grounds
and will simplify planned future changes. There is a purely
cosmetic side-effect that the order of entries in the joinrel's
tlist may change; but since it becomes more like the order of
entries in the input tlists, that's not bad.
The reason it wasn't done like this originally was the potential
cost of looking up PlaceHolderInfo entries to consult ph_needed.
Now that that's O(1) it shouldn't hurt.
Discussion: https://postgr.es/m/1405792.1660677844@sss.pgh.pa.us
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Up to now, callers of find_placeholder_info() were required to pass
a flag indicating if it's OK to make a new PlaceHolderInfo. That'd
be fine if the callers had free choice, but they do not. Once we
begin deconstruct_jointree() it's no longer OK to make more PHIs;
while callers before that always want to create a PHI if it's not
there already. So there's no freedom of action, only the opportunity
to cause bugs by creating PHIs too late. Let's get rid of that in
favor of adding a state flag PlannerInfo.placeholdersFrozen, which
we can set at the point where it's no longer OK to make more PHIs.
This patch also simplifies a couple of call sites that were using
complicated logic to avoid calling find_placeholder_info() as much
as possible. Now that that lookup is O(1) thanks to the previous
commit, the extra bitmap manipulations are probably a net negative.
Discussion: https://postgr.es/m/1405792.1660677844@sss.pgh.pa.us
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Up to now we've just searched the placeholder_list when we want to
find the PlaceHolderInfo with a given ID. While there's no evidence
of that being a problem in the field, an upcoming patch will add
find_placeholder_info() calls in build_joinrel_tlist(), which seems
likely to make it more of an issue: a joinrel emitting lots of
PlaceHolderVars would incur O(N^2) cost, and we might be building
a lot of joinrels in complex queries. Hence, add an array that
can be indexed directly by phid to make the lookups constant-time.
Discussion: https://postgr.es/m/1405792.1660677844@sss.pgh.pa.us
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Commit fac1b470a thought we could check for set-returning functions
by testing only the top-level node in an expression tree. This is
wrong in itself, and to make matters worse it encouraged others
to make the same mistake, by exporting tlist.c's special-purpose
IS_SRF_CALL() as a widely-visible macro. I can't find any evidence
that anyone's taken the bait, but it was only a matter of time.
Use expression_returns_set() instead, and stuff the IS_SRF_CALL()
genie back in its bottle, this time with a warning label. I also
added a couple of cross-reference comments.
After a fair amount of fooling around, I've despaired of making
a robust test case that exposes the bug reliably, so no test case
here. (Note that the test case added by fac1b470a is itself
broken, in that it doesn't notice if you remove the code change.
The repro given by the bug submitter currently doesn't fail either
in v15 or HEAD, though I suspect that may indicate an unrelated bug.)
Per bug #17564 from Martijn van Oosterhout. Back-patch to v13,
as the faulty patch was.
Discussion: https://postgr.es/m/17564-c7472c2f90ef2da3@postgresql.org
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setrefs.c contains logic to discard no-op SubqueryScan nodes, that is,
ones that have no qual to check and copy the input targetlist unchanged.
(Formally it's not very nice to be applying such optimizations so late
in the planner, but there are practical reasons for it; mostly that we
can't unify relids between the subquery and the parent query until we
flatten the rangetable during setrefs.c.) This behavior falsifies our
previous cost estimates, since we would've charged cpu_tuple_cost per
row just to pass data through the node. Most of the time that's little
enough to not matter, but there are cases where this effect visibly
changes the plan compared to what you would've gotten with no
sub-select.
To improve the situation, make the callers of cost_subqueryscan tell
it whether they think the targetlist is trivial. cost_subqueryscan
already has the qual list, so it can check the other half of the
condition easily. It could make its own determination of tlist
triviality too, but doing so would be repetitive (for callers that
may call it several times) or unnecessarily expensive (for callers
that can determine this more cheaply than a general test would do).
This isn't a 100% solution, because createplan.c also does things
that can falsify any earlier estimate of whether the tlist is
trivial. However, it fixes nearly all cases in practice, if results
for the regression tests are anything to go by.
setrefs.c also contains logic to discard no-op Append and MergeAppend
nodes. We did have knowledge of that behavior at costing time, but
somebody failed to update it when a check on parallel-awareness was
added to the setrefs.c logic. Fix that while we're here.
These changes result in two minor changes in query plans shown in
our regression tests. Neither is relevant to the purposes of its
test case AFAICT.
Patch by me; thanks to Richard Guo for review.
Discussion: https://postgr.es/m/2581077.1651703520@sss.pgh.pa.us
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numGroups is unused since commit b5635948a; let's get rid of it.
XueJing Zhao, reviewed by Richard Guo
Discussion: https://postgr.es/m/DM6PR05MB64923CC8B63A2CAF3B2E5D47B7AD9@DM6PR05MB6492.namprd05.prod.outlook.com
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Run pgindent, pgperltidy, and reformat-dat-files.
I manually fixed a couple of comments that pgindent uglified.
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This follows in the footsteps of commit 2591ee8ec by removing one more
ill-advised shortcut from planning of GroupingFuncs. It's true that
we don't intend to execute the argument expression(s) at runtime, but
we still have to process any Vars appearing within them, or we risk
failure at setrefs.c time (or more fundamentally, in EXPLAIN trying
to print such an expression). Vars in upper plan nodes have to have
referents in the next plan level, whether we ever execute 'em or not.
Per bug #17479 from Michael J. Sullivan. Back-patch to all supported
branches.
Richard Guo
Discussion: https://postgr.es/m/17479-6260deceaf0ad304@postgresql.org
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Window functions such as row_number() always return a value higher than
the previously returned value for tuples in any given window partition.
Traditionally queries such as;
SELECT * FROM (
SELECT *, row_number() over (order by c) rn
FROM t
) t WHERE rn <= 10;
were executed fairly inefficiently. Neither the query planner nor the
executor knew that once rn made it to 11 that nothing further would match
the outer query's WHERE clause. It would blindly continue until all
tuples were exhausted from the subquery.
Here we implement means to make the above execute more efficiently.
This is done by way of adding a pg_proc.prosupport function to various of
the built-in window functions and adding supporting code to allow the
support function to inform the planner if the window function is
monotonically increasing, monotonically decreasing, both or neither. The
planner is then able to make use of that information and possibly allow
the executor to short-circuit execution by way of adding a "run condition"
to the WindowAgg to allow it to determine if some of its execution work
can be skipped.
This "run condition" is not like a normal filter. These run conditions
are only built using quals comparing values to monotonic window functions.
For monotonic increasing functions, quals making use of the btree
operators for <, <= and = can be used (assuming the window function column
is on the left). You can see here that once such a condition becomes false
that a monotonic increasing function could never make it subsequently true
again. For monotonically decreasing functions the >, >= and = btree
operators for the given type can be used for run conditions.
The best-case situation for this is when there is a single WindowAgg node
without a PARTITION BY clause. Here when the run condition becomes false
the WindowAgg node can simply return NULL. No more tuples will ever match
the run condition. It's a little more complex when there is a PARTITION
BY clause. In this case, we cannot return NULL as we must still process
other partitions. To speed this case up we pull tuples from the outer
plan to check if they're from the same partition and simply discard them
if they are. When we find a tuple belonging to another partition we start
processing as normal again until the run condition becomes false or we run
out of tuples to process.
When there are multiple WindowAgg nodes to evaluate then this complicates
the situation. For intermediate WindowAggs we must ensure we always
return all tuples to the calling node. Any filtering done could lead to
incorrect results in WindowAgg nodes above. For all intermediate nodes,
we can still save some work when the run condition becomes false. We've
no need to evaluate the WindowFuncs anymore. Other WindowAgg nodes cannot
reference the value of these and these tuples will not appear in the final
result anyway. The savings here are small in comparison to what can be
saved in the top-level WingowAgg, but still worthwhile.
Intermediate WindowAgg nodes never filter out tuples, but here we change
WindowAgg so that the top-level WindowAgg filters out tuples that don't
match the intermediate WindowAgg node's run condition. Such filters
appear in the "Filter" clause in EXPLAIN for the top-level WindowAgg node.
Here we add prosupport functions to allow the above to work for;
row_number(), rank(), dense_rank(), count(*) and count(expr). It appears
technically possible to do the same for min() and max(), however, it seems
unlikely to be useful enough, so that's not done here.
Bump catversion
Author: David Rowley
Reviewed-by: Andy Fan, Zhihong Yu
Discussion: https://postgr.es/m/CAApHDvqvp3At8++yF8ij06sdcoo1S_b2YoaT9D4Nf+MObzsrLQ@mail.gmail.com
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When evaluating a query with a multi-column GROUP BY clause using sort,
the cost may be heavily dependent on the order in which the keys are
compared when building the groups. Grouping does not imply any ordering,
so we're allowed to compare the keys in arbitrary order, and a Hash Agg
leverages this. But for Group Agg, we simply compared keys in the order
as specified in the query. This commit explores alternative ordering of
the keys, trying to find a cheaper one.
In principle, we might generate grouping paths for all permutations of
the keys, and leave the rest to the optimizer. But that might get very
expensive, so we try to pick only a couple interesting orderings based
on both local and global information.
When planning the grouping path, we explore statistics (number of
distinct values, cost of the comparison function) for the keys and
reorder them to minimize comparison costs. Intuitively, it may be better
to perform more expensive comparisons (for complex data types etc.)
last, because maybe the cheaper comparisons will be enough. Similarly,
the higher the cardinality of a key, the lower the probability we’ll
need to compare more keys. The patch generates and costs various
orderings, picking the cheapest ones.
The ordering of group keys may interact with other parts of the query,
some of which may not be known while planning the grouping. E.g. there
may be an explicit ORDER BY clause, or some other ordering-dependent
operation, higher up in the query, and using the same ordering may allow
using either incremental sort or even eliminate the sort entirely.
The patch generates orderings and picks those minimizing the comparison
cost (for various pathkeys), and then adds orderings that might be
useful for operations higher up in the plan (ORDER BY, etc.). Finally,
it always keeps the ordering specified in the query, on the assumption
the user might have additional insights.
This introduces a new GUC enable_group_by_reordering, so that the
optimization may be disabled if needed.
The original patch was proposed by Teodor Sigaev, and later improved and
reworked by Dmitry Dolgov. Reviews by a number of people, including me,
Andrey Lepikhov, Claudio Freire, Ibrar Ahmed and Zhihong Yu.
Author: Dmitry Dolgov, Teodor Sigaev, Tomas Vondra
Reviewed-by: Tomas Vondra, Andrey Lepikhov, Claudio Freire, Ibrar Ahmed, Zhihong Yu
Discussion: https://postgr.es/m/7c79e6a5-8597-74e8-0671-1c39d124c9d6%40sigaev.ru
Discussion: https://postgr.es/m/CA%2Bq6zcW_4o2NC0zutLkOJPsFt80megSpX_dVRo6GK9PC-Jx_Ag%40mail.gmail.com
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This introduces the SQL/JSON functions for querying JSON data using
jsonpath expressions. The functions are:
JSON_EXISTS()
JSON_QUERY()
JSON_VALUE()
All of these functions only operate on jsonb. The workaround for now is
to cast the argument to jsonb.
JSON_EXISTS() tests if the jsonpath expression applied to the jsonb
value yields any values. JSON_VALUE() must return a single value, and an
error occurs if it tries to return multiple values. JSON_QUERY() must
return a json object or array, and there are various WRAPPER options for
handling scalar or multi-value results. Both these functions have
options for handling EMPTY and ERROR conditions.
Nikita Glukhov
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zihong Yu,
Himanshu Upadhyaya, Daniel Gustafsson, Justin Pryzby.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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MERGE performs actions that modify rows in the target table using a
source table or query. MERGE provides a single SQL statement that can
conditionally INSERT/UPDATE/DELETE rows -- a task that would otherwise
require multiple PL statements. For example,
MERGE INTO target AS t
USING source AS s
ON t.tid = s.sid
WHEN MATCHED AND t.balance > s.delta THEN
UPDATE SET balance = t.balance - s.delta
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED AND s.delta > 0 THEN
INSERT VALUES (s.sid, s.delta)
WHEN NOT MATCHED THEN
DO NOTHING;
MERGE works with regular tables, partitioned tables and inheritance
hierarchies, including column and row security enforcement, as well as
support for row and statement triggers and transition tables therein.
MERGE is optimized for OLTP and is parameterizable, though also useful
for large scale ETL/ELT. MERGE is not intended to be used in preference
to existing single SQL commands for INSERT, UPDATE or DELETE since there
is some overhead. MERGE can be used from PL/pgSQL.
MERGE does not support targetting updatable views or foreign tables, and
RETURNING clauses are not allowed either. These limitations are likely
fixable with sufficient effort. Rewrite rules are also not supported,
but it's not clear that we'd want to support them.
Author: Pavan Deolasee <pavan.deolasee@gmail.com>
Author: Álvaro Herrera <alvherre@alvh.no-ip.org>
Author: Amit Langote <amitlangote09@gmail.com>
Author: Simon Riggs <simon.riggs@enterprisedb.com>
Reviewed-by: Peter Eisentraut <peter.eisentraut@enterprisedb.com>
Reviewed-by: Andres Freund <andres@anarazel.de> (earlier versions)
Reviewed-by: Peter Geoghegan <pg@bowt.ie> (earlier versions)
Reviewed-by: Robert Haas <robertmhaas@gmail.com> (earlier versions)
Reviewed-by: Japin Li <japinli@hotmail.com>
Reviewed-by: Justin Pryzby <pryzby@telsasoft.com>
Reviewed-by: Tomas Vondra <tomas.vondra@enterprisedb.com>
Reviewed-by: Zhihong Yu <zyu@yugabyte.com>
Discussion: https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.com
Discussion: https://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
Discussion: https://postgr.es/m/20201231134736.GA25392@alvherre.pgsql
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This patch introduces the SQL/JSON standard constructors for JSON:
JSON()
JSON_ARRAY()
JSON_ARRAYAGG()
JSON_OBJECT()
JSON_OBJECTAGG()
For the most part these functions provide facilities that mimic
existing json/jsonb functions. However, they also offer some useful
additional functionality. In addition to text input, the JSON() function
accepts bytea input, which it will decode and constuct a json value from.
The other functions provide useful options for handling duplicate keys
and null values.
This series of patches will be followed by a consolidated documentation
patch.
Nikita Glukhov
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zihong Yu,
Himanshu Upadhyaya, Daniel Gustafsson, Justin Pryzby.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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This introduces some of the building blocks used by the SQL/JSON
constructor and query functions. Specifically, it provides node
executor and grammar support for the FORMAT JSON [ENCODING foo]
clause, and values decorated with it, and for the RETURNING clause.
The following SQL/JSON patches will leverage these.
Nikita Glukhov (who probably deserves an award for perseverance).
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zihong Yu,
Himanshu Upadhyaya, Daniel Gustafsson, Justin Pryzby.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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flatten_join_alias_vars_mutator counted attnums, but didn't
do anything with the count (no doubt it did at one time).
Noted by buildfarm member seawasp.
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This reverts commit 865fe4d5df560a6f5353da652018ff876978ad2d.
This has caused issues with a significant number of buildfarm members
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This introduces some of the building blocks used by the SQL/JSON
constructor and query functions. Specifically, it provides node
executor and grammar support for the FORMAT JSON [ENCODING foo]
clause, and values decorated with it, and for the RETURNING clause.
The following SQL/JSON patches will leverage these.
Nikita Glukhov (who probably deserves an award for perseverance).
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup. Erik Rijkers, Zihong Yu and
Himanshu Upadhyaya.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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If a RowExpr is marked as returning a named composite type, we aren't
going to consult its colnames list; we'll use the attribute names
shown for the type in pg_attribute. Hence, skip storing that list,
to save a few nanoseconds when copying the expression tree around.
Discussion: https://postgr.es/m/2950001.1638729947@sss.pgh.pa.us
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There are three parallel ways to call parse/analyze: with fixed
parameters, with variable parameters, and by supplying your own parser
callback. Some of the involved functions were confusingly named and
made this API structure more confusing. This patch renames some
functions to make this clearer:
parse_analyze() -> parse_analyze_fixedparams()
pg_analyze_and_rewrite() -> pg_analyze_and_rewrite_fixedparams()
(Otherwise one might think this variant doesn't accept parameters, but
in fact all three ways accept parameters.)
pg_analyze_and_rewrite_params() -> pg_analyze_and_rewrite_withcb()
(Before, and also when considering pg_analyze_and_rewrite(), one might
think this is the only way to pass parameters. Moreover, the parser
callback doesn't necessarily need to parse only parameters, it's just
one of the things it could do.)
parse_fixed_parameters() -> setup_parse_fixed_parameters()
parse_variable_parameters() -> setup_parse_variable_parameters()
(These functions don't actually do any parsing, they just set up
callbacks to use during parsing later.)
This patch also adds some const decorations to the fixed-parameters
API, so the distinction from the variable-parameters API is more
clear.
Reviewed-by: Nathan Bossart <bossartn@amazon.com>
Discussion: https://www.postgresql.org/message-id/flat/c67ce276-52b4-0239-dc0e-39875bf81840@enterprisedb.com
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This fixes a set of issues that have accumulated over the past months
(or years) in various code areas. Most fixes are related to some recent
additions, as of the development of v15.
Author: Justin Pryzby
Discussion: https://postgr.es/m/20220124030001.GQ23027@telsasoft.com
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Add pg_statistic_ext_data.stxdinherit flag, so that for each extended
statistics definition we can store two versions of data - one for the
relation alone, one for the whole inheritance tree. This is analogous to
pg_statistic.stainherit, but we failed to include such flag in catalogs
for extended statistics, and we had to work around it (see commits
859b3003de, 36c4bc6e72 and 20b9fa308e).
This changes the relationship between the two catalogs storing extended
statistics objects (pg_statistic_ext and pg_statistic_ext_data). Until
now, there was a simple 1:1 mapping - for each definition there was one
pg_statistic_ext_data row, and this row was inserted while creating the
statistics (and then updated during ANALYZE). With the stxdinherit flag,
we don't know how many rows there will be (child relations may be added
after the statistics object is defined), so there may be up to two rows.
We could make CREATE STATISTICS to always create both rows, but that
seems wasteful - without partitioning we only need stxdinherit=false
rows, and declaratively partitioned tables need only stxdinherit=true.
So we no longer initialize pg_statistic_ext_data in CREATE STATISTICS,
and instead make that a responsibility of ANALYZE. Which is what we do
for regular statistics too.
Patch by me, with extensive improvements and fixes by Justin Pryzby.
Author: Tomas Vondra, Justin Pryzby
Reviewed-by: Tomas Vondra, Justin Pryzby
Discussion: https://postgr.es/m/20210923212624.GI831%40telsasoft.com
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Since this function is defined to accept pg_node_tree values, it could
get applied to any nodetree that can appear in a cataloged pg_node_tree
column. Some such cases can't be supported --- for example, its API
doesn't allow providing referents for more than one relation --- but
we should try to throw a user-facing error rather than an internal
error when encountering such a case.
In support of this, extend expression_tree_walker/mutator to be sure
they'll work on any such node tree (which basically means adding
support for relpartbound node types). That allows us to run pull_varnos
and check for the case of multiple relations before we start processing
the tree. The alternative of changing the low-level error thrown for an
out-of-range varno isn't appealing, because that could mask actual bugs
in other usages of ruleutils.
Per report from Justin Pryzby. This is basically cosmetic, so no
back-patch.
Discussion: https://postgr.es/m/20211219205422.GT17618@telsasoft.com
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Backpatch-through: 10
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Add more macros to group some RELKIND_* macros:
- RELKIND_HAS_PARTITIONS()
- RELKIND_HAS_TABLESPACE()
- RELKIND_HAS_TABLE_AM()
Reviewed-by: Michael Paquier <michael@paquier.xyz>
Reviewed-by: Alvaro Herrera <alvherre@alvh.no-ip.org>
Discussion: https://www.postgresql.org/message-id/flat/a574c8f1-9c84-93ad-a9e5-65233d6fc00f%40enterprisedb.com
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It's possible that a subplan below a Memoize node contains a parameter
from above the Memoize node. If this parameter changes then cache entries
may become out-dated due to the new parameter value.
Previously Memoize was mistakenly not aware of this. We fix this here by
flushing the cache whenever a parameter that's not part of the cache
key changes.
Bug: #17213
Reported by: Elvis Pranskevichus
Author: David Rowley
Discussion: https://postgr.es/m/17213-988ed34b225a2862@postgresql.org
Backpatch-through: 14, where Memoize was added
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This reverts commit 1050048a315790a505465bfcceb26eaf8dbc7e2e.
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It's possible that a subplan below a Memoize node contains a parameter
from above the Memoize node. If this parameter changes then cache entries
may become out-dated due to the new parameter value.
Previously Memoize was mistakenly not aware of this. We fix this here by
flushing the cache whenever a parameter that's not part of the cache
key changes.
Bug: #17213
Reported by: Elvis Pranskevichus
Author: David Rowley
Discussion: https://postgr.es/m/17213-988ed34b225a2862@postgresql.org
Backpatch-through: 14, where Memoize was added
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Memoize would always use the hash equality operator for the cache key
types to determine if the current set of parameters were the same as some
previously cached set. Certain types such as floating points where -0.0
and +0.0 differ in their binary representation but are classed as equal by
the hash equality operator may cause problems as unless the join uses the
same operator it's possible that whichever join operator is being used
would be able to distinguish the two values. In which case we may
accidentally return in the incorrect rows out of the cache.
To fix this here we add a binary mode to Memoize to allow it to the
current set of parameters to previously cached values by comparing
bit-by-bit rather than logically using the hash equality operator. This
binary mode is always used for LATERAL joins and it's used for normal
joins when any of the join operators are not hashable.
Reported-by: Tom Lane
Author: David Rowley
Discussion: https://postgr.es/m/3004308.1632952496@sss.pgh.pa.us
Backpatch-through: 14, where Memoize was added
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In v14, because we don't have a field in RestrictInfo to cache both the
left and right type's hash equality operator, we just restrict the scope
of Memoize to only when the left and right types of a RestrictInfo are the
same.
In master we add another field to RestrictInfo and cache both hash
equality operators.
Reported-by: Jaime Casanova
Author: David Rowley
Discussion: https://postgr.es/m/20210929185544.GB24346%40ahch-to
Backpatch-through: 14
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As in commits 6301c3ada and e9d9ba2a4, avoid doing repetitive
list_delete_first() operations, since that would be expensive when
there are many files waiting to be unlinked. This is a slightly
larger change than in those cases. We have to keep the list state
valid for calls to AbsorbSyncRequests(), so it's necessary to invent a
"canceled" field instead of immediately deleting PendingUnlinkEntry
entries. Also, because we might not be able to process all the
entries, we need a new list primitive list_delete_first_n().
list_delete_first_n() is almost list_copy_tail(), but it modifies the
input List instead of making a new copy. I found a couple of existing
uses of the latter that could profitably use the new function. (There
might be more, but the other callers look like they probably shouldn't
overwrite the input List.)
As before, back-patch to v13.
Discussion: https://postgr.es/m/CD2F0E7F-9822-45EC-A411-AE56F14DEA9F@amazon.com
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Several mistakes have piled in the code comments over the time,
including incorrect grammar, function names and simple typos. This
commit takes care of a portion of these.
No backpatch is done as this is only cosmetic.
Author: Justin Pryzby
Discussion: https://postgr.es/m/20210924215827.GS831@telsasoft.com
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Commit 55dc86eca changed pull_varnos to use (if possible) the associated
ph_eval_at for a PlaceHolderVar. I missed a fine point though: we might
be looking at a PHV in the quals or tlist of a child appendrel, in which
case we need to compute a ph_eval_at value that's been translated in the
same way that the PHV itself has been (cf. adjust_appendrel_attrs).
Fortunately, enough info is available in the PlaceHolderInfo to make
such translation possible without additional outside data, so we don't
need another round of uglification of planner APIs. This is a little
bit complicated, but since it's a hard-to-hit corner case, I'm not much
worried about adding cycles here.
Per report from Jaime Casanova. Back-patch to v12, like the previous
commit.
Discussion: https://postgr.es/m/20210915230959.GB17635@ahch-to
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All the code paths simplified here were already using a boolean or used
an expression that led to zero or one, making the extra bits
unnecessary.
Author: Justin Pryzby
Reviewed-by: Tom Lane, Michael Paquier, Peter Smith
Discussion: https://postgr.es/m/20210428182936.GE27406@telsasoft.com
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When starting to use a query parsetree loaded from the catalogs,
we must begin by applying AcquireRewriteLocks(), to obtain the same
relation locks that the parser would have gotten if the query were
entered interactively, and to do some other cleanup such as dealing
with later-dropped columns. New-style SQL functions are just as
subject to this rule as other stored parsetrees; however, of the
places dealing with such functions, only init_sql_fcache had gotten
the memo. In particular, if we successfully inlined a new-style
set-returning SQL function that contained any relation references,
we'd either get an assertion failure or attempt to use those
relation(s) sans locks.
I also added AcquireRewriteLocks calls to fmgr_sql_validator and
print_function_sqlbody. Desultory experiments didn't demonstrate any
failures in those, but I suspect that I just didn't try hard enough.
Certainly we don't expect nearby code paths to operate without locks.
On the same logic of it-ought-to-have-the-same-effects-as-the-old-code,
call pg_rewrite_query() in fmgr_sql_validator, too. It's possible
that neither code path there needs to bother with rewriting, but
doing the analysis to prove that is beyond my goals for today.
Per bug #17161 from Alexander Lakhin.
Discussion: https://postgr.es/m/17161-048a1cdff8422800@postgresql.org
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This makes the structure of all JoinPath-derived nodes the same,
independent of whether they have additional fields.
Discussion: https://www.postgresql.org/message-id/flat/c1097590-a6a4-486a-64b1-e1f9cc0533ce@enterprisedb.com
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For partitioned tables with large numbers of partitions where queries are
able to prune all but a very small number of partitions, the time spent in
the planner looping over RelOptInfo.part_rels checking for non-NULL
RelOptInfos could become a large portion of the overall planning time.
Here we add a Bitmapset that records the non-pruned partitions. This
allows us to more efficiently skip the pruned partitions by looping over
the Bitmapset.
This will cause a very slight slow down in cases where no or not many
partitions could be pruned, however, those cases are already slow to plan
anyway and the overhead of looping over the Bitmapset would be
unmeasurable when compared with the other tasks such as path creation for
a large number of partitions.
Reviewed-by: Amit Langote, Zhihong Yu
Discussion: https://postgr.es/m/CAApHDvqnPx6JnUuPwaf5ao38zczrAb9mxt9gj4U1EKFfd4AqLA@mail.gmail.com
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The point of introducing the hash_mem_multiplier GUC was to let users
reproduce the old behavior of hash aggregation, i.e. that it could use
more than work_mem at need. However, the implementation failed to get
the job done on Win64, where work_mem is clamped to 2GB to protect
various places that calculate memory sizes using "long int". As
written, the same clamp was applied to hash_mem. This resulted in
severe performance regressions for queries requiring a bit more than
2GB for hash aggregation, as they now spill to disk and there's no
way to stop that.
Getting rid of the work_mem restriction seems like a good idea, but
it's a big job and could not conceivably be back-patched. However,
there's only a fairly small number of places that are concerned with
the hash_mem value, and it turns out to be possible to remove the
restriction there without too much code churn or any ABI breaks.
So, let's do that for now to fix the regression, and leave the
larger task for another day.
This patch does introduce a bit more infrastructure that should help
with the larger task, namely pg_bitutils.h support for working with
size_t values.
Per gripe from Laurent Hasson. Back-patch to v13 where the
behavior change came in.
Discussion: https://postgr.es/m/997817.1627074924@sss.pgh.pa.us
Discussion: https://postgr.es/m/MN2PR15MB25601E80A9B6D1BA6F592B1985E39@MN2PR15MB2560.namprd15.prod.outlook.com
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Instead of castNode(…, lfoo(…))
Author: Dagfinn Ilmari Mannsåker <ilmari@ilmari.org>
Discussion: https://www.postgresql.org/message-id/flat/87eecahraj.fsf@wibble.ilmari.org
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This allows Param substitution to produce just the same result
as writing a constant value literally would have done. While
it hardly matters so far as the current core code is concerned,
extensions might take more interest in node location fields.
Julien Rouhaud
Discussion: https://postgr.es/m/20170311220932.GJ15188@nol.local
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"Result Cache" was never a great name for this node, but nobody managed
to come up with another name that anyone liked enough. That was until
David Johnston mentioned "Node Memoization", which Tom Lane revised to
just "Memoize". People seem to like "Memoize", so let's do the rename.
Reviewed-by: Justin Pryzby
Discussion: https://postgr.es/m/20210708165145.GG1176@momjian.us
Backpatch-through: 14, where Result Cache was introduced
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Similar to 50e17ad28, which allowed hash tables to be used for IN clauses
with a set of constants, here we add the same feature for NOT IN clauses.
NOT IN evaluates the same as: WHERE a <> v1 AND a <> v2 AND a <> v3.
Obviously, if we're using a hash table we must be exactly equivalent to
that and return the same result taking into account that either side of
the condition could contain a NULL. This requires a little bit of
special handling to make work with the hash table version.
When processing NOT IN, the ScalarArrayOpExpr's operator will be the <>
operator. To be able to build and lookup a hash table we must use the
<>'s negator operator. The planner checks if that exists and is hashable
and sets the relevant fields in ScalarArrayOpExpr to instruct the executor
to use hashing.
Author: David Rowley, James Coleman
Reviewed-by: James Coleman, Zhihong Yu
Discussion: https://postgr.es/m/CAApHDvoF1mum_FRk6D621edcB6KSHBi2+GAgWmioj5AhOu2vwQ@mail.gmail.com
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Commit 2453ea142 redefined pg_proc.proargtypes to include the types of
OUT parameters, for procedures only. While that had some advantages
for implementing the SQL-spec behavior of DROP PROCEDURE, it was pretty
disastrous from a number of other perspectives. Notably, since the
primary key of pg_proc is name + proargtypes, this made it possible to
have multiple procedures with identical names + input arguments and
differing output argument types. That would make it impossible to call
any one of the procedures by writing just NULL (or "?", or any other
data-type-free notation) for the output argument(s). The change also
seems likely to cause grave confusion for client applications that
examine pg_proc and expect the traditional definition of proargtypes.
Hence, revert the definition of proargtypes to what it was, and
undo a number of complications that had been added to support that.
To support the SQL-spec behavior of DROP PROCEDURE, when there are
no argmode markers in the command's parameter list, we perform the
lookup both ways (that is, matching against both proargtypes and
proallargtypes), succeeding if we get just one unique match.
In principle this could result in ambiguous-function failures
that would not happen when using only one of the two rules.
However, overloading of procedure names is thought to be a pretty
rare usage, so this shouldn't cause many problems in practice.
Postgres-specific code such as pg_dump can defend against any
possibility of such failures by being careful to specify argmodes
for all procedure arguments.
This also fixes a few other bugs in the area of CALL statements
with named parameters, and improves the documentation a little.
catversion bump forced because the representation of procedures
with OUT arguments changes.
Discussion: https://postgr.es/m/3742981.1621533210@sss.pgh.pa.us
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