Preprocessing of the HAVING clause will reduce havingQual to NIL
if the clause is constant-TRUE. This is one case where that
convention is rather unfortunate, because "HAVING TRUE" is not at all
the same as not having any HAVING clause at all. (Per the SQL spec,
it still forces the query to be grouped.) The planner deals with this
by having a boolean hasHavingQual that records whether havingQual was
originally nonempty; places that just want to check whether HAVING
was specified are supposed to consult that.
I found three places that got that wrong. Fortunately, these could
only affect cost estimates not correctness. It'd be hard even
to demonstrate the errors; for example, the one in allpaths.c would
only matter in a query that has HAVING TRUE but no GROUP BY and no
aggregates, which would require a completely variable-free SELECT
list, making the case probably of only academic interest. Hence,
while these are worth fixing before someone copies the incorrect
coding somewhere more critical, they don't seem worth back-patching.
I didn't bother trying to devise regression tests, either.
Discussion: https://postgr.es/m/2503888.1666042643@sss.pgh.pa.us
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
While directly targetting a foreign table with MERGE was already
expressly forbidden, we failed to catch the case of a partitioned table
that has a foreign table as a partition; and the result if you try is an
incomprehensible error. Fix that by adding a specific check.
Backpatch to 15.
Reported-by: Tatsuhiro Nakamori <bt22nakamorit@oss.nttdata.com>
Discussion: https://postgr.es/m/bt22nakamorit@oss.nttdata.com
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
This reverts commit db0d67db24 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
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
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
The header comment for get_cheapest_group_keys_order() claimed that the
output arguments were set to a newly allocated list which may be freed by
the calling function, however, this was not always true as the function
would simply leave these arguments untouched in some cases.
This tripped me up when working on 1349d2790 as I mistakenly assumed I
could perform a list_concat with the output parameters. That turned out
bad due to list_concat modifying the original input lists.
In passing, make it more clear that the number of distinct values is
important to reduce tiebreaks during sorts. Also, explain what the
n_preordered parameter means.
Backpatch-through: 15, where get_cheapest_group_keys_order was introduced.
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.
The planner has to special-case indexes on boolean columns, because
what we need for an indexscan on such a column is a qual of the shape
of "boolvar = pseudoconstant". For plain bool constants, previous
simplification will have reduced this to "boolvar" or "NOT boolvar",
and we have to reverse that if we want to make an indexqual. There is
existing code to do so, but it only fires when the index's opfamily
is BOOL_BTREE_FAM_OID or BOOL_HASH_FAM_OID. Thus extension AMs, or
extension opclasses such as contrib/btree_gin, are out in the cold.
The reason for hard-wiring the set of relevant opfamilies was mostly
to avoid a catalog lookup in a hot code path. We can improve matters
while not taking much of a performance hit by relying on the
hard-wired set when the opfamily OID is visibly built-in, and only
checking the catalogs when dealing with an extension opfamily.
While here, rename IsBooleanOpfamily to IsBuiltinBooleanOpfamily
to remind future users of that macro of its limitations. At some
point we might want to make indxpath.c's improved version of the
test globally accessible, but it's not presently needed elsewhere.
Zongliang Quan and Tom Lane
Discussion: https://postgr.es/m/f293b91d-1d46-d386-b6bb-4b06ff5c667b@yeah.net
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
In a similar effort to f01592f91, here we're targetting fixing the
warnings where we've deemed the shadowing variable to serve a close enough
purpose to the shadowed variable just to reuse the shadowed version and
not declare the shadowing variable at all.
By my count, this takes the warning count from 106 down to 71.
Author: Justin Pryzby
Discussion: https://postgr.es/m/20220825020839.GT2342@telsasoft.com
These should have been included in 421892a19 as these shadowed variable
warnings can also be fixed by adjusting the scope of the shadowed variable
to put the declaration for it in an inner scope.
This is part of the same effort as f01592f91.
By my count, this takes the warning count from 114 down to 106.
Author: David Rowley and Justin Pryzby
Discussion: https://postgr.es/m/CAApHDvrwLGBP%2BYw9vriayyf%3DXR4uPWP5jr6cQhP9au_kaDUhbA%40mail.gmail.com
In a similar effort to f01592f91, here we're targetting fixing the
warnings that -Wshadow=compatible-local produces that we can fix by moving
a variable to an inner scope to stop that variable from being shadowed by
another variable declared somewhere later in the function.
All of the warnings being fixed here are changing the scope of variables
which are being used as an iterator for a "for" loop. In each instance,
the fix happens to be changing the for loop to use the C99 type
initialization. Much of this code likely pre-dates our use of C99.
Reducing the scope of the outer scoped variable seems like the safest way
to fix these. Renaming seems more likely to risk patches using the wrong
variable. Reducing the scope is more likely to result in a compilation
failure after applying some future patch rather than introducing bugs with
it.
By my count, this takes the warning count from 129 down to 114.
Author: Justin Pryzby
Discussion: https://postgr.es/m/CAApHDvrwLGBP%2BYw9vriayyf%3DXR4uPWP5jr6cQhP9au_kaDUhbA%40mail.gmail.com
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
1349d2790 changed things to make the planner request that the
query_pathkeys contain pathkeys for any ORDER BY / DISTINCT aggregates.
Some code added prior to that commit in db0d67db2 made it so the order
that the pathkeys appear in the group_pathkeys could be changed so that
the GROUP BY could be executed in a more optimal order which minimized
sort comparisons. 1349d2790 had to make sure that the pathkeys for any
ORDER BY / DISTINCT aggregates remained at the end of the groupby_pathkeys
and wasn't reordered, so some code was added to
add_paths_to_grouping_rel() to first strip off any pathkeys belonging to
ORDER BY / DISTINCT aggregates before passing to the function to optimize
the order of the group_pathkeys.
It seems I dropped the ball in 1349d2790 and mistakenly used the untouched
PlannerInfo.group_pathkeys to pass to get_useful_group_keys_orderings()
instead of the version that had the aggregate pathkeys removed. It was
only the code path that was handling creating paths for
partially_grouped_rel which made this mistake. In practice, we'll never
have any extra pathkeys to strip off when processing
partially_grouped_rel as that's only used when considering partial
paths, which we never do when there are ORDER BY / DISTINCT aggregates.
So this is just a hypothetical bug, not a live bug. We already have the
correct pathkeys determined, so it's of no extra cost to pass the
correct variable.
Reported-by: Justin Pryzby
Discussion: https://postgr.es/m/20220817015755.GB26426@telsasoft.com
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
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
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
The standard way to check for list emptiness is to compare the
List pointer to NIL; our list code goes out of its way to ensure
that that is the only representation of an empty list. (An
acceptable alternative is a plain boolean test for non-null
pointer, but explicit mention of NIL is usually preferable.)
Various places didn't get that memo and expressed the condition
with list_length(), which might not be so bad except that there
were such a variety of ways to check it exactly: equal to zero,
less than or equal to zero, less than one, yadda yadda. In the
name of code readability, let's standardize all those spellings
as "list == NIL" or "list != NIL". (There's probably some
microscopic efficiency gain too, though few of these look to be
at all performance-critical.)
A very small number of cases were left as-is because they seemed
more consistent with other adjacent list_length tests that way.
Peter Smith, with bikeshedding from a number of us
Discussion: https://postgr.es/m/CAHut+PtQYe+ENX5KrONMfugf0q6NHg4hR5dAhqEXEc2eefFeig@mail.gmail.com
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
ORDER BY / DISTINCT aggreagtes have, since implemented in Postgres, been
executed by always performing a sort in nodeAgg.c to sort the tuples in
the current group into the correct order before calling the transition
function on the sorted tuples. This was not great as often there might be
an index that could have provided pre-sorted input and allowed the
transition functions to be called as the rows come in, rather than having
to store them in a tuplestore in order to sort them once all the tuples
for the group have arrived.
Here we change the planner so it requests a path with a sort order which
supports the most amount of ORDER BY / DISTINCT aggregate functions and
add new code to the executor to allow it to support the processing of
ORDER BY / DISTINCT aggregates where the tuples are already sorted in the
correct order.
Since there can be many ORDER BY / DISTINCT aggregates in any given query
level, it's very possible that we can't find an order that suits all of
these aggregates. The sort order that the planner chooses is simply the
one that suits the most aggregate functions. We take the most strictly
sorted variation of each order and see how many aggregate functions can
use that, then we try again with the order of the remaining aggregates to
see if another order would suit more aggregate functions. For example:
SELECT agg(a ORDER BY a),agg2(a ORDER BY a,b) ...
would request the sort order to be {a, b} because {a} is a subset of the
sort order of {a,b}, but;
SELECT agg(a ORDER BY a),agg2(a ORDER BY c) ...
would just pick a plan ordered by {a} (we give precedence to aggregates
which are earlier in the targetlist).
SELECT agg(a ORDER BY a),agg2(a ORDER BY b),agg3(a ORDER BY b) ...
would choose to order by {b} since two aggregates suit that vs just one
that requires input ordered by {a}.
Author: David Rowley
Reviewed-by: Ronan Dunklau, James Coleman, Ranier Vilela, Richard Guo, Tom Lane
Discussion: https://postgr.es/m/CAApHDvpHzfo92%3DR4W0%2BxVua3BUYCKMckWAmo-2t_KiXN-wYH%3Dw%40mail.gmail.com
The select_outer_pathkeys_for_merge function made an attempt to build the
merge join pathkeys in the same order as query_pathkeys. This was done as
it may have led to no sort being required for an ORDER BY or GROUP BY
clause in the upper planner. However, this restriction seems overly
strict as it required that we match the query_pathkeys entirely or we
don't bother putting the merge join pathkeys in that order.
Here we relax this rule so that we use a prefix of the query_pathkeys
providing that prefix matches all of the join quals. This may provide the
upper planner with partially sorted input which will allow the use of
incremental sorts instead of full sorts.
Author: David Rowley
Reviewed-by: Richard Guo
Discussion: https://postgr.es/m/CAApHDvrtZu0PHVfDPFM4Yx3jNR2Wuwosv+T2zqa7LrhhBr2rRg@mail.gmail.com
Two callers of generate_useful_gather_paths were testing the wrong
thing when deciding whether to call that function: they checked for
being at the top of the current join subproblem, rather than being at
the actual top join. This'd result in failing to construct parallel
paths for a sub-join for which they might be useful.
While set_rel_pathlist() isn't actively broken, it seems best to
make its identical-in-intention test for this be like the other two.
This has been wrong all along, but given the lack of field complaints
I'm hesitant to back-patch into stable branches; we usually prefer
to avoid non-bug-fix changes in plan choices in minor releases.
It seems not too late for v15 though.
Richard Guo, reviewed by Antonin Houska and Tom Lane
Discussion: https://postgr.es/m/CAMbWs4-mH8Zf87-w+3P2J=nJB+5OyicO28ia9q_9o=Lamf_VHg@mail.gmail.com
Commit 4f658dc8 provided the traditional BSD fls() function in
src/port/fls.c so it could be used in several places. Later we added a
bunch of similar facilities in pg_bitutils.h, based on compiler
builtins that map to hardware instructions. It's a bit confusing to
have both 1-based and 0-based variants of this operation in use in
different parts of the tree, and neither is blessed by a standard.
Let's drop fls.c and the configure probe, and reuse the newer code.
Reviewed-by: David Rowley <dgrowleyml@gmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://postgr.es/m/CA%2BhUKG%2B7dSX1XF8yFGmYk-%3D48dbjH2kmzZj16XvhbrWP-9BzRg%40mail.gmail.com
This is mostly just to get outfuncs.c support for them, so that
the agginfos and aggtransinfos lists can be dumped when dumping
the contents of PlannerInfo.
While here, improve some related comments; notably, clean up
obsolete comments left over from when preprocess_minmax_aggregates
had to make its own scan of the query tree.
Discussion: https://postgr.es/m/742479.1658160504@sss.pgh.pa.us
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
This replaces all MemSet() calls with struct initialization where that
is easily and obviously possible. (For example, some cases have to
worry about padding bits, so I left those.)
(The same could be done with appropriate memset() calls, but this
patch is part of an effort to phase out MemSet(), so it doesn't touch
memset() calls.)
Reviewed-by: Ranier Vilela <ranier.vf@gmail.com>
Reviewed-by: Alvaro Herrera <alvherre@alvh.no-ip.org>
Discussion: https://www.postgresql.org/message-id/9847b13c-b785-f4e2-75c3-12ec77a3b05c@enterprisedb.com
No members of the buildfarm are using this version of Visual Studio,
resulting in all the code cleaned up here as being mostly dead, and
VS2017 is the oldest version still supported.
More versions could be cut, but the gain would be minimal, while
removing only VS2013 has the advantage to remove from the core code all
the dependencies on the value defined by _MSC_VER, where compatibility
tweaks have accumulated across the years mostly around locales and
strtof(), so that's a nice isolated cleanup.
Note that this commit additionally allows a revert of 3154e16. The
versions of Visual Studio now supported range from 2015 to 2022.
Author: Michael Paquier
Reviewed-by: Juan José Santamaría Flecha, Tom Lane, Thomas Munro, Justin
Pryzby
Discussion: https://postgr.es/m/YoH2IMtxcS3ncWn+@paquier.xyz
Truncating off the end of a freshly copied List is not a very efficient
way of copying the first N elements of a List.
In many of the cases that are updated here, the pattern was only being
used to remove the final element of a List. That's about the best case
for it, but there were many instances where the truncate trimming the List
down much further.
4cc832f94 added list_copy_head(), so let's use it in cases where it's
useful.
Author: David Rowley
Discussion: https://postgr.es/m/1986787.1657666922%40sss.pgh.pa.us
There are a few things that we could do a little better within
get_cheapest_group_keys_order():
1. We should be using list_free() rather than pfree() on a List.
2. We should use for_each_from() instead of manually coding a for loop to
skip the first n elements of a List
3. list_truncate(list_copy(...), n) is not a great way to copy the first n
elements of a list. Let's invent list_copy_head() for that. That way we
don't need to copy the entire list just to truncate it directly
afterwards.
4. We can simplify finding the cheapest cost by setting the cheapest cost
variable to DBL_MAX. That allows us to skip special-casing the initial
iteration of the loop.
Author: David Rowley
Discussion: https://postgr.es/m/CAApHDvrGyL3ft8waEkncG9y5HDMu5TFFJB1paoTC8zi9YK97Nw@mail.gmail.com
Backpatch-through: 15, where get_cheapest_group_keys_order was added.
This function can be called from mark_async_capable_plan(), a helper
function for create_append_plan(), before set_subqueryscan_references(),
to determine the triviality of a SubqueryScan that is a child of an
Append plan node, which is done before doing finalize_plan() on the
SubqueryScan (if necessary) and set_plan_references() on the subplan,
unlike when called from set_subqueryscan_references(). The reason why
this is safe wouldn't be that obvious, so add comments explaining this.
Follow-up for commit c2bb02bc2.
Reviewed by Zhihong Yu.
Discussion: https://postgr.es/m/CAPmGK17%2BGiJBthC6va7%2B9n6t75e-M1N0U18YB2G1B%2BE5OdrNTA%40mail.gmail.com
9d9c02ccd added code to allow the executor to take shortcuts when quals
on monotonic window functions guaranteed that once the qual became false
it could never become true again. When possible, baserestrictinfo quals
are converted to become these quals, which we call run conditions.
Unfortunately, in 9d9c02ccd, I forgot to update
remove_unused_subquery_outputs to teach it about these run conditions.
This could cause a WindowFunc column which was unused in the target list
but referenced by an upper-level WHERE clause to be removed from the
subquery when the qual in the WHERE clause was converted into a window run
condition. Because of this, the entire WindowClause would be removed from
the query resulting in additional rows making it into the resultset when
they should have been filtered out by the WHERE clause.
Here we fix this by recording which target list items in the subquery have
run conditions. That gets passed along to remove_unused_subquery_outputs
to tell it not to remove these items from the target list.
Bug: #17495
Reported-by: Jeremy Evans
Reviewed-by: Richard Guo
Discussion: https://postgr.es/m/17495-7ffe2fa0b261b9fa@postgresql.org
Several places in the planner tried to clamp a double value to fit
in a "long" by doing
(long) Min(x, (double) LONG_MAX);
This is subtly incorrect, because it casts LONG_MAX to double and
potentially back again. If long is 64 bits then the double value
is inexact, and the platform might round it up to LONG_MAX+1
resulting in an overflow and an undesirably negative output.
While it's not hard to rewrite the expression into a safe form,
let's put it into a common function to reduce the risk of someone
doing it wrong in future.
In principle this is a bug fix, but since the problem could only
manifest with group count estimates exceeding 2^63, it seems unlikely
that anyone has actually hit this or will do so anytime soon. We're
fixing it mainly to satisfy fuzzer-type tools. That being the case,
a HEAD-only fix seems sufficient.
Andrey Lepikhov
Discussion: https://postgr.es/m/ebbc2efb-7ef9-bf2f-1ada-d6ec48f70e58@postgrespro.ru
In order to estimate the cache hit ratio of a Memoize node, one of the
inputs we require is the estimated number of times the Memoize node will
be rescanned. The higher this number, the large the cache hit ratio is
likely to become. Unfortunately, the value being passed as the number of
"calls" to the Memoize was incorrectly using the Nested Loop's
outer_path->parent->rows instead of outer_path->rows. This failed to
account for the fact that the outer_path might be parameterized by some
upper-level Nested Loop.
This problem could lead to Memoize plans appearing more favorable than
they might actually be. It could also lead to extended executor startup
times when work_mem values were large due to the planner setting overly
large MemoizePath->est_entries resulting in the Memoize hash table being
initially made much larger than might be required.
Fix this simply by passing outer_path->rows rather than
outer_path->parent->rows. Also, adjust the expected regression test
output for a plan change.
Reported-by: Pavel Stehule
Author: David Rowley
Discussion: https://postgr.es/m/CAFj8pRAMp%3DQsMi6sPQJ4W3hczoFJRvyXHJV3AZAZaMyTVM312Q%40mail.gmail.com
Backpatch-through: 14, where Memoize was introduced
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
SubqueryScan was always getting labeled with a rowcount estimate
appropriate for non-parallel cases. However, nodes that are
underneath a Gather should be treated as processing only one
worker's share of the rows, whether the particular node is explicitly
parallel-aware or not. Most non-scan-level node types get this
right automatically because they base their rowcount estimate on
that of their input sub-Path(s). But SubqueryScan didn't do that,
instead using the whole-relation rowcount estimate as if it were
a non-parallel-aware scan node. If there is a parallel-aware node
below the SubqueryScan, this is wrong, and it results in inflating
the cost estimates for nodes above the SubqueryScan, which can cause
us to not choose a parallel plan, or choose a silly one --- as indeed
is visible in the one regression test whose results change with this
patch. (Although that plan tree appears to contain no SubqueryScans,
there were some in it before setrefs.c deleted them.)
To fix, use path->subpath->rows not baserel->tuples as the number
of input tuples we'll process. This requires estimating the quals'
selectivity afresh, which is slightly annoying; but it shouldn't
really add much cost thanks to the caching done in RestrictInfo.
This is pretty clearly a bug fix, but I'll refrain from back-patching
as people might not appreciate plan choices changing in stable branches.
The fact that it took us this long to identify the bug suggests that
it's not a major problem.
Per report from bucoo, though this is not his proposed patch.
Discussion: https://postgr.es/m/202204121457159307248@sohu.com
mark_async_capable_plan(), which is called from create_append_plan() to
determine whether subplans are async-capable, failed to take into
account that the given subplan created from a given subpath might
include a gating Result node if the subpath is a SubqueryScanPath or
ForeignPath, causing a segmentation fault there when the subplan created
from a SubqueryScanPath includes the Result node, or causing
ExecAsyncRequest() to throw an error about an unrecognized node type
when the subplan created from a ForeignPath includes the Result node,
because in the latter case the Result node was unintentionally
considered as async-capable, but we don't currently support executing
Result nodes asynchronously. Fix by modifying mark_async_capable_plan()
to disable asynchronous execution in such cases. Also, adjust code in
the ProjectionPath case in mark_async_capable_plan(), for consistency
with other cases, and adjust/improve comments there.
is_async_capable_path() added in commit 27e1f1456, which was rewritten
to mark_async_capable_plan() in a later commit, has the same issue,
causing the error at execution mentioned above, so back-patch to v14
where the aforesaid commit went in.
Per report from Justin Pryzby.
Etsuro Fujita, reviewed by Zhihong Yu and Justin Pryzby.
Discussion: https://postgr.es/m/20220408124338.GK24419%40telsasoft.com
inline_cte() expected to find exactly as many references to the
target CTE as its cterefcount indicates. While that should be
accurate for the tree as emitted by the parser, there are some
optimizations that occur upstream of here that could falsify it,
notably removal of unused subquery output expressions.
Trying to make the accounting 100% accurate seems expensive and
doomed to future breakage. It's not really worth it, because
all this code is protecting is downstream assumptions that every
referenced CTE has a plan. Let's convert those assertions to
regular test-and-elog just in case there's some actual problem,
and then drop the failing assertion.
Per report from Tomas Vondra (thanks also to Richard Guo for
analysis). Back-patch to v12 where the faulty code came in.
Discussion: https://postgr.es/m/29196a1e-ed47-c7ca-9be2-b1c636816183@enterprisedb.com
We were setting MERGE source subplan's targetlist by expanding the
individual attributes of the source relation completely, early in the
parse analysis phase. This failed to work when the condition of an
action included a whole-row reference, causing setrefs.c to error out
with
ERROR: variable not found in subplan target lists
because at that point there is nothing to resolve the whole-row
reference with. We can fix this by having preprocess_targetlist expand
the source targetlist for Vars required from the source rel by all
actions. Moreover, by using this expansion mechanism we can do away
with the targetlist expansion in transformMergeStmt, which is good
because then we no longer pull in columns that aren't needed for
anything.
Add a test case for the problem.
While at it, remove some redundant code in preprocess_targetlist():
MERGE was doing separately what is already being done for UPDATE/DELETE,
so we can just rely on the latter and remove the former. (The handling
of inherited rels was different for MERGE, but that was a no-longer-
necessary hack.)
Fix outdated, related comments for fix_join_expr also.
Author: Richard Guo <guofenglinux@gmail.com>
Author: Álvaro Herrera <alvherre@alvh.no-ip.org>
Reported-by: Joe Wildish <joe@lateraljoin.com>
Discussion: https://postgr.es/m/fab3b90a-914d-46a9-beb0-df011ee39ee5@www.fastmail.com
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
In commit 27e1f1456, create_append_plan() only allowed the subplan
created from a given subpath to be executed asynchronously when it was
an async-capable ForeignPath. To extend coverage, this patch handles
cases when the given subpath includes some other Path types as well that
can be omitted in the plan processing, such as a ProjectionPath directly
atop an async-capable ForeignPath, allowing asynchronous execution in
partitioned-scan/partitioned-join queries with non-Var tlist expressions
and more UNION queries.
Andrey Lepikhov and Etsuro Fujita, reviewed by Alexander Pyhalov and
Zhihong Yu.
Discussion: https://postgr.es/m/659c37a8-3e71-0ff2-394c-f04428c76f08%40postgrespro.ru
postgres_fdw would push ORDER BY clauses to the remote side without
verifying that the sort operator is safe to ship. Moreover, it failed
to print a suitable USING clause if the sort operator isn't default
for the sort expression's type. The net result of this is that the
remote sort might not have anywhere near the semantics we expect,
which'd be disastrous for locally-performed merge joins in particular.
We addressed similar issues in the context of ORDER BY within an
aggregate function call in commit 7012b132d, but failed to notice
that query-level ORDER BY was broken. Thus, much of the necessary
logic already existed, but it requires refactoring to be usable
in both cases.
Back-patch to all supported branches. In HEAD only, remove the
core code's copy of find_em_expr_for_rel, which is no longer used
and really should never have been pushed into equivclass.c in the
first place.
Ronan Dunklau, per report from David Rowley;
reviews by David Rowley, Ranier Vilela, and myself
Discussion: https://postgr.es/m/CAApHDvr4OeC2DBVY--zVP83-K=bYrTD7F8SZDhN4g+pj2f2S-A@mail.gmail.com
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
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
MERGE performs actions that modify rows in the target table using a
source table or query. MERGE provides a single SQL statement that can
conditionally INSERT/UPDATE/DELETE rows -- a task that would otherwise
require multiple PL statements. For example,
MERGE INTO target AS t
USING source AS s
ON t.tid = s.sid
WHEN MATCHED AND t.balance > s.delta THEN
UPDATE SET balance = t.balance - s.delta
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED AND s.delta > 0 THEN
INSERT VALUES (s.sid, s.delta)
WHEN NOT MATCHED THEN
DO NOTHING;
MERGE works with regular tables, partitioned tables and inheritance
hierarchies, including column and row security enforcement, as well as
support for row and statement triggers and transition tables therein.
MERGE is optimized for OLTP and is parameterizable, though also useful
for large scale ETL/ELT. MERGE is not intended to be used in preference
to existing single SQL commands for INSERT, UPDATE or DELETE since there
is some overhead. MERGE can be used from PL/pgSQL.
MERGE does not support targetting updatable views or foreign tables, and
RETURNING clauses are not allowed either. These limitations are likely
fixable with sufficient effort. Rewrite rules are also not supported,
but it's not clear that we'd want to support them.
Author: Pavan Deolasee <pavan.deolasee@gmail.com>
Author: Álvaro Herrera <alvherre@alvh.no-ip.org>
Author: Amit Langote <amitlangote09@gmail.com>
Author: Simon Riggs <simon.riggs@enterprisedb.com>
Reviewed-by: Peter Eisentraut <peter.eisentraut@enterprisedb.com>
Reviewed-by: Andres Freund <andres@anarazel.de> (earlier versions)
Reviewed-by: Peter Geoghegan <pg@bowt.ie> (earlier versions)
Reviewed-by: Robert Haas <robertmhaas@gmail.com> (earlier versions)
Reviewed-by: Japin Li <japinli@hotmail.com>
Reviewed-by: Justin Pryzby <pryzby@telsasoft.com>
Reviewed-by: Tomas Vondra <tomas.vondra@enterprisedb.com>
Reviewed-by: Zhihong Yu <zyu@yugabyte.com>
Discussion: https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.com
Discussion: https://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
Discussion: https://postgr.es/m/20201231134736.GA25392@alvherre.pgsql
This patch introduces the SQL/JSON standard constructors for JSON:
JSON()
JSON_ARRAY()
JSON_ARRAYAGG()
JSON_OBJECT()
JSON_OBJECTAGG()
For the most part these functions provide facilities that mimic
existing json/jsonb functions. However, they also offer some useful
additional functionality. In addition to text input, the JSON() function
accepts bytea input, which it will decode and constuct a json value from.
The other functions provide useful options for handling duplicate keys
and null values.
This series of patches will be followed by a consolidated documentation
patch.
Nikita Glukhov
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zihong Yu,
Himanshu Upadhyaya, Daniel Gustafsson, Justin Pryzby.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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
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.
Up to now, the planner estimated the size of a recursive query's
worktable as 10 times the size of the non-recursive term. It's hard
to see how to do significantly better than that automatically, but
we can give users control over the multiplier to allow tuning for
specific use-cases. The default behavior remains the same.
Simon Riggs
Discussion: https://postgr.es/m/CANbhV-EuaLm4H3g0+BSTYHEGxJj3Kht0R+rJ8vT57Dejnh=_nA@mail.gmail.com
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
The planner needs to treat GroupingFunc like Aggref for many purposes,
in particular with respect to processing of the argument expressions,
which are not to be evaluated at runtime. A few places hadn't gotten
that memo, notably including subselect.c's processing of outer-level
aggregates. This resulted in assertion failures or wrong plans for
cases in which a GROUPING() construct references an outer aggregation
level.
Also fix missing special cases for GroupingFunc in cost_qual_eval
(resulting in wrong cost estimates for GROUPING(), although it's
not clear that that would affect plan shapes in practice) and in
ruleutils.c (resulting in excess parentheses in pretty-print mode).
Per bug #17088 from Yaoguang Chen. Back-patch to all supported
branches.
Richard Guo, Tom Lane
Discussion: https://postgr.es/m/17088-e33882b387de7f5c@postgresql.org
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
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
createplan.c tries to save a runtime projection step by specifying
a scan plan node's output as being exactly the table's columns, or
index's columns in the case of an index-only scan, if there is not a
reason to do otherwise. This logic did not previously pay attention
to whether an index's columns are returnable. That worked, sort of
accidentally, until commit 9a3ddeb51 taught setrefs.c to reject plans
that try to read a non-returnable column. I have no desire to loosen
setrefs.c's new check, so instead adjust use_physical_tlist() to not
try to optimize this way when there are non-returnable column(s).
Per report from Ryan Kelly. Like the previous patch, back-patch
to all supported branches.
Discussion: https://postgr.es/m/CAHUie24ddN+pDNw7fkhNrjrwAX=fXXfGZZEHhRuofV_N_ftaSg@mail.gmail.com
8edd0e794 added some code to remove Append and MergeAppend nodes when they
contained a single child node. As it turned out, this was unsafe to do
when the Append/MergeAppend was parallel_aware and the child node was not.
Removing the Append/MergeAppend, in this case, could lead to the child plan
being called multiple times by parallel workers when it was unsafe to do
so.
Here we fix this by just not removing the Append/MergeAppend when the
parallel_aware flag of the parent and child node don't match.
Reported-by: Yura Sokolov
Bug: #17335
Discussion: https://postgr.es/m/b59605fecb20ba9ea94e70ab60098c237c870628.camel%40postgrespro.ru
Backpatch-through: 12, where 8edd0e794 was first introduced
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
In the normal configuration where GEQO_DEBUG isn't defined,
recent clang versions have started to complain that geqo_main.c
accumulates the edge_failures count but never does anything
with it. As a minimal back-patchable fix, insert a void cast
to silence this warning. (I'd speculated about ripping out the
GEQO_DEBUG logic altogether, but I don't think we'd wish to
back-patch that.)
Per recently-established project policy, this is a candidate
for back-patching into out-of-support branches: it suppresses
an annoying compiler warning but changes no behavior. Hence,
back-patch all the way to 9.2.
Discussion: https://postgr.es/m/CA+hUKGLTSZQwES8VNPmWO9AO0wSeLt36OCPDAZTccT1h7Q7kTQ@mail.gmail.com
In sort_inner_and_outer we iterate a list of PathKey elements, but the
variable is declared as (List *). This mistake is benign, because we
only pass the pointer to lcons() and never dereference it.
This exists since ~2004, but it's confusing. So fix and backpatch to all
supported branches.
Backpatch-through: 10
Discussion: https://postgr.es/m/bf3a6ea1-a7d8-7211-0669-189d5c169374%40enterprisedb.com
The need for this was foreseen long ago, but when record_eq
actually became hashable (in commit 01e658fa7), we missed updating
this spot.
Per bug #17363 from Elvis Pranskevichus. Back-patch to v14 where
the faulty commit came in.
Discussion: https://postgr.es/m/17363-f6d42fd0d726be02@postgresql.org
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
When building append paths, we've been looking only at startup and total
costs for the paths. When building fractional paths that may eliminate
the cheapest one, because it may be dominated by two separate paths (one
for startup, one for total cost).
This extends generate_orderedappend_paths() to also consider which paths
have lowest fractional cost. Currently we only consider paths matching
pathkeys - in the future this may be improved by also considering paths
that are only partially sorted, with an incremental sort on top.
Original report of an issue by Arne Roland, patch by me (based on a
suggestion by Tom Lane).
Reviewed-by: Arne Roland, Zhihong Yu
Discussion: https://postgr.es/m/e8f9ec90-546d-e948-acce-0525f3e92773%40enterprisedb.com
Discussion: https://postgr.es/m/1581042da8044e71ada2d6e3a51bf7bb%40index.de
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
We can revert the code changes of commit b5febc1d1 now, because
commit 9a3ddeb51 installed a real solution for the difficulty
that b5febc1d1 just dodged, namely that the planner might pick
the wrong one of several index columns nominally containing the
same value. It only matters which one we pick if we pick one
that's not returnable, and that mistake is now foreclosed.
Although both of the aforementioned commits were back-patched,
I don't feel a need to take any risk by back-patching this one.
The cases that it improves are very corner-ish.
Discussion: https://postgr.es/m/3179992.1641150853@sss.pgh.pa.us
Commit 4ace45677 failed to fix the problem fully, because the
same issue of attempting to fetch a non-returnable index column
can occur when rechecking the indexqual after using a lossy index
operator. Moreover, it broke EXPLAIN for such indexquals (which
indicates a gap in our test cases :-().
Revert the code changes of 4ace45677 in favor of adding a new field
to struct IndexOnlyScan, containing a version of the indexqual that
can be executed against the index-returned tuple without using any
non-returnable columns. (The restrictions imposed by check_index_only
guarantee this is possible, although we may have to recompute indexed
expressions.) Support construction of that during setrefs.c
processing by marking IndexOnlyScan.indextlist entries as resjunk
if they can't be returned, rather than removing them entirely.
(We could alternatively require setrefs.c to look up the IndexOptInfo
again, but abusing resjunk this way seems like a reasonably safe way
to avoid needing to do that.)
This solution isn't great from an API-stability standpoint: if there
are any extensions out there that build IndexOnlyScan structs directly,
they'll be broken in the next minor releases. However, only a very
invasive extension would be likely to do such a thing. There's no
change in the Path representation, so typical planner extensions
shouldn't have a problem.
As before, back-patch to all supported branches.
Discussion: https://postgr.es/m/3179992.1641150853@sss.pgh.pa.us
Discussion: https://postgr.es/m/17350-b5bdcf476e5badbb@postgresql.org
If an index has both returnable and non-returnable columns, and one of
the non-returnable columns is an expression using a Var that is in a
returnable column, then a query returning that expression could result
in an index-only scan plan that attempts to read the non-returnable
column, instead of recomputing the expression from the returnable
column as intended.
To fix, redefine the "indextlist" list of an IndexOnlyScan plan node
as containing null Consts in place of any non-returnable columns.
This solves the problem by preventing setrefs.c from falsely matching
to such entries. The executor is happy since it only cares about the
exposed types of the entries, and ruleutils.c doesn't care because a
correct plan won't reference those entries. I considered some other
ways to prevent setrefs.c from doing the wrong thing, but this way
seems good since (a) it allows a very localized fix, (b) it makes
the indextlist structure more compact in many cases, and (c) the
indextlist is now a more faithful representation of what the index AM
will actually produce, viz. nulls for any non-returnable columns.
This is easier to hit since we introduced included columns, but it's
possible to construct failing examples without that, as per the
added regression test. Hence, back-patch to all supported branches.
Per bug #17350 from Louis Jachiet.
Discussion: https://postgr.es/m/17350-b5bdcf476e5badbb@postgresql.org
Standardize on xoroshiro128** as our basic PRNG algorithm, eliminating
a bunch of platform dependencies as well as fundamentally-obsolete PRNG
code. In addition, this API replacement will ease replacing the
algorithm again in future, should that become necessary.
xoroshiro128** is a few percent slower than the drand48 family,
but it can produce full-width 64-bit random values not only 48-bit,
and it should be much more trustworthy. It's likely to be noticeably
faster than the platform's random(), depending on which platform you
are thinking about; and we can have non-global state vectors easily,
unlike with random(). It is not cryptographically strong, but neither
are the functions it replaces.
Fabien Coelho, reviewed by Dean Rasheed, Aleksander Alekseev, and myself
Discussion: https://postgr.es/m/alpine.DEB.2.22.394.2105241211230.165418@pseudo
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
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
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
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
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
If a function-in-FROM laterally references the output of some sub-SELECT
earlier in the FROM clause, and we are able to flatten that sub-SELECT
into the outer query, the expression(s) copied into the function RTE
missed being processed by eval_const_expressions. This'd lead to trouble
and probable crashes at execution if such expressions contained
named-argument function call syntax or functions with defaulted arguments.
The bug is masked if the query contains any explicit JOIN syntax, which
may help explain why we'd not noticed.
Per bug #17227 from Bernd Dorn. This is an oversight in commit 7266d0997,
so back-patch to v13 where that came in.
Discussion: https://postgr.es/m/17227-5a28ed1512189fa4@postgresql.org
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
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
Up to now the size of a query's rangetable has been limited by the
constants INNER_VAR et al, which mustn't be equal to any real
rangetable index. 65000 doubtless seemed like enough for anybody,
and it still is orders of magnitude larger than the number of joins
we can realistically handle. However, we need a rangetable entry
for each child partition that is (or might be) processed by a query.
Queries with a few thousand partitions are getting more realistic,
so that the day when that limit becomes a problem is in sight,
even if it's not here yet. Hence, let's raise the limit.
Rather than just increase the values of INNER_VAR et al, this patch
adopts the approach of making them small negative values, so that
rangetables could theoretically become as long as INT_MAX.
The bulk of the patch is concerned with changing Var.varno and some
related variables from "Index" (unsigned int) to plain "int". This
is basically cosmetic, with little actual effect other than to help
debuggers print their values nicely. As such, I've only bothered
with changing places that could actually see INNER_VAR et al, which
the parser and most of the planner don't. We do have to be careful
in places that are performing less/greater comparisons on varnos,
but there are very few such places, other than the IS_SPECIAL_VARNO
macro itself.
A notable side effect of this patch is that while it used to be
possible to add INNER_VAR et al to a Bitmapset, that will now
draw an error. I don't see any likelihood that it wouldn't be a
bug to include these fake varnos in a bitmapset of real varnos,
so I think this is all to the good.
Although this touches outfuncs/readfuncs, I don't think a catversion
bump is required, since stored rules would never contain Vars
with these fake varnos.
Andrey Lepikhov and Tom Lane, after a suggestion by Peter Eisentraut
Discussion: https://postgr.es/m/43c7f2f5-1e27-27aa-8c65-c91859d15190@postgrespro.ru
It's possible for us to copy an AlternativeSubPlan expression node
into multiple places, for example the scan quals of several
partition children. Then it's possible that we choose a different
one of the alternatives as optimal in each place. Commit 41efb8340
failed to consider this scenario, so its attempt to remove "unused"
subplans could remove subplans that were still used elsewhere.
Fix by delaying the removal logic until we've examined all the
AlternativeSubPlans in a given query level. (This does assume that
AlternativeSubPlans couldn't get copied to other query levels, but
for the foreseeable future that's fine; cf qual_is_pushdown_safe.)
Per report from Rajkumar Raghuwanshi. Back-patch to v14
where the faulty logic came in.
Discussion: https://postgr.es/m/CAKcux6==O3NNZC3bZ2prRYv3cjm3_Zw1GfzmOjEVqYN4jub2+Q@mail.gmail.com
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
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
We've supported parallel aggregation since e06a38965. At the time, we
didn't quite get around to also adding parallel DISTINCT. So, let's do
that now.
This is implemented by introducing a two-phase DISTINCT. Phase 1 is
performed on parallel workers, rows are made distinct there either by
hashing or by sort/unique. The results from the parallel workers are
combined and the final distinct phase is performed serially to get rid of
any duplicate rows that appear due to combining rows for each of the
parallel workers.
Author: David Rowley
Reviewed-by: Zhihong Yu
Discussion: https://postgr.es/m/CAApHDvrjRxVKwQN0he79xS+9wyotFXL=RmoWqGGO2N45Farpgw@mail.gmail.com
959d00e9d added the ability to make use of an Append node instead of a
MergeAppend when we wanted to perform a scan of a partitioned table and
the required sort order was the same as the partitioned keys and the
partitioned table was defined in such a way that earlier partitions were
guaranteed to only contain lower-order values than later partitions.
However, previously we didn't allow these ordered partition scans for
LIST partitioned table when there were any partitions that allowed
multiple Datums. This was a very cheap check to make and we could likely
have done a little better by checking if there were interleaved
partitions, but at the time we didn't have visibility about which
partitions were pruned, so we still may have disallowed cases where all
interleaved partitions were pruned.
Since 475dbd0b7, we now have knowledge of pruned partitions, we can do a
much better job inside partitions_are_ordered().
Here we pass which partitions survived partition pruning into
partitions_are_ordered() and, for LIST partitioning, have it check to see
if any live partitions exist that are also in the new "interleaved_parts"
field defined in PartitionBoundInfo.
For RANGE partitioning we can relax the code which caused the partitions
to be unordered if a DEFAULT partition existed. Since we now know which
partitions were pruned, partitions_are_ordered() now returns true when the
DEFAULT partition was pruned.
Reviewed-by: Amit Langote, Zhihong Yu
Discussion: https://postgr.es/m/CAApHDvrdoN_sXU52i=QDXe2k3WAo=EVry29r2+Tq2WYcn2xhEA@mail.gmail.com
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
Adjust the header comment in get_agg_clause_costs so that it matches what
the function currently does. No recursive searching has been done ever
since 0a2bc5d61. It also does not determine the aggtranstype like the
comment claimed. That's all done in preprocess_aggref().
preprocess_aggref also now determines the numOrderedAggs, so remove the
mention that get_agg_clause_costs also calculates "counts".
Normally, since this is just an adjustment of a comment it might not be
worth back-patching, but since this code is new to PG14 and that version
is still in beta, then it seems worth having the comments match.
Discussion: https://postgr.es/m/CAApHDvrrGrTJFPELrjx0CnDtz9B7Jy2XYW3Z2BKifAWLSaJYwQ@mail.gmail.com
Backpatch-though: 14
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
As of v14, pg_depend contains almost 7000 "pin" entries recording
the OIDs of built-in objects. This is a fair amount of bloat for
every database, and it adds time to pg_depend lookups as well as
initdb. We can get rid of all of those entries in favor of an OID
range check, i.e. "OIDs below FirstUnpinnedObjectId are pinned".
(template1 and the public schema are exceptions. Those exceptions
are now wired into IsPinnedObject() instead of initdb's code for
filling pg_depend, but it's the same amount of cruft either way.)
The contents of pg_shdepend are modified likewise.
Discussion: https://postgr.es/m/3737988.1618451008@sss.pgh.pa.us
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
"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
Commit 7266d0997 added code to pull up simple constant function
results, converting the RTE_FUNCTION RTE to a dummy RTE_RESULT
RTE since it no longer need be scanned. But I forgot to clear
the LATERAL flag if the RTE has it set. If the function reduced
to a constant, it surely contains no lateral references so this
simplification is logically OK. It's needed because various other
places will Assert that RESULT RTEs aren't LATERAL.
Per bug #17097 from Yaoguang Chen. Back-patch to v13 where the
faulty code came in.
Discussion: https://postgr.es/m/17097-3372ef9f798fc94f@postgresql.org
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
Previously, all CustomScan providers had to support projections,
but there may be cases where this is inconvenient. Add a flag
bit to say if it's supported.
Important item for the release notes: this is non-backwards-compatible
since the default is now to assume that CustomScan providers can't
project, instead of assuming that they can. It's fail-soft, but could
result in visible performance penalties due to adding unnecessary
Result nodes.
Sven Klemm, reviewed by Aleksander Alekseev; some cosmetic fiddling
by me.
Discussion: https://postgr.es/m/CAMCrgp1kyakOz6c8aKhNDJXjhQ1dEjEnp+6KNT3KxPrjNtsrDg@mail.gmail.com
Joel Jacobson reported that deep nesting of trivial (flattenable)
views results in O(N^3) growth of planning time for N-deep nesting.
It turns out that a large chunk of this cost comes from copying around
the "subquery" sub-tree of each view's RTE_SUBQUERY RTE. But once we
have successfully flattened the subquery, we don't need that anymore,
because the planner isn't going to do anything else interesting with
that RTE. We already zap the subquery pointer during setrefs.c (cf.
add_rte_to_flat_rtable), but it's useless baggage earlier than that
too. Clearing the pointer as soon as pull_up_simple_subquery is done
with the RTE reduces the cost from O(N^3) to O(N^2); which is still
not great, but it's quite a lot better. Further improvements will
require rethinking of the RTE data structure, which is being considered
in another thread.
Patch by me; thanks to Dean Rasheed for review.
Discussion: https://postgr.es/m/797aff54-b49b-4914-9ff9-aa42564a4d7d@www.fastmail.com
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
Commit 428b260f8 broke planning of cases where row marks are needed
(SELECT FOR UPDATE, etc) and one of the query's tables is a foreign
table that has regular table(s) as inheritance children. We got the
reverse case right, but apparently were thinking that foreign tables
couldn't be inheritance parents. Not so; so we need to be able to
add a CTID junk column while adding a new child, not only a wholerow
junk column.
Back-patch to v12 where the faulty code came in.
Amit Langote
Discussion: https://postgr.es/m/CA+HiwqEmo3FV1LAQ4TVyS2h1WM=kMkZUmbNuZSCnfHvMcUcPeA@mail.gmail.com
create_projection_plan contains a hidden assumption (here made
explicit by an Assert) that a projection-capable Path will yield a
projection-capable Plan. Unfortunately, that assumption is violated
only a few lines away, by create_projection_plan itself. This means
that two stacked ProjectionPaths can yield an outcome where we try to
jam the upper path's tlist into a non-projection-capable child node,
resulting in an invalid plan.
There isn't any good reason to have stacked ProjectionPaths; indeed the
whole concept is faulty, since the set of Vars/Aggs/etc needed by the
upper one wouldn't necessarily be available in the output of the lower
one, nor could the lower one create such values if they weren't
available from its input. Hence, we can fix this by adjusting
create_projection_path to strip any top-level ProjectionPath from the
subpath it's given. (This amounts to saying "oh, we changed our
minds about what we need to project here".)
The test case added here only fails in v13 and HEAD; before that, we
don't attempt to shove the Sort into the parallel part of the plan,
for reasons that aren't entirely clear to me. However, all the
directly-related code looks generally the same as far back as v11,
where the hazard was introduced (by d7c19e62a). So I've got no faith
that the same type of bug doesn't exist in v11 and v12, given the
right test case. Hence, back-patch the code changes, but not the
irrelevant test case, into those branches.
Per report from Bas Poot.
Discussion: https://postgr.es/m/534fca83789c4a378c7de379e9067d4f@politie.nl
Commit e717a9a18 introduced a code path that bypassed the call of
get_expr_result_type, which is not good because we need its rettupdesc
result to pass to check_sql_fn_retval. We'd failed to notice right
away because the code path in which check_sql_fn_retval uses that
argument is fairly hard to reach in this context. It's not impossible
though, and in any case inline_function would have no business
assuming that check_sql_fn_retval doesn't need that value.
To fix, move get_expr_result_type out of the if-block, which in
turn requires moving the construction of the dummy FuncExpr
out of it.
Per report from Ranier Vilela. (I'm bemused by the lack of any
compiler complaints...)
Discussion: https://postgr.es/m/CAEudQAqBqQpQ3HruWAGU_7WaMJ7tntpk0T8k_dVtNB46DqdBgw@mail.gmail.com
Result Cache, added in 9eacee2e6 neglected to properly adjust the plan
references in setrefs.c. This could lead to the following error during
EXPLAIN:
ERROR: cannot decompile join alias var in plan tree
Fix that.
Bug: 17030
Reported-by: Hans Buschmann
Discussion: https://postgr.es/m/17030-5844aecae42fe223@postgresql.org
Code added in 9e215378d to disable building of Result Cache paths when
not all join conditions are part of the parameterization of a unique
join failed to first check if the inner path's param_info was set before
checking the param_info's ppi_clauses.
Add a check for NULL values here and just bail on trying to build the
path if param_info is NULL. lateral_vars are not considered when
deciding if the join is unique, so we're not missing out on doing the
optimization when there are lateral_vars and no param_info.
Reported-by: Coverity, via Tom Lane
Discussion: https://postgr.es/m/457998.1621779290@sss.pgh.pa.us
When the planner considered using a Result Cache node to cache results
from the inner side of a Nested Loop Join, it failed to consider that the
inner path's parameterization may not be the entire join condition. If
the join was marked as inner_unique then we may accidentally put the cache
in singlerow mode. This meant that entries would be marked as complete
after caching the first row. That was wrong as if only part of the join
condition was parameterized then the uniqueness of the unique join was not
guaranteed at the Result Cache's level. The uniqueness is only guaranteed
after Nested Loop applies the join filter. If subsequent rows were found,
this would lead to:
ERROR: cache entry already complete
This could have been fixed by only putting the cache in singlerow mode if
the entire join condition was parameterized. However, Nested Loop will
only read its inner side so far as the first matching row when the join is
unique, so that might mean we never get an opportunity to mark cache
entries as complete. Since non-complete cache entries are useless for
subsequent lookups, we just don't bother considering a Result Cache path
in this case.
In passing, remove the XXX comment that claimed the above ERROR might be
better suited to be an Assert. After there being an actual case which
triggered it, it seems better to keep it an ERROR.
Reported-by: David Christensen
Discussion: https://postgr.es/m/CAOxo6X+dy-V58iEPFgst8ahPKEU+38NZzUuc+a7wDBZd4TrHMQ@mail.gmail.com
Also "make reformat-dat-files".
The only change worthy of note is that pgindent messed up the formatting
of launcher.c's struct LogicalRepWorkerId, which led me to notice that
that struct wasn't used at all anymore, so I just took it out.
It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE
list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present.
If it happens, the ON CONFLICT UPDATE code path would end up storing
tuples that include the values of the extra resjunk columns. That's
fairly harmless in the short run, but if new columns are added to
the table then the values would become accessible, possibly leading
to malfunctions if they don't match the datatypes of the new columns.
This had escaped notice through a confluence of missing sanity checks,
including
* There's no cross-check that a tuple presented to heap_insert or
heap_update matches the table rowtype. While it's difficult to
check that fully at reasonable cost, we can easily add assertions
that there aren't too many columns.
* The output-column-assignment cases in execExprInterp.c lacked
any sanity checks on the output column numbers, which seems like
an oversight considering there are plenty of assertion checks on
input column numbers. Add assertions there too.
* We failed to apply nodeModifyTable's ExecCheckPlanOutput() to
the ON CONFLICT UPDATE tlist. That wouldn't have caught this
specific error, since that function is chartered to ignore resjunk
columns; but it sure seems like a bad omission now that we've seen
this bug.
In HEAD, the right way to fix this is to make the processing of
ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists
now do, that is don't add "SET x = x" entries, and use
ExecBuildUpdateProjection to evaluate the tlist and combine it with
old values of the not-set columns. This adds a little complication
to ExecBuildUpdateProjection, but allows removal of a comparable
amount of now-dead code from the planner.
In the back branches, the most expedient solution seems to be to
(a) use an output slot for the ON CONFLICT UPDATE projection that
actually matches the target table, and then (b) invent a variant of
ExecBuildProjectionInfo that can be told to not store values resulting
from resjunk columns, so it doesn't try to store into nonexistent
columns of the output slot. (We can't simply ignore the resjunk columns
altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.)
This works back to v10. In 9.6, projections work much differently and
we can't cheaply give them such an option. The 9.6 version of this
patch works by inserting a JunkFilter when it's necessary to get rid
of resjunk columns.
In addition, v11 and up have the reverse problem when trying to
perform ON CONFLICT UPDATE on a partitioned table. Through a
further oversight, adjust_partition_tlist() discarded resjunk columns
when re-ordering the ON CONFLICT UPDATE tlist to match a partition.
This accidentally prevented the storing-bogus-tuples problem, but
at the cost that MULTIEXPR_SUBLINK cases didn't work, typically
crashing if more than one row has to be updated. Fix by preserving
resjunk columns in that routine. (I failed to resist the temptation
to add more assertions there too, and to do some minor code
beautification.)
Per report from Andres Freund. Back-patch to all supported branches.
Security: CVE-2021-32028
Design problems were discovered in the handling of composite types and
record types that would cause some relevant versions not to be recorded.
Misgivings were also expressed about the use of the pg_depend catalog
for this purpose. We're out of time for this release so we'll revert
and try again.
Commits reverted:
1bf946bd: Doc: Document known problem with Windows collation versions.
cf002008: Remove no-longer-relevant test case.
ef387bed: Fix bogus collation-version-recording logic.
0fb0a050: Hide internal error for pg_collation_actual_version(<bad OID>).
ff942057: Suppress "warning: variable 'collcollate' set but not used".
d50e3b1f: Fix assertion in collation version lookup.
f24b1569: Rethink extraction of collation dependencies.
257836a7: Track collation versions for indexes.
cd6f479e: Add pg_depend.refobjversion.
7d1297df: Remove pg_collation.collversion.
Discussion: https://postgr.es/m/CA%2BhUKGLhj5t1fcjqAu8iD9B3ixJtsTNqyCCD4V0aTO9kAKAjjA%40mail.gmail.com
During queries coming from ri_triggers.c, we need to omit partitions
that are marked pending detach -- otherwise, the RI query is tricked
into allowing a row into the referencing table whose corresponding row
is in the detached partition. Which is bogus: once the detach operation
completes, the row becomes an orphan.
However, the code was not doing that in repeatable-read transactions,
because relcache kept a copy of the partition descriptor that included
the partition, and used it in the RI query. This commit changes the
partdesc cache code to only keep descriptors that aren't dependent on
a snapshot (namely: those where no detached partition exist, and those
where detached partitions are included). When a partdesc-without-
detached-partitions is requested, we create one afresh each time; also,
those partdescs are stored in PortalContext instead of
CacheMemoryContext.
find_inheritance_children gets a new output *detached_exist boolean,
which indicates whether any partition marked pending-detach is found.
Its "include_detached" input flag is changed to "omit_detached", because
that name captures desired the semantics more naturally.
CreatePartitionDirectory() and RelationGetPartitionDesc() arguments are
identically renamed.
This was noticed because a buildfarm member that runs with relcache
clobbering, which would not keep the improperly cached partdesc, broke
one test, which led us to realize that the expected output of that test
was bogus. This commit also corrects that expected output.
Author: Amit Langote <amitlangote09@gmail.com>
Author: Álvaro Herrera <alvherre@alvh.no-ip.org>
Discussion: https://postgr.es/m/3269784.1617215412@sss.pgh.pa.us
I didn't particularly like this function name, as it fails to
express what's going on. Also, returning the sort expression
alone isn't too helpful --- typically, a caller would also
need some other fields of the EquivalenceMember. But the
sole caller really only needs a bool result, so let's make
it "bool relation_can_be_sorted_early()".
Discussion: https://postgr.es/m/91f3ec99-85a4-fa55-ea74-33f85a5c651f@swarm64.com
An oversight introduced by the incremental-sort patches caused
"could not find pathkey item to sort" errors in some situations
where a sort key involves an aggregate or window function.
The basic problem here is that find_em_expr_usable_for_sorting_rel
isn't properly modeling what prepare_sort_from_pathkeys will do
later. Rather than hoping we can keep those functions in sync,
let's refactor so that they actually share the code for
identifying a suitable sort expression.
With this refactoring, tlist.c's tlist_member_ignore_relabel
is unused. I removed it in HEAD but left it in place in v13,
in case any extensions are using it.
Per report from Luc Vlaming. Back-patch to v13 where the
problem arose.
James Coleman and Tom Lane
Discussion: https://postgr.es/m/91f3ec99-85a4-fa55-ea74-33f85a5c651f@swarm64.com
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
ScalarArrayOpExprs with "useOr=true" and a set of Consts on the righthand
side have traditionally been evaluated by using a linear search over the
array. When these arrays contain large numbers of elements then this
linear search could become a significant part of execution time.
Here we add a new method of evaluating ScalarArrayOpExpr expressions to
allow them to be evaluated by first building a hash table containing each
element, then on subsequent evaluations, we just probe that hash table to
determine if there is a match.
The planner is in charge of determining when this optimization is possible
and it enables it by setting hashfuncid in the ScalarArrayOpExpr. The
executor will only perform the hash table evaluation when the hashfuncid
is set.
This means that not all cases are optimized. For example CHECK constraints
containing an IN clause won't go through the planner, so won't get the
hashfuncid set. We could maybe do something about that at some later
date. The reason we're not doing it now is from fear that we may slow
down cases where the expression is evaluated only once. Those cases can
be common, for example, a single row INSERT to a table with a CHECK
constraint containing an IN clause.
In the planner, we enable this when there are suitable hash functions for
the ScalarArrayOpExpr's operator and only when there is at least
MIN_ARRAY_SIZE_FOR_HASHED_SAOP elements in the array. The threshold is
currently set to 9.
Author: James Coleman, David Rowley
Reviewed-by: David Rowley, Tomas Vondra, Heikki Linnakangas
Discussion: https://postgr.es/m/CAAaqYe8x62+=wn0zvNKCj55tPpg-JBHzhZFFc6ANovdqFw7-dA@mail.gmail.com
This adds support for writing CREATE FUNCTION and CREATE PROCEDURE
statements for language SQL with a function body that conforms to the
SQL standard and is portable to other implementations.
Instead of the PostgreSQL-specific AS $$ string literal $$ syntax,
this allows writing out the SQL statements making up the body
unquoted, either as a single statement:
CREATE FUNCTION add(a integer, b integer) RETURNS integer
LANGUAGE SQL
RETURN a + b;
or as a block
CREATE PROCEDURE insert_data(a integer, b integer)
LANGUAGE SQL
BEGIN ATOMIC
INSERT INTO tbl VALUES (a);
INSERT INTO tbl VALUES (b);
END;
The function body is parsed at function definition time and stored as
expression nodes in a new pg_proc column prosqlbody. So at run time,
no further parsing is required.
However, this form does not support polymorphic arguments, because
there is no more parse analysis done at call time.
Dependencies between the function and the objects it uses are fully
tracked.
A new RETURN statement is introduced. This can only be used inside
function bodies. Internally, it is treated much like a SELECT
statement.
psql needs some new intelligence to keep track of function body
boundaries so that it doesn't send off statements when it sees
semicolons that are inside a function body.
Tested-by: Jaime Casanova <jcasanov@systemguards.com.ec>
Reviewed-by: Julien Rouhaud <rjuju123@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/1c11f1eb-f00c-43b7-799d-2d44132c02d7@2ndquadrant.com
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 allows something like
SELECT ... FROM t1 JOIN t2 USING (a, b, c) AS x
where x has the columns a, b, c and unlike a regular alias it does not
hide the range variables of the tables being joined t1 and t2.
Per SQL:2016 feature F404 "Range variable for common column names".
Reviewed-by: Vik Fearing <vik.fearing@2ndquadrant.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://www.postgresql.org/message-id/flat/454638cf-d563-ab76-a585-2564428062af@2ndquadrant.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
Here we add a new output parameter to estimate_num_groups() to allow it to
inform the caller of additional, possibly useful information about the
estimation.
The new output parameter is a struct that currently contains just a single
field with a set of flags. This was done rather than having the flags as
an output parameter to allow future fields to be added without having to
change the signature of the function at a later date when we want to pass
back further information that might not be suitable to store in the flags
field.
It seems reasonable that one day in the future that the planner would want
to know more about the estimation. For example, how many individual sets
of statistics was the estimation generated from? The planner may want to
take that into account if we ever want to consider risks as well as costs
when generating plans.
For now, there's only 1 flag we set in the flags field. This is to
indicate if the estimation fell back on using the hard-coded constants in
any part of the estimation. Callers may like to change their behavior if
this is set, and this gives them the ability to do so. Callers may pass
the flag pointer as NULL if they have no interest in obtaining any
additional information about the estimate.
We're not adding any actual usages of these flags here. Some follow-up
commits will make use of this feature. Additionally, we're also not
making any changes to add support for clauselist_selectivity() and
clauselist_selectivity_ext(). However, if this is required in the future
then the same struct being added here should be fine to use as a new
output argument for those functions too.
Author: David Rowley
Discussion: https://postgr.es/m/CAApHDvqQqpk=1W-G_ds7A9CsXX3BggWj_7okinzkLVhDubQzjA@mail.gmail.com
Here we aim to reduce duplicate work done by contain_volatile_functions()
by caching whether PathTargets and RestrictInfos contain any volatile
functions the first time contain_volatile_functions() is called for them.
Any future calls for these nodes just use the cached value rather than
going to the trouble of recursively checking the sub-node all over again.
Thanks to Tom Lane for the idea.
Any locations in the code which make changes to a PathTarget or
RestrictInfo which could change the outcome of the volatility check must
change the cached value back to VOLATILITY_UNKNOWN again.
contain_volatile_functions() is the only code in charge of setting the
cache value to either VOLATILITY_VOLATILE or VOLATILITY_NOVOLATILE.
Some existing code does benefit from this additional caching, however,
this change is mainly aimed at an upcoming patch that must check for
volatility during the join search. Repeated volatility checks in that
case can become very expensive when the join search contains more than a
few relations.
Author: David Rowley
Discussion: https://postgr.es/m/3795226.1614059027@sss.pgh.pa.us
Allow defining extended statistics on expressions, not just just on
simple column references. With this commit, expressions are supported
by all existing extended statistics kinds, improving the same types of
estimates. A simple example may look like this:
CREATE TABLE t (a int);
CREATE STATISTICS s ON mod(a,10), mod(a,20) FROM t;
ANALYZE t;
The collected statistics are useful e.g. to estimate queries with those
expressions in WHERE or GROUP BY clauses:
SELECT * FROM t WHERE mod(a,10) = 0 AND mod(a,20) = 0;
SELECT 1 FROM t GROUP BY mod(a,10), mod(a,20);
This introduces new internal statistics kind 'e' (expressions) which is
built automatically when the statistics object definition includes any
expressions. This represents single-expression statistics, as if there
was an expression index (but without the index maintenance overhead).
The statistics is stored in pg_statistics_ext_data as an array of
composite types, which is possible thanks to 79f6a942bd.
CREATE STATISTICS allows building statistics on a single expression, in
which case in which case it's not possible to specify statistics kinds.
A new system view pg_stats_ext_exprs can be used to display expression
statistics, similarly to pg_stats and pg_stats_ext views.
ALTER TABLE ... ALTER COLUMN ... TYPE now treats indexes the same way it
treats indexes, i.e. it drops and recreates the statistics. This means
all statistics are reset, and we no longer try to preserve at least the
functional dependencies. This should not be a major issue in practice,
as the functional dependencies actually rely on per-column statistics,
which were always reset anyway.
Author: Tomas Vondra
Reviewed-by: Justin Pryzby, Dean Rasheed, Zhihong Yu
Discussion: https://postgr.es/m/ad7891d2-e90c-b446-9fe2-7419143847d7%40enterprisedb.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
Previously, to check relation permanence, the Relation's Form_pg_class
structure member relpersistence was compared to the value
RELPERSISTENCE_PERMANENT ("p"). This commit adds the macro
RelationIsPermanent() and is used in appropirate places to simplify the
code. This matches other RelationIs* macros.
This macro will be used in more places in future cluster file encryption
patches.
Discussion: https://postgr.es/m/20210318153134.GH20766@tamriel.snowman.net
With grouping sets, it's possible that some of the grouping sets are
duplicate. This is especially common with CUBE and ROLLUP clauses. For
example GROUP BY CUBE (a,b), CUBE (b,c) is equivalent to
GROUP BY GROUPING SETS (
(a, b, c),
(a, b, c),
(a, b, c),
(a, b),
(a, b),
(a, b),
(a),
(a),
(a),
(c, a),
(c, a),
(c, a),
(c),
(b, c),
(b),
()
)
Some of the grouping sets are calculated multiple times, which is mostly
unnecessary. This commit implements a new GROUP BY DISTINCT feature, as
defined in the SQL standard, which eliminates the duplicate sets.
Author: Vik Fearing
Reviewed-by: Erik Rijkers, Georgios Kokolatos, Tomas Vondra
Discussion: https://postgr.es/m/bf3805a8-d7d1-ae61-fece-761b7ff41ecc@postgresfriends.org
Commit 05c8482f7f added the implementation of parallel SELECT for
"INSERT INTO ... SELECT ..." which may incur non-negligible overhead in
the additional parallel-safety checks that it performs, even when, in the
end, those checks determine that parallelism can't be used. This is
normally only ever a problem in the case of when the target table has a
large number of partitions.
A new GUC option "enable_parallel_insert" is added, to allow insert in
parallel-mode. The default is on.
In addition to the GUC option, the user may want a mechanism to allow
inserts in parallel-mode with finer granularity at table level. The new
table option "parallel_insert_enabled" allows this. The default is true.
Author: "Hou, Zhijie"
Reviewed-by: Greg Nancarrow, Amit Langote, Takayuki Tsunakawa, Amit Kapila
Discussion: https://postgr.es/m/CAA4eK1K-cW7svLC2D7DHoGHxdAdg3P37BLgebqBOC2ZLc9a6QQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAJcOf-cXnB5cnMKqWEp2E2z7Mvcd04iLVmV=qpFJrR3AcrTS3g@mail.gmail.com
Commit 05c8482f7f added special logic related to parallel-safety of FK
triggers. This is a bit of a hack and should have instead been done by
simply setting appropriate proparallel values on those trigger functions
themselves.
Suggested-by: Tom Lane
Author: Greg Nancarrow
Reviewed-by: Amit Kapila
Discussion: https://postgr.es/m/2309260.1615485644@sss.pgh.pa.us
The commit added code which used a relcache TriggerDesc field across
another cache access, which it shouldn't because the relcache doesn't
guarantee it won't get moved.
Diagnosed-by: Tom Lane
Author: Greg Nancarrow
Reviewed-by: Hou Zhijie, Amit Kapila
Discussion: https://postgr.es/m/2309260.1615485644@sss.pgh.pa.us
Initialize other newly added variables in max_parallel_hazard_context via
is_parallel_safe() because we don't check the parallel-safety of target
relations in that function.
Reported-by: Tom Lane as per buildfarm
Author: Amit Kapila
Discussion: https://postgr.es/m/2060179.1615347455@sss.pgh.pa.us
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
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
Alvaro Herrera
Tom Lane
Peter Eisentraut
David Rowley
Andres Freund
Peter Geoghegan
Andrew Dunstan
Thomas Munro
Michael Paquier
Etsuro Fujita
Tomas Vondra
Bruce Momjian
Amit Kapila