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
Tom Lane
David Rowley
Thomas Munro
Alvaro Herrera
Peter Eisentraut
Michael Paquier
Etsuro Fujita
Andrew Dunstan
Tomas Vondra