Currently, information about the permissions to be checked on relations
mentioned in a query is stored in their range table entries. So the
executor must scan the entire range table looking for relations that
need to have permissions checked. This can make the permission checking
part of the executor initialization needlessly expensive when many
inheritance children are present in the range range. While the
permissions need not be checked on the individual child relations, the
executor still must visit every range table entry to filter them out.
This commit moves the permission checking information out of the range
table entries into a new plan node called RTEPermissionInfo. Every
top-level (inheritance "root") RTE_RELATION entry in the range table
gets one and a list of those is maintained alongside the range table.
This new list is initialized by the parser when initializing the range
table. The rewriter can add more entries to it as rules/views are
expanded. Finally, the planner combines the lists of the individual
subqueries into one flat list that is passed to the executor for
checking.
To make it quick to find the RTEPermissionInfo entry belonging to a
given relation, RangeTblEntry gets a new Index field 'perminfoindex'
that stores the corresponding RTEPermissionInfo's index in the query's
list of the latter.
ExecutorCheckPerms_hook has gained another List * argument; the
signature is now:
typedef bool (*ExecutorCheckPerms_hook_type) (List *rangeTable,
List *rtePermInfos,
bool ereport_on_violation);
The first argument is no longer used by any in-core uses of the hook,
but we leave it in place because there may be other implementations that
do. Implementations should likely scan the rtePermInfos list to
determine which operations to allow or deny.
Author: Amit Langote <amitlangote09@gmail.com>
Discussion: https://postgr.es/m/CA+HiwqGjJDmUhDSfv-U2qhKJjt9ST7Xh9JXC_irsAQ1TAUsJYg@mail.gmail.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
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 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
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
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
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
Noticed while working in this area. This code was introduced in PG15,
which is still in beta, so backpatch to there for consistency.
Backpatch-through: 15
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
Up until now, we've had a policy of only marking certain variables
in the PostgreSQL header files with PGDLLIMPORT, but now we've
decided to mark them all. This means that extensions running on
Windows should no longer operate at a disadvantage as compared to
extensions running on Linux: if the variable is present in a header
file, it should be accessible.
Discussion: http://postgr.es/m/CA+TgmoYanc1_FSfimhgiWSqVyP5KKmh5NP2BWNwDhO8Pg2vGYQ@mail.gmail.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
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
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
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
"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 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
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
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
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
Here we add a new executor node type named "Result Cache". The planner
can include this node type in the plan to have the executor cache the
results from the inner side of parameterized nested loop joins. This
allows caching of tuples for sets of parameters so that in the event that
the node sees the same parameter values again, it can just return the
cached tuples instead of rescanning the inner side of the join all over
again. Internally, result cache uses a hash table in order to quickly
find tuples that have been previously cached.
For certain data sets, this can significantly improve the performance of
joins. The best cases for using this new node type are for join problems
where a large portion of the tuples from the inner side of the join have
no join partner on the outer side of the join. In such cases, hash join
would have to hash values that are never looked up, thus bloating the hash
table and possibly causing it to multi-batch. Merge joins would have to
skip over all of the unmatched rows. If we use a nested loop join with a
result cache, then we only cache tuples that have at least one join
partner on the outer side of the join. The benefits of using a
parameterized nested loop with a result cache increase when there are
fewer distinct values being looked up and the number of lookups of each
value is large. Also, hash probes to lookup the cache can be much faster
than the hash probe in a hash join as it's common that the result cache's
hash table is much smaller than the hash join's due to result cache only
caching useful tuples rather than all tuples from the inner side of the
join. This variation in hash probe performance is more significant when
the hash join's hash table no longer fits into the CPU's L3 cache, but the
result cache's hash table does. The apparent "random" access of hash
buckets with each hash probe can cause a poor L3 cache hit ratio for large
hash tables. Smaller hash tables generally perform better.
The hash table used for the cache limits itself to not exceeding work_mem
* hash_mem_multiplier in size. We maintain a dlist of keys for this cache
and when we're adding new tuples and realize we've exceeded the memory
budget, we evict cache entries starting with the least recently used ones
until we have enough memory to add the new tuples to the cache.
For parameterized nested loop joins, we now consider using one of these
result cache nodes in between the nested loop node and its inner node. We
determine when this might be useful based on cost, which is primarily
driven off of what the expected cache hit ratio will be. Estimating the
cache hit ratio relies on having good distinct estimates on the nested
loop's parameters.
For now, the planner will only consider using a result cache for
parameterized nested loop joins. This works for both normal joins and
also for LATERAL type joins to subqueries. It is possible to use this new
node for other uses in the future. For example, to cache results from
correlated subqueries. However, that's not done here due to some
difficulties obtaining a distinct estimation on the outer plan to
calculate the estimated cache hit ratio. Currently we plan the inner plan
before planning the outer plan so there is no good way to know if a result
cache would be useful or not since we can't estimate the number of times
the subplan will be called until the outer plan is generated.
The functionality being added here is newly introducing a dependency on
the return value of estimate_num_groups() during the join search.
Previously, during the join search, we only ever needed to perform
selectivity estimations. With this commit, we need to use
estimate_num_groups() in order to estimate what the hit ratio on the
result cache will be. In simple terms, if we expect 10 distinct values
and we expect 1000 outer rows, then we'll estimate the hit ratio to be
99%. Since cache hits are very cheap compared to scanning the underlying
nodes on the inner side of the nested loop join, then this will
significantly reduce the planner's cost for the join. However, it's
fairly easy to see here that things will go bad when estimate_num_groups()
incorrectly returns a value that's significantly lower than the actual
number of distinct values. If this happens then that may cause us to make
use of a nested loop join with a result cache instead of some other join
type, such as a merge or hash join. Our distinct estimations have been
known to be a source of trouble in the past, so the extra reliance on them
here could cause the planner to choose slower plans than it did previous
to having this feature. Distinct estimations are also fairly hard to
estimate accurately when several tables have been joined already or when a
WHERE clause filters out a set of values that are correlated to the
expressions we're estimating the number of distinct value for.
For now, the costing we perform during query planning for result caches
does put quite a bit of faith in the distinct estimations being accurate.
When these are accurate then we should generally see faster execution
times for plans containing a result cache. However, in the real world, we
may find that we need to either change the costings to put less trust in
the distinct estimations being accurate or perhaps even disable this
feature by default. There's always an element of risk when we teach the
query planner to do new tricks that it decides to use that new trick at
the wrong time and causes a regression. Users may opt to get the old
behavior by turning the feature off using the enable_resultcache GUC.
Currently, this is enabled by default. It remains to be seen if we'll
maintain that setting for the release.
Additionally, the name "Result Cache" is the best name I could think of
for this new node at the time I started writing the patch. Nobody seems
to strongly dislike the name. A few people did suggest other names but no
other name seemed to dominate in the brief discussion that there was about
names. Let's allow the beta period to see if the current name pleases
enough people. If there's some consensus on a better name, then we can
change it before the release. Please see the 2nd discussion link below
for the discussion on the "Result Cache" name.
Author: David Rowley
Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu, Hou Zhijie
Tested-By: Konstantin Knizhnik
Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com
This removes "Add Result Cache executor node". It seems that something
weird is going on with the tracking of cache hits and misses as
highlighted by many buildfarm animals. It's not yet clear what the
problem is as other parts of the plan indicate that the cache did work
correctly, it's just the hits and misses that were being reported as 0.
This is especially a bad time to have the buildfarm so broken, so
reverting before too many more animals go red.
Discussion: https://postgr.es/m/CAApHDvq_hydhfovm4=izgWs+C5HqEeRScjMbOgbpC-jRAeK3Yw@mail.gmail.com
Here we add a new executor node type named "Result Cache". The planner
can include this node type in the plan to have the executor cache the
results from the inner side of parameterized nested loop joins. This
allows caching of tuples for sets of parameters so that in the event that
the node sees the same parameter values again, it can just return the
cached tuples instead of rescanning the inner side of the join all over
again. Internally, result cache uses a hash table in order to quickly
find tuples that have been previously cached.
For certain data sets, this can significantly improve the performance of
joins. The best cases for using this new node type are for join problems
where a large portion of the tuples from the inner side of the join have
no join partner on the outer side of the join. In such cases, hash join
would have to hash values that are never looked up, thus bloating the hash
table and possibly causing it to multi-batch. Merge joins would have to
skip over all of the unmatched rows. If we use a nested loop join with a
result cache, then we only cache tuples that have at least one join
partner on the outer side of the join. The benefits of using a
parameterized nested loop with a result cache increase when there are
fewer distinct values being looked up and the number of lookups of each
value is large. Also, hash probes to lookup the cache can be much faster
than the hash probe in a hash join as it's common that the result cache's
hash table is much smaller than the hash join's due to result cache only
caching useful tuples rather than all tuples from the inner side of the
join. This variation in hash probe performance is more significant when
the hash join's hash table no longer fits into the CPU's L3 cache, but the
result cache's hash table does. The apparent "random" access of hash
buckets with each hash probe can cause a poor L3 cache hit ratio for large
hash tables. Smaller hash tables generally perform better.
The hash table used for the cache limits itself to not exceeding work_mem
* hash_mem_multiplier in size. We maintain a dlist of keys for this cache
and when we're adding new tuples and realize we've exceeded the memory
budget, we evict cache entries starting with the least recently used ones
until we have enough memory to add the new tuples to the cache.
For parameterized nested loop joins, we now consider using one of these
result cache nodes in between the nested loop node and its inner node. We
determine when this might be useful based on cost, which is primarily
driven off of what the expected cache hit ratio will be. Estimating the
cache hit ratio relies on having good distinct estimates on the nested
loop's parameters.
For now, the planner will only consider using a result cache for
parameterized nested loop joins. This works for both normal joins and
also for LATERAL type joins to subqueries. It is possible to use this new
node for other uses in the future. For example, to cache results from
correlated subqueries. However, that's not done here due to some
difficulties obtaining a distinct estimation on the outer plan to
calculate the estimated cache hit ratio. Currently we plan the inner plan
before planning the outer plan so there is no good way to know if a result
cache would be useful or not since we can't estimate the number of times
the subplan will be called until the outer plan is generated.
The functionality being added here is newly introducing a dependency on
the return value of estimate_num_groups() during the join search.
Previously, during the join search, we only ever needed to perform
selectivity estimations. With this commit, we need to use
estimate_num_groups() in order to estimate what the hit ratio on the
result cache will be. In simple terms, if we expect 10 distinct values
and we expect 1000 outer rows, then we'll estimate the hit ratio to be
99%. Since cache hits are very cheap compared to scanning the underlying
nodes on the inner side of the nested loop join, then this will
significantly reduce the planner's cost for the join. However, it's
fairly easy to see here that things will go bad when estimate_num_groups()
incorrectly returns a value that's significantly lower than the actual
number of distinct values. If this happens then that may cause us to make
use of a nested loop join with a result cache instead of some other join
type, such as a merge or hash join. Our distinct estimations have been
known to be a source of trouble in the past, so the extra reliance on them
here could cause the planner to choose slower plans than it did previous
to having this feature. Distinct estimations are also fairly hard to
estimate accurately when several tables have been joined already or when a
WHERE clause filters out a set of values that are correlated to the
expressions we're estimating the number of distinct value for.
For now, the costing we perform during query planning for result caches
does put quite a bit of faith in the distinct estimations being accurate.
When these are accurate then we should generally see faster execution
times for plans containing a result cache. However, in the real world, we
may find that we need to either change the costings to put less trust in
the distinct estimations being accurate or perhaps even disable this
feature by default. There's always an element of risk when we teach the
query planner to do new tricks that it decides to use that new trick at
the wrong time and causes a regression. Users may opt to get the old
behavior by turning the feature off using the enable_resultcache GUC.
Currently, this is enabled by default. It remains to be seen if we'll
maintain that setting for the release.
Additionally, the name "Result Cache" is the best name I could think of
for this new node at the time I started writing the patch. Nobody seems
to strongly dislike the name. A few people did suggest other names but no
other name seemed to dominate in the brief discussion that there was about
names. Let's allow the beta period to see if the current name pleases
enough people. If there's some consensus on a better name, then we can
change it before the release. Please see the 2nd discussion link below
for the discussion on the "Result Cache" name.
Author: David Rowley
Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu
Tested-By: Konstantin Knizhnik
Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com
This patch makes two closely related sets of changes:
1. For UPDATE, the subplan of the ModifyTable node now only delivers
the new values of the changed columns (i.e., the expressions computed
in the query's SET clause) plus row identity information such as CTID.
ModifyTable must re-fetch the original tuple to merge in the old
values of any unchanged columns. The core advantage of this is that
the changed columns are uniform across all tables of an inherited or
partitioned target relation, whereas the other columns might not be.
A secondary advantage, when the UPDATE involves joins, is that less
data needs to pass through the plan tree. The disadvantage of course
is an extra fetch of each tuple to be updated. However, that seems to
be very nearly free in context; even worst-case tests don't show it to
add more than a couple percent to the total query cost. At some point
it might be interesting to combine the re-fetch with the tuple access
that ModifyTable must do anyway to mark the old tuple dead; but that
would require a good deal of refactoring and it seems it wouldn't buy
all that much, so this patch doesn't attempt it.
2. For inherited UPDATE/DELETE, instead of generating a separate
subplan for each target relation, we now generate a single subplan
that is just exactly like a SELECT's plan, then stick ModifyTable
on top of that. To let ModifyTable know which target relation a
given incoming row refers to, a tableoid junk column is added to
the row identity information. This gets rid of the horrid hack
that was inheritance_planner(), eliminating O(N^2) planning cost
and memory consumption in cases where there were many unprunable
target relations.
Point 2 of course requires point 1, so that there is a uniform
definition of the non-junk columns to be returned by the subplan.
We can't insist on uniform definition of the row identity junk
columns however, if we want to keep the ability to have both
plain and foreign tables in a partitioning hierarchy. Since
it wouldn't scale very far to have every child table have its
own row identity column, this patch includes provisions to merge
similar row identity columns into one column of the subplan result.
In particular, we can merge the whole-row Vars typically used as
row identity by FDWs into one column by pretending they are type
RECORD. (It's still okay for the actual composite Datums to be
labeled with the table's rowtype OID, though.)
There is more that can be done to file down residual inefficiencies
in this patch, but it seems to be committable now.
FDW authors should note several API changes:
* The argument list for AddForeignUpdateTargets() has changed, and so
has the method it must use for adding junk columns to the query. Call
add_row_identity_var() instead of manipulating the parse tree directly.
You might want to reconsider exactly what you're adding, too.
* PlanDirectModify() must now work a little harder to find the
ForeignScan plan node; if the foreign table is part of a partitioning
hierarchy then the ForeignScan might not be the direct child of
ModifyTable. See postgres_fdw for sample code.
* To check whether a relation is a target relation, it's no
longer sufficient to compare its relid to root->parse->resultRelation.
Instead, check it against all_result_relids or leaf_result_relids,
as appropriate.
Amit Langote and Tom Lane
Discussion: https://postgr.es/m/CA+HiwqHpHdqdDn48yCEhynnniahH78rwcrv1rEX65-fsZGBOLQ@mail.gmail.com
This implements asynchronous execution, which runs multiple parts of a
non-parallel-aware Append concurrently rather than serially to improve
performance when possible. Currently, the only node type that can be
run concurrently is a ForeignScan that is an immediate child of such an
Append. In the case where such ForeignScans access data on different
remote servers, this would run those ForeignScans concurrently, and
overlap the remote operations to be performed simultaneously, so it'll
improve the performance especially when the operations involve
time-consuming ones such as remote join and remote aggregation.
We may extend this to other node types such as joins or aggregates over
ForeignScans in the future.
This also adds the support for postgres_fdw, which is enabled by the
table-level/server-level option "async_capable". The default is false.
Robert Haas, Kyotaro Horiguchi, Thomas Munro, and myself. This commit
is mostly based on the patch proposed by Robert Haas, but also uses
stuff from the patch proposed by Kyotaro Horiguchi and from the patch
proposed by Thomas Munro. Reviewed by Kyotaro Horiguchi, Konstantin
Knizhnik, Andrey Lepikhov, Movead Li, Thomas Munro, Justin Pryzby, and
others.
Discussion: https://postgr.es/m/CA%2BTgmoaXQEt4tZ03FtQhnzeDEMzBck%2BLrni0UWHVVgOTnA6C1w%40mail.gmail.com
Discussion: https://postgr.es/m/CA%2BhUKGLBRyu0rHrDCMC4%3DRn3252gogyp1SjOgG8SEKKZv%3DFwfQ%40mail.gmail.com
Discussion: https://postgr.es/m/20200228.170650.667613673625155850.horikyota.ntt%40gmail.com
To allow inserts in parallel-mode this feature has to ensure that all the
constraints, triggers, etc. are parallel-safe for the partition hierarchy
which is costly and we need to find a better way to do that. Additionally,
we could have used existing cached information in some cases like indexes,
domains, etc. to determine the parallel-safety.
List of commits reverted, in reverse chronological order:
ed62d3737c Doc: Update description for parallel insert reloption.
c8f78b6161 Add a new GUC and a reloption to enable inserts in parallel-mode.
c5be48f092 Improve FK trigger parallel-safety check added by 05c8482f7f.
e2cda3c20a Fix use of relcache TriggerDesc field introduced by commit 05c8482f7f.
e4e87a32cc Fix valgrind issue in commit 05c8482f7f.
05c8482f7f Enable parallel SELECT for "INSERT INTO ... SELECT ...".
Discussion: https://postgr.es/m/E1lMiB9-0001c3-SY@gemulon.postgresql.org
Commit 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
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
It turns out that the calculation of [Merge]AppendPath.partitioned_rels
in allpaths.c is faulty and sometimes omits relevant non-leaf partitions,
allowing an assertion added by commit a929e17e5a to trigger. Rather
than fix that, it seems better to get rid of those fields altogether.
We don't really need the info until create_plan time, and calculating
it once for the selected plan should be cheaper than calculating it
for each append path we consider.
The preceding two commits did away with all use of the partitioned_rels
values; this commit just mechanically removes the fields and the code
that calculated them.
Discussion: https://postgr.es/m/87sg8tqhsl.fsf@aurora.ydns.eu
Discussion: https://postgr.es/m/CAJKUy5gCXDSmFs2c=R+VGgn7FiYcLCsEFEuDNNLGfoha=pBE_g@mail.gmail.com
Previously, pull_varnos() took the relids of a PlaceHolderVar as being
equal to the relids in its contents, but that fails to account for the
possibility that we have to postpone evaluation of the PHV due to outer
joins. This could result in a malformed plan. The known cases end up
triggering the "failed to assign all NestLoopParams to plan nodes"
sanity check in createplan.c, but other symptoms may be possible.
The right value to use is the join level we actually intend to evaluate
the PHV at. We can get that from the ph_eval_at field of the associated
PlaceHolderInfo. However, there are some places that call pull_varnos()
before the PlaceHolderInfos have been created; in that case, fall back
to the conservative assumption that the PHV will be evaluated at its
syntactic level. (In principle this might result in missing some legal
optimization, but I'm not aware of any cases where it's an issue in
practice.) Things are also a bit ticklish for calls occurring during
deconstruct_jointree(), but AFAICS the ph_eval_at fields should have
reached their final values by the time we need them.
The main problem in making this work is that pull_varnos() has no
way to get at the PlaceHolderInfos. We can fix that easily, if a
bit tediously, in HEAD by passing it the planner "root" pointer.
In the back branches that'd cause an unacceptable API/ABI break for
extensions, so leave the existing entry points alone and add new ones
with the additional parameter. (If an old entry point is called and
encounters a PHV, it'll fall back to using the syntactic level,
again possibly missing some valid optimization.)
Back-patch to v12. The computation is surely also wrong before that,
but it appears that we cannot reach a bad plan thanks to join order
restrictions imposed on the subquery that the PlaceHolderVar came from.
The error only became reachable when commit 4be058fe9 allowed trivial
subqueries to be collapsed out completely, eliminating their join order
restrictions.
Per report from Stephan Springl.
Discussion: https://postgr.es/m/171041.1610849523@sss.pgh.pa.us
While we do allow SRFs in ORDER BY, scan/join processing should not
consider such cases - such sorts should only happen via final Sort atop
a ProjectSet. So make sure we don't try adding such sorts below Gather
Merge, just like we do for expressions that are volatile and/or not
parallel safe.
Backpatch to PostgreSQL 13, where this code was introduced as part of
the Incremental Sort patch.
Author: James Coleman
Reviewed-by: Tomas Vondra
Backpatch-through: 13
Discussion: https://postgr.es/m/CAAaqYe8cK3g5CfLC4w7bs=hC0mSksZC=H5M8LSchj5e5OxpTAg@mail.gmail.com
Discussion: https://postgr.es/m/295524.1606246314%40sss.pgh.pa.us
Commit ebb7ae839d ensured we ignore pathkeys with volatile expressions
when considering adding a sort below a Gather Merge. Turns out we need
to care about parallel safety of the pathkeys too, otherwise we might
try sorting e.g. on results of a correlated subquery (as demonstrated
by a report from Luis Roberto).
Initial investigation by Tom Lane, patch by James Coleman. Backpatch
to 13, where the code was instroduced (as part of Incremental Sort).
Reported-by: Luis Roberto
Author: James Coleman
Reviewed-by: Tomas Vondra
Backpatch-through: 13
Discussion: https://postgr.es/m/622580997.37108180.1604080457319.JavaMail.zimbra%40siscobra.com.br
Discussion: https://postgr.es/m/CAAaqYe8cK3g5CfLC4w7bs=hC0mSksZC=H5M8LSchj5e5OxpTAg@mail.gmail.com
Formerly we only applied extended statistics to an OR clause as part
of the clauselist_selectivity() code path for an OR clause appearing
in an implicitly-ANDed list of clauses. This meant that it could only
use extended statistics if all sub-clauses of the OR clause were
covered by a single extended statistics object.
Instead, teach clause_selectivity() how to apply extended statistics
to an OR clause by handling its ORed list of sub-clauses in a similar
manner to an implicitly-ANDed list of sub-clauses, but with different
combination rules. This allows one or more extended statistics objects
to be used to estimate all or part of the list of sub-clauses. Any
remaining sub-clauses are then treated as if they are independent.
Additionally, to avoid double-application of extended statistics, this
introduces "extended" versions of clause_selectivity() and
clauselist_selectivity(), which include an option to ignore extended
statistics. This replaces the old clauselist_selectivity_simple()
function which failed to completely ignore extended statistics when
called from the extended statistics code.
A known limitation of the current infrastructure is that an AND clause
under an OR clause is not treated as compatible with extended
statistics (because we don't build RestrictInfos for such sub-AND
clauses). Thus, for example, "(a=1 AND b=1) OR (a=2 AND b=2)" will
currently be treated as two independent AND clauses (each of which may
be estimated using extended statistics), but extended statistics will
not currently be used to account for any possible overlap between
those clauses. Improving that is left as a task for the future.
Original patch by Tomas Vondra, with additional improvements by me.
Discussion: https://postgr.es/m/20200113230008.g67iyk4cs3xbnjju@development
For debugging purposes, Path nodes are supposed to have outfuncs
support, but this was overlooked in the original incremental sort patch.
While at it, clean up a couple other minor oversights, as well as
bizarre choice of return type for create_incremental_sort_path().
(All the existing callers just cast it to "Path *" immediately, so
they don't care, but some future caller might care.)
outfuncs.c fix by Zhijie Hou, the rest by me
Discussion: https://postgr.es/m/324c4d81d8134117972a5b1f6cdf9560@G08CNEXMBPEKD05.g08.fujitsu.local
When considering Incremental Sort below a Gather Merge, we need to be
a bit more careful when matching pathkeys to EC members. It's not enough
to find a member whose Vars are all in the current relation's target;
volatile expressions in particular need to be contained in the target,
otherwise it's too early to use the pathkey.
Reported-by: Jaime Casanova
Author: James Coleman
Reviewed-by: Tomas Vondra
Backpatch-through: 13, where the incremental sort code was added
Discussion: https://postgr.es/m/CAJGNTeNaxpXgBVcRhJX%2B2vSbq%2BF2kJqGBcvompmpvXb7pq%2BoFA%40mail.gmail.com
get_foreign_key_join_selectivity() looks for join clauses that equate
the two sides of the FK constraint. However, if we have a query like
"WHERE fktab.a = pktab.a and fktab.a = 1", it won't find any such join
clause, because equivclass.c replaces the given clauses with "fktab.a
= 1 and pktab.a = 1", which can be enforced at the scan level, leaving
nothing to be done for column "a" at the join level.
We can fix that expectation without much trouble, but then a new problem
arises: applying the foreign-key-based selectivity rule produces a
rowcount underestimate, because we're effectively double-counting the
selectivity of the "fktab.a = 1" clause. So we have to cancel that
selectivity out of the estimate.
To fix, refactor process_implied_equality() so that it can pass back the
new RestrictInfo to its callers in equivclass.c, allowing the generated
"fktab.a = 1" clause to be saved in the EquivalenceClass's ec_derives
list. Then it's not much trouble to dig out the relevant RestrictInfo
when we need to adjust an FK selectivity estimate. (While at it, we
can also remove the expensive use of initialize_mergeclause_eclasses()
to set up the new RestrictInfo's left_ec and right_ec pointers.
The equivclass.c code can set those basically for free.)
This seems like clearly a bug fix, but I'm hesitant to back-patch it,
first because there's some API/ABI risk for extensions and second because
we're usually loath to destabilize plan choices in stable branches.
Per report from Sigrid Ehrenreich.
Discussion: https://postgr.es/m/1019549.1603770457@sss.pgh.pa.us
Discussion: https://postgr.es/m/AM6PR02MB5287A0ADD936C1FA80973E72AB190@AM6PR02MB5287.eurprd02.prod.outlook.com
nodeSubplan.c expects that the testexpr for a hashable ANY SubPlan
has the form of one or more OpExprs whose LHS is an expression of the
outer query's, while the RHS is an expression over Params representing
output columns of the subquery. However, the planner only went as far
as verifying that the clauses were all binary OpExprs. This works
99.99% of the time, because the clauses have the right shape when
emitted by the parser --- but it's possible for function inlining to
break that, as reported by PegoraroF10. To fix, teach the planner
to check that the LHS and RHS contain the right things, or more
accurately don't contain the wrong things. Given that this has been
broken for years without anyone noticing, it seems sufficient to just
give up hashing when it happens, rather than go to the trouble of
commuting the clauses back again (which wouldn't necessarily work
anyway).
While poking at that, I also noticed that nodeSubplan.c had a baked-in
assumption that the number of hash clauses is identical to the number
of subquery output columns. Again, that's fine as far as parser output
goes, but it's not hard to break it via function inlining. There seems
little reason for that assumption though --- AFAICS, the only thing
it's buying us is not having to store the number of hash clauses
explicitly. Adding code to the planner to reject such cases would take
more code than getting nodeSubplan.c to cope, so I fixed it that way.
This has been broken for as long as we've had hashable SubPlans,
so back-patch to all supported branches.
Discussion: https://postgr.es/m/1549209182255-0.post@n3.nabble.com
Note: This GUC was originally named enable_hashagg_disk when it appeared
in commit 1f39bce0, which added disk-based hash aggregation. It was
subsequently renamed in commit 92c58fd9.
Author: Peter Geoghegan
Reviewed-By: Jeff Davis, Álvaro Herrera
Discussion: https://postgr.es/m/9d9d1e1252a52ea1bad84ea40dbebfd54e672a0f.camel%40j-davis.com
Backpatch: 13-, where disk-based hash aggregation was introduced.
Eliminate enable_groupingsets_hash_disk, which was primarily useful
for testing grouping sets that use HashAgg and spill. Instead, hack
the table stats to convince the planner to choose hashed aggregation
for grouping sets that will spill to disk. Suggested by Melanie
Plageman.
Rename enable_hashagg_disk to hashagg_avoid_disk_plan, and invert the
meaning of on/off. The new name indicates more strongly that it only
affects the planner. Also, the word "avoid" is less definite, which
should avoid surprises when HashAgg still needs to use the
disk. Change suggested by Justin Pryzby, though I chose a different
GUC name.
Discussion: https://postgr.es/m/CAAKRu_aisiENMsPM2gC4oUY1hHG3yrCwY-fXUg22C6_MJUwQdA%40mail.gmail.com
Discussion: https://postgr.es/m/20200610021544.GA14879@telsasoft.com
Backpatch-through: 13
WITH TIES is an option to the FETCH FIRST N ROWS clause (the SQL
standard's spelling of LIMIT), where you additionally get rows that
compare equal to the last of those N rows by the columns in the
mandatory ORDER BY clause.
There was a proposal by Andrew Gierth to implement this functionality in
a more powerful way that would yield more features, but the other patch
had not been finished at this time, so we decided to use this one for
now in the spirit of incremental development.
Author: Surafel Temesgen <surafel3000@gmail.com>
Reviewed-by: Álvaro Herrera <alvherre@alvh.no-ip.org>
Reviewed-by: Tomas Vondra <tomas.vondra@2ndquadrant.com>
Discussion: https://postgr.es/m/CALAY4q9ky7rD_A4vf=FVQvCGngm3LOes-ky0J6euMrg=_Se+ag@mail.gmail.com
Discussion: https://postgr.es/m/87o8wvz253.fsf@news-spur.riddles.org.uk
Commit d2d8a229bc introduced Incremental Sort, but it was considered
only in create_ordered_paths() as an alternative to regular Sort. There
are many other places that require sorted input and might benefit from
considering Incremental Sort too.
This patch modifies a number of those places, but not all. The concern
is that just adding Incremental Sort to any place that already adds
Sort may increase the number of paths considered, negatively affecting
planning time, without any benefit. So we've taken a more conservative
approach, based on analysis of which places do affect a set of queries
that did seem practical. This means some less common queries may not
benefit from Incremental Sort yet.
Author: Tomas Vondra
Reviewed-by: James Coleman
Discussion: https://postgr.es/m/CAPpHfds1waRZ=NOmueYq0sx1ZSCnt+5QJvizT8ndT2=etZEeAQ@mail.gmail.com
Incremental Sort is an optimized variant of multikey sort for cases when
the input is already sorted by a prefix of the requested sort keys. For
example when the relation is already sorted by (key1, key2) and we need
to sort it by (key1, key2, key3) we can simply split the input rows into
groups having equal values in (key1, key2), and only sort/compare the
remaining column key3.
This has a number of benefits:
- Reduced memory consumption, because only a single group (determined by
values in the sorted prefix) needs to be kept in memory. This may also
eliminate the need to spill to disk.
- Lower startup cost, because Incremental Sort produce results after each
prefix group, which is beneficial for plans where startup cost matters
(like for example queries with LIMIT clause).
We consider both Sort and Incremental Sort, and decide based on costing.
The implemented algorithm operates in two different modes:
- Fetching a minimum number of tuples without check of equality on the
prefix keys, and sorting on all columns when safe.
- Fetching all tuples for a single prefix group and then sorting by
comparing only the remaining (non-prefix) keys.
We always start in the first mode, and employ a heuristic to switch into
the second mode if we believe it's beneficial - the goal is to minimize
the number of unnecessary comparions while keeping memory consumption
below work_mem.
This is a very old patch series. The idea was originally proposed by
Alexander Korotkov back in 2013, and then revived in 2017. In 2018 the
patch was taken over by James Coleman, who wrote and rewrote most of the
current code.
There were many reviewers/contributors since 2013 - I've done my best to
pick the most active ones, and listed them in this commit message.
Author: James Coleman, Alexander Korotkov
Reviewed-by: Tomas Vondra, Andreas Karlsson, Marti Raudsepp, Peter Geoghegan, Robert Haas, Thomas Munro, Antonin Houska, Andres Freund, Alexander Kuzmenkov
Discussion: https://postgr.es/m/CAPpHfdscOX5an71nHd8WSUH6GNOCf=V7wgDaTXdDd9=goN-gfA@mail.gmail.com
Discussion: https://postgr.es/m/CAPpHfds1waRZ=NOmueYq0sx1ZSCnt+5QJvizT8ndT2=etZEeAQ@mail.gmail.com
Move have_partkey_equi_join and match_expr_to_partition_keys to
relnode.c, since they're used only there. Refactor
build_joinrel_partition_info to split out the code that fills the
joinrel's partition key lists; this doesn't have any non-cosmetic
impact, but it seems like a useful separation of concerns.
Improve assorted nearby comments.
Amit Langote, with a little further editorialization by me
Discussion: https://postgr.es/m/CA+HiwqG2WVUGmLJqtR0tPFhniO=H=9qQ+Z3L_ZC+Y3-EVQHFGg@mail.gmail.com
This commit adds query_string argument into the planner-related functions
and hook and allows us to pass the query string to them.
Currently there is no user of the query string passed. But the upcoming patch
for the planning counters will add the planning hook function into
pg_stat_statements and the function will need the query string. So this change
will be necessary for that patch.
Also this change is useful for some extensions that want to use the query
string in their planner hook function.
Author: Pascal Legrand, Julien Rouhaud
Reviewed-by: Yoshikazu Imai, Tom Lane, Fujii Masao
Discussion: https://postgr.es/m/CAOBaU_bU1m3_XF5qKYtSj1ua4dxd=FWDyh2SH4rSJAUUfsGmAQ@mail.gmail.com
Discussion: https://postgr.es/m/1583789487074-0.post@n3.nabble.com
While performing hash aggregation, track memory usage when adding new
groups to a hash table. If the memory usage exceeds work_mem, enter
"spill mode".
In spill mode, new groups are not created in the hash table(s), but
existing groups continue to be advanced if input tuples match. Tuples
that would cause a new group to be created are instead spilled to a
logical tape to be processed later.
The tuples are spilled in a partitioned fashion. When all tuples from
the outer plan are processed (either by advancing the group or
spilling the tuple), finalize and emit the groups from the hash
table. Then, create new batches of work from the spilled partitions,
and select one of the saved batches and process it (possibly spilling
recursively).
Author: Jeff Davis
Reviewed-by: Tomas Vondra, Adam Lee, Justin Pryzby, Taylor Vesely, Melanie Plageman
Discussion: https://postgr.es/m/507ac540ec7c20136364b5272acbcd4574aa76ef.camel@j-davis.com
Commit d25ea0127 got rid of what I thought were entirely unnecessary
derived child expressions in EquivalenceClasses for EC members that
mention multiple baserels. But it turns out that some of the child
expressions that code created are necessary for partitionwise joins,
else we fail to find matching pathkeys for Sort nodes. (This happens
only for certain shapes of the resulting plan; it may be that
partitionwise aggregation is also necessary to show the failure,
though I'm not sure of that.)
Reverting that commit entirely would be quite painful performance-wise
for large partition sets. So instead, add code that explicitly
generates child expressions that match only partitionwise child join
rels we have actually generated.
Per report from Justin Pryzby. (Amit Langote noticed the problem
earlier, though it's not clear if he recognized then that it could
result in a planner error, not merely failure to exploit partitionwise
join, in the code as-committed.) Back-patch to v12 where commit
d25ea0127 came in.
Amit Langote, with lots of kibitzing from me
Discussion: https://postgr.es/m/CA+HiwqG2WVUGmLJqtR0tPFhniO=H=9qQ+Z3L_ZC+Y3-EVQHFGg@mail.gmail.com
Discussion: https://postgr.es/m/20191011143703.GN10470@telsasoft.com
Merge setup_append_rel_array into setup_simple_rel_arrays. There's no
particularly good reason to keep them separate, and it's inconsistent
with the lack of separation in expand_planner_arrays. The only apparent
benefit was that the fast path for trivial queries in query_planner()
doesn't need to set up the append_rel_array; but all we're saving there
is an if-test and NULL assignment, which surely ought to be negligible.
Also improve some obsolete comments.
Discussion: https://postgr.es/m/17220.1565301350@sss.pgh.pa.us
This allows simplification of the plan tree in some common usage
patterns: we can get rid of a join to the function RTE.
In principle we could pull up any immutable expression, but restricting
it to Consts avoids the risk that multiple evaluations of the expression
might cost more than we can save. (Possibly this could be improved in
future --- but we've more or less promised people that putting a function
in FROM guarantees single evaluation, so we'd have to tread carefully.)
To do this, we need to rearrange when eval_const_expressions()
happens for expressions in function RTEs. I moved it to
inline_set_returning_functions(), which already has to iterate over
every function RTE, and in consequence renamed that function to
preprocess_function_rtes(). A useful consequence is that
inline_set_returning_function() no longer has to do this for itself,
simplifying that code.
In passing, break out pull_up_simple_subquery's code that knows where
everything that needs pullup_replace_vars() processing is, so that
the new pull_up_constant_function() routine can share it. We'd
gotten away with one-and-a-half copies of that code so far, since
pull_up_simple_values() could assume that a lot of cases didn't apply
to it --- but I don't think pull_up_constant_function() can make any
simplifying assumptions. Might as well make pull_up_simple_values()
use it too.
(Possibly this refactoring should go further: maybe we could share
some of the code to fill in the pullup_replace_vars_context struct?
For now, I left it that the callers fill that completely.)
Note: the one existing test case that this patch changes has to be
changed because inlining its function RTEs would destroy the point
of the test, namely to check join order.
Alexander Kuzmenkov and Aleksandr Parfenov, reviewed by
Antonin Houska and Anastasia Lubennikova, and whacked around
some more by me
Discussion: https://postgr.es/m/402356c32eeb93d4fed01f66d6c7fe2d@postgrespro.ru
If we need ordered output from a scan of a partitioned table, but
the ordering matches the partition ordering, then we don't need to
use a MergeAppend to combine the pre-ordered per-partition scan
results: a plain Append will produce the same results. This
both saves useless comparison work inside the MergeAppend proper,
and allows us to start returning tuples after istarting up just
the first child node not all of them.
However, all is not peaches and cream, because if some of the
child nodes have high startup costs then there will be big
discontinuities in the tuples-returned-versus-elapsed-time curve.
The planner's cost model cannot handle that (yet, anyway).
If we model the Append's startup cost as being just the first
child's startup cost, we may drastically underestimate the cost
of fetching slightly more tuples than are available from the first
child. Since we've had bad experiences with over-optimistic choices
of "fast start" plans for ORDER BY LIMIT queries, that seems scary.
As a klugy workaround, set the startup cost estimate for an ordered
Append to be the sum of its children's startup costs (as MergeAppend
would). This doesn't really describe reality, but it's less likely
to cause a bad plan choice than an underestimated startup cost would.
In practice, the cases where we really care about this optimization
will have child plans that are IndexScans with zero startup cost,
so that the overly conservative estimate is still just zero.
David Rowley, reviewed by Julien Rouhaud and Antonin Houska
Discussion: https://postgr.es/m/CAKJS1f-hAqhPLRk_RaSFTgYxd=Tz5hA7kQ2h4-DhJufQk8TGuw@mail.gmail.com
This just moves the table/matview[/toast] determination of relation
size to a callback, and uses a copy of the existing logic to implement
that callback for heap.
It probably would make sense to also move the index specific logic
into a callback, so the metapage handling (and probably more) can be
index specific. But that's a separate task.
Author: Andres Freund
Discussion: https://postgr.es/m/20180703070645.wchpu5muyto5n647@alap3.anarazel.de
Previously, the planner created RangeTblEntry and RelOptInfo structs
for every partition of a partitioned table, even though many of them
might later be deemed uninteresting thanks to partition pruning logic.
This incurred significant overhead when there are many partitions.
Arrange to postpone creation of these data structures until after
we've processed the query enough to identify restriction quals for
the partitioned table, and then apply partition pruning before not
after creation of each partition's data structures. In this way
we need not open the partition relations at all for partitions that
the planner has no real interest in.
For queries that can be proven at plan time to access only a small
number of partitions, this patch improves the practical maximum
number of partitions from under 100 to perhaps a few thousand.
Amit Langote, reviewed at various times by Dilip Kumar, Jesper Pedersen,
Yoshikazu Imai, and David Rowley
Discussion: https://postgr.es/m/9d7c5112-cb99-6a47-d3be-cf1ee6862a1d@lab.ntt.co.jp
This is an SQL-standard feature that allows creating columns that are
computed from expressions rather than assigned, similar to a view or
materialized view but on a column basis.
This implements one kind of generated column: stored (computed on
write). Another kind, virtual (computed on read), is planned for the
future, and some room is left for it.
Reviewed-by: Michael Paquier <michael@paquier.xyz>
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/b151f851-4019-bdb1-699e-ebab07d2f40a@2ndquadrant.com
Introduce a third extended statistic type, supported by the CREATE
STATISTICS command - MCV lists, a generalization of the statistic
already built and used for individual columns.
Compared to the already supported types (n-distinct coefficients and
functional dependencies), MCV lists are more complex, include column
values and allow estimation of much wider range of common clauses
(equality and inequality conditions, IS NULL, IS NOT NULL etc.).
Similarly to the other types, a new pseudo-type (pg_mcv_list) is used.
Author: Tomas Vondra
Reviewed-by: Dean Rasheed, David Rowley, Mark Dilger, Alvaro Herrera
Discussion: https://postgr.es/m/dfdac334-9cf2-2597-fb27-f0fb3753f435@2ndquadrant.com
In the dim past, the planner kept the fully-processed version of the query
targetlist (the result of preprocess_targetlist) in grouping_planner's
local variable "tlist", and only grudgingly passed it to individual other
routines as needed. Later we discovered a need to still have it available
after grouping_planner finishes, and invented the root->processed_tlist
field for that purpose, but it wasn't used internally to grouping_planner;
the tlist was still being passed around separately in the same places as
before.
Now comes a proposed patch to allow appendrel expansion to add entries
to the processed tlist, well after preprocess_targetlist has finished
its work. To avoid having to pass around the tlist explicitly, it's
proposed to allow appendrel expansion to modify root->processed_tlist.
That makes aliasing the tlist with assorted parameters and local
variables really scary. It would accidentally work as long as the
tlist is initially nonempty, because then the List header won't move
around, but it's not exactly hard to think of ways for that to break.
Aliased values are poor programming practice anyway.
Hence, get rid of local variables and parameters that can be identified
with root->processed_tlist, in favor of just using that field directly.
And adjust comments to match. (Some of the new comments speak as though
it's already possible for appendrel expansion to modify the tlist; that's
not true yet, but will happen in a later patch.)
Discussion: https://postgr.es/m/9d7c5112-cb99-6a47-d3be-cf1ee6862a1d@lab.ntt.co.jp
Up to now, otherrel RelOptInfos were built at the same time as baserel
RelOptInfos, thanks to recursion in build_simple_rel(). However,
nothing in query_planner's preprocessing cares at all about otherrels,
only baserels, so we don't really need to build them until just before
we enter make_one_rel. This has two benefits:
* create_lateral_join_info did a lot of extra work to propagate
lateral-reference information from parents to the correct children.
But if we delay creation of the children till after that, it's
trivial (and much harder to break, too).
* Since we have all the restriction quals correctly assigned to
parent appendrels by this point, it'll be possible to do plan-time
pruning and never make child RelOptInfos at all for partitions that
can be pruned away. That's not done here, but will be later on.
Amit Langote, reviewed at various times by Dilip Kumar, Jesper Pedersen,
Yoshikazu Imai, and David Rowley
Discussion: https://postgr.es/m/9d7c5112-cb99-6a47-d3be-cf1ee6862a1d@lab.ntt.co.jp
This adds a flag "deterministic" to collations. If that is false,
such a collation disables various optimizations that assume that
strings are equal only if they are byte-wise equal. That then allows
use cases such as case-insensitive or accent-insensitive comparisons
or handling of strings with different Unicode normal forms.
This functionality is only supported with the ICU provider. At least
glibc doesn't appear to have any locales that work in a
nondeterministic way, so it's not worth supporting this for the libc
provider.
The term "deterministic comparison" in this context is from Unicode
Technical Standard #10
(https://unicode.org/reports/tr10/#Deterministic_Comparison).
This patch makes changes in three areas:
- CREATE COLLATION DDL changes and system catalog changes to support
this new flag.
- Many executor nodes and auxiliary code are extended to track
collations. Previously, this code would just throw away collation
information, because the eventually-called user-defined functions
didn't use it since they only cared about equality, which didn't
need collation information.
- String data type functions that do equality comparisons and hashing
are changed to take the (non-)deterministic flag into account. For
comparison, this just means skipping various shortcuts and tie
breakers that use byte-wise comparison. For hashing, we first need
to convert the input string to a canonical "sort key" using the ICU
analogue of strxfrm().
Reviewed-by: Daniel Verite <daniel@manitou-mail.org>
Reviewed-by: Peter Geoghegan <pg@bowt.ie>
Discussion: https://www.postgresql.org/message-id/flat/1ccc668f-4cbc-0bef-af67-450b47cdfee7@2ndquadrant.com
When we introduced separate ProjectSetPath nodes for application of
set-returning functions in v10, we inadvertently broke some cases where
we're supposed to recognize that the result of a subquery is known to be
empty (contain zero rows). That's because IS_DUMMY_REL was just looking
for a childless AppendPath without allowing for a ProjectSetPath being
possibly stuck on top. In itself, this didn't do anything much worse
than produce slightly worse plans for some corner cases.
Then in v11, commit 11cf92f6e rearranged things to allow the scan/join
targetlist to be applied directly to partial paths before they get
gathered. But it inserted a short-circuit path for dummy relations
that was a little too short: it failed to insert a ProjectSetPath node
at all for a targetlist containing set-returning functions, resulting in
bogus "set-valued function called in context that cannot accept a set"
errors, as reported in bug #15669 from Madelaine Thibaut.
The best way to fix this mess seems to be to reimplement IS_DUMMY_REL
so that it drills down through any ProjectSetPath nodes that might be
there (and it seems like we'd better allow for ProjectionPath as well).
While we're at it, make it look at rel->pathlist not cheapest_total_path,
so that it gives the right answer independently of whether set_cheapest
has been done lately. That dependency looks pretty shaky in the context
of code like apply_scanjoin_target_to_paths, and even if it's not broken
today it'd certainly bite us at some point. (Nastily, unsafe use of the
old coding would almost always work; the hazard comes down to possibly
looking through a dangling pointer, and only once in a blue moon would
you find something there that resulted in the wrong answer.)
It now looks like it was a mistake for IS_DUMMY_REL to be a macro: if
there are any extensions using it, they'll continue to use the old
inadequate logic until they're recompiled, after which they'll fail
to load into server versions predating this fix. Hopefully there are
few such extensions.
Having fixed IS_DUMMY_REL, the special path for dummy rels in
apply_scanjoin_target_to_paths is unnecessary as well as being wrong,
so we can just drop it.
Also change a few places that were testing for partitioned-ness of a
planner relation but not using IS_PARTITIONED_REL for the purpose; that
seems unsafe as well as inconsistent, plus it required an ugly hack in
apply_scanjoin_target_to_paths.
In passing, save a few cycles in apply_scanjoin_target_to_paths by
skipping processing of pre-existing paths for partitioned rels,
and do some cosmetic cleanup and comment adjustment in that function.
I renamed IS_DUMMY_PATH to IS_DUMMY_APPEND with the intention of breaking
any code that might be using it, since in almost every case that would
be wrong; IS_DUMMY_REL is what to be using instead.
In HEAD, also make set_dummy_rel_pathlist static (since it's no longer
used from outside allpaths.c), and delete is_dummy_plan, since it's no
longer used anywhere.
Back-patch as appropriate into v11 and v10.
Tom Lane and Julien Rouhaud
Discussion: https://postgr.es/m/15669-02fb3296cca26203@postgresql.org
For a long time, indxpath.c has had the ability to extract derived (lossy)
index conditions from certain operators such as LIKE. For just as long,
it's been obvious that we really ought to make that capability available
to extensions. This commit finally accomplishes that, by adding another
API for planner support functions that lets them create derived index
conditions for their functions. As proof of concept, the hardwired
"special index operator" code formerly present in indxpath.c is pushed
out to planner support functions attached to LIKE and other relevant
operators.
A weak spot in this design is that an extension needs to know OIDs for
the operators, datatypes, and opfamilies involved in the transformation
it wants to make. The core-code prototypes use hard-wired OID references
but extensions don't have that option for their own operators etc. It's
usually possible to look up the required info, but that may be slow and
inconvenient. However, improving that situation is a separate task.
I want to do some additional refactorization around selfuncs.c, but
that also seems like a separate task.
Discussion: https://postgr.es/m/15193.1548028093@sss.pgh.pa.us
Add support function requests for estimating the selectivity, cost,
and number of result rows (if a SRF) of the target function.
The lack of a way to estimate selectivity of a boolean-returning
function in WHERE has been a recognized deficiency of the planner
since Berkeley days. This commit finally fixes it.
In addition, non-constant estimates of cost and number of output
rows are now possible. We still fall back to looking at procost
and prorows if the support function doesn't service the request,
of course.
To make concrete use of the possibility of estimating output rowcount
for SRFs, this commit adds support functions for array_unnest(anyarray)
and the integer variants of generate_series; the lack of plausible
rowcount estimates for those, even when it's obvious to a human,
has been a repeated subject of complaints. Obviously, much more
could now be done in this line, but I'm mostly just trying to get
the infrastructure in place.
Discussion: https://postgr.es/m/15193.1548028093@sss.pgh.pa.us
In place of three separate but interrelated lists (indexclauses,
indexquals, and indexqualcols), an IndexPath now has one list
"indexclauses" of IndexClause nodes. This holds basically the same
information as before, but in a more useful format: in particular, there
is now a clear connection between an indexclause (an original restriction
clause from WHERE or JOIN/ON) and the indexquals (directly usable index
conditions) derived from it.
We also change the ground rules a bit by mandating that clause commutation,
if needed, be done up-front so that what is stored in the indexquals list
is always directly usable as an index condition. This gets rid of repeated
re-determination of which side of the clause is the indexkey during costing
and plan generation, as well as repeated lookups of the commutator
operator. To minimize the added up-front cost, the typical case of
commuting a plain OpExpr is handled by a new special-purpose function
commute_restrictinfo(). For RowCompareExprs, generating the new clause
properly commuted to begin with is not really any more complex than before,
it's just different --- and we can save doing that work twice, as the
pretty-klugy original implementation did.
Tracking the connection between original and derived clauses lets us
also track explicitly whether the derived clauses are an exact or lossy
translation of the original. This provides a cheap solution to getting
rid of unnecessary rechecks of boolean index clauses, which previously
seemed like it'd be more expensive than it was worth.
Another pleasant (IMO) side-effect is that EXPLAIN now always shows
index clauses with the indexkey on the left; this seems less confusing.
This commit leaves expand_indexqual_conditions() and some related
functions in a slightly messy state. I didn't bother to change them
any more than minimally necessary to work with the new data structure,
because all that code is going to be refactored out of existence in
a follow-on patch.
Discussion: https://postgr.es/m/22182.1549124950@sss.pgh.pa.us
Up to now postgres_fdw has been using create_foreignscan_path() to
generate not only base-relation paths, but also paths for foreign joins
and foreign upperrels. This is wrong, because create_foreignscan_path()
calls get_baserel_parampathinfo() which will only do the right thing for
baserels. It accidentally fails to fail for unparameterized paths, which
are the only ones postgres_fdw (thought it) was handling, but we really
need different APIs for the baserel and join cases.
In HEAD, the best thing to do seems to be to split up the baserel,
joinrel, and upperrel cases into three functions so that they can
have different APIs. I haven't actually given create_foreign_join_path
a different API in this commit: we should spend a bit of time thinking
about just what we want to do there, since perhaps FDWs would want to
do something different from the build-up-a-join-pairwise approach that
get_joinrel_parampathinfo expects. In the meantime, since postgres_fdw
isn't prepared to generate parameterized joins anyway, just give it a
defense against trying to plan joins with lateral refs.
In addition (and this is what triggered this whole mess) fix bug #15613
from Srinivasan S A, by teaching file_fdw and postgres_fdw that plain
baserel foreign paths still have outer refs if the relation has
lateral_relids. Add some assertions in relnode.c to catch future
occurrences of the same error --- in particular, to catch other FDWs
doing that, but also as backstop against core-code mistakes like the
one fixed by commit bdd9a99aa.
Bug #15613 also needs to be fixed in the back branches, but the
appropriate fix will look quite a bit different there, since we don't
want to assume that existing FDWs get the word right away.
Discussion: https://postgr.es/m/15613-092be1be9576c728@postgresql.org
The old name of this file was never a very good indication of what it
was for. Now that there's also access/relation.h, we have a potential
confusion hazard as well, so let's rename it to something more apropos.
Per discussion, "pathnodes.h" is reasonable, since a good fraction of
the file is Path node definitions.
While at it, tweak a couple of other headers that were gratuitously
importing relation.h into modules that don't need it.
Discussion: https://postgr.es/m/7719.1548688728@sss.pgh.pa.us
Create a new header optimizer/optimizer.h, which exposes just the
planner functions that can be used "at arm's length", without need
to access Paths or the other planner-internal data structures defined
in nodes/relation.h. This is intended to provide the whole planner
API seen by most of the rest of the system; although FDWs still need
to use additional stuff, and more thought is also needed about just
what selfuncs.c should rely on.
The main point of doing this now is to limit the amount of new
#include baggage that will be needed by "planner support functions",
which I expect to introduce later, and which will be in relevant
datatype modules rather than anywhere near the planner.
This commit just moves relevant declarations into optimizer.h from
other header files (a couple of which go away because everything
got moved), and adjusts #include lists to match. There's further
cleanup that could be done if we want to decide that some stuff
being exposed by optimizer.h doesn't belong in the planner at all,
but I'll leave that for another day.
Discussion: https://postgr.es/m/11460.1548706639@sss.pgh.pa.us
Move a few very simple node-creation and node-type-testing functions
from the planner's clauses.c to nodes/makefuncs and nodes/nodeFuncs.
There's nothing planner-specific about them, as evidenced by the
number of other places that were using them.
While at it, rename and_clause() etc to is_andclause() etc, to clarify
that they are node-type-testing functions not node-creation functions.
And use "static inline" implementations for the shortest ones.
Also, modify flatten_join_alias_vars() and some subsidiary functions
to take a Query not a PlannerInfo to define the join structure that
Vars should be translated according to. They were only using the
"parse" field of the PlannerInfo anyway, so this just requires removing
one level of indirection. The advantage is that now parse_agg.c can
use flatten_join_alias_vars() without the horrid kluge of creating an
incomplete PlannerInfo, which will allow that file to be decoupled from
relation.h in a subsequent patch.
Discussion: https://postgr.es/m/11460.1548706639@sss.pgh.pa.us
The fact that "SELECT expression" has no base relations has long been a
thorn in the side of the planner. It makes it hard to flatten a sub-query
that looks like that, or is a trivial VALUES() item, because the planner
generally uses relid sets to identify sub-relations, and such a sub-query
would have an empty relid set if we flattened it. prepjointree.c contains
some baroque logic that works around this in certain special cases --- but
there is a much better answer. We can replace an empty FROM clause with a
dummy RTE that acts like a table of one row and no columns, and then there
are no such corner cases to worry about. Instead we need some logic to
get rid of useless dummy RTEs, but that's simpler and covers more cases
than what was there before.
For really trivial cases, where the query is just "SELECT expression" and
nothing else, there's a hazard that adding the extra RTE makes for a
noticeable slowdown; even though it's not much processing, there's not
that much for the planner to do overall. However testing says that the
penalty is very small, close to the noise level. In more complex queries,
this is able to find optimizations that we could not find before.
The new RTE type is called RTE_RESULT, since the "scan" plan type it
gives rise to is a Result node (the same plan we produced for a "SELECT
expression" query before). To avoid confusion, rename the old ResultPath
path type to GroupResultPath, reflecting that it's only used in degenerate
grouping cases where we know the query produces just one grouped row.
(It wouldn't work to unify the two cases, because there are different
rules about where the associated quals live during query_planner.)
Note: although this touches readfuncs.c, I don't think a catversion
bump is required, because the added case can't occur in stored rules,
only plans.
Patch by me, reviewed by David Rowley and Mark Dilger
Discussion: https://postgr.es/m/15944.1521127664@sss.pgh.pa.us
Previously, only literals were allowed. This change allows general
expressions, including functions calls, which are evaluated at the
time the DDL command is executed.
Besides offering some more functionality, it simplifies the parser
structures and removes some inconsistencies in how the literals were
handled.
Author: Kyotaro Horiguchi, Tom Lane, Amit Langote
Reviewed-by: Peter Eisentraut <peter.eisentraut@2ndquadrant.com>
Discussion: https://www.postgresql.org/message-id/flat/9f88b5e0-6da2-5227-20d0-0d7012beaa1c@lab.ntt.co.jp/
Up to now, createplan.c attempted to share PARAM_EXEC slots for
NestLoopParams across different plan levels, if the same underlying Var
was being fed down to different righthand-side subplan trees by different
NestLoops. This was, I think, more of an artifact of using subselect.c's
PlannerParamItem infrastructure than an explicit design goal, but anyway
that was the end result.
This works well enough as long as the plan tree is executing synchronously,
but the feature whereby Gather can execute the parallelized subplan locally
breaks it. An upper NestLoop node might execute for a row retrieved from
a parallel worker, and assign a value for a PARAM_EXEC slot from that row,
while the leader's copy of the parallelized subplan is suspended with a
different active value of the row the Var comes from. When control
eventually returns to the leader's subplan, it gets the wrong answers if
the same PARAM_EXEC slot is being used within the subplan, as reported
in bug #15577 from Bartosz Polnik.
This is pretty reminiscent of the problem fixed in commit 46c508fbc, and
the proper fix seems to be the same: don't try to share PARAM_EXEC slots
across different levels of controlling NestLoop nodes.
This requires decoupling NestLoopParam handling from PlannerParamItem
handling, although the logic remains somewhat similar. To avoid bizarre
division of labor between subselect.c and createplan.c, I decided to move
all the param-slot-assignment logic for both cases out of those files
and put it into a new file paramassign.c. Hopefully it's a bit better
documented now, too.
A regression test case for this might be nice, but we don't know a
test case that triggers the problem with a suitably small amount
of data.
Back-patch to 9.6 where we added Gather nodes. It's conceivable that
related problems exist in older branches; but without some evidence
for that, I'll leave the older branches alone.
Discussion: https://postgr.es/m/15577-ca61ab18904af852@postgresql.org
Avoid using "typeid" as a parameter name in header files, since that
is a C++ keyword. These cases were introduced recently, in 04fe805a1
and 586b98fdf.
Since I'm an incurable neatnik, also rename these parameters in the
underlying function definitions. That's not really necessary per
project rules, but I don't like function declarations that don't
quite agree with the underlying definitions.
Per src/tools/pginclude/cpluspluscheck.
This commit moves expand_inherited_tables and underlings from
optimizer/prep/prepunionc.c to optimizer/utils/inherit.c.
Also, all of the AppendRelInfo-based expression manipulation routines
are moved to optimizer/utils/appendinfo.c.
No functional code changes. One exception is the introduction of
make_append_rel_info, but that's still just moving around code.
Also, stop including <limits.h> in prepunion.c, which no longer needs
it since 3fc6e2d7f5. I (Álvaro) noticed this because Amit was copying
that to inherit.c, which likewise doesn't need it.
Author: Amit Langote
Discussion: https://postgr.es/m/3be67028-a00a-502c-199a-da00eec8fb6e@lab.ntt.co.jp
If a domain has no constraints, then CoerceToDomain doesn't really do
anything and can be simplified to a RelabelType. This not only
eliminates cycles at execution, but allows the planner to optimize better
(for instance, match the coerced expression to an index on the underlying
column). However, we do have to support invalidating the plan later if
a constraint gets added to the domain. That's comparable to the case of
a change to a SQL function that had been inlined into a plan, so all the
necessary logic already exists for plans depending on functions. We
need only duplicate or share that logic for domains.
ALTER DOMAIN ADD/DROP CONSTRAINT need to be taught to send out sinval
messages for the domain's pg_type entry, since those operations don't
update that row. (ALTER DOMAIN SET/DROP NOT NULL do update that row,
so no code change is needed for them.)
Testing this revealed what's really a pre-existing bug in plpgsql:
it caches the SQL-expression-tree expansion of type coercions and
had no provision for invalidating entries in that cache. Up to now
that was only a problem if such an expression had inlined a SQL
function that got changed, which is unlikely though not impossible.
But failing to track changes of domain constraints breaks an existing
regression test case and would likely cause practical problems too.
We could fix that locally in plpgsql, but what seems like a better
idea is to build some generic infrastructure in plancache.c to store
standalone expressions and track invalidation events for them.
(It's tempting to wonder whether plpgsql's "simple expression" stuff
could use this code with lower overhead than its current use of the
heavyweight plancache APIs. But I've left that idea for later.)
Other stuff fixed in passing:
* Allow estimate_expression_value() to drop CoerceToDomain
unconditionally, effectively assuming that the coercion will succeed.
This will improve planner selectivity estimates for cases involving
estimatable expressions that are coerced to domains. We could have
done this independently of everything else here, but there wasn't
previously any need for eval_const_expressions_mutator to know about
CoerceToDomain at all.
* Use a dlist for plancache.c's list of cached plans, rather than a
manually threaded singly-linked list. That eliminates a potential
performance problem in DropCachedPlan.
* Fix a couple of inconsistencies in typecmds.c about whether
operations on domains drop RowExclusiveLock on pg_type. Our common
practice is that DDL operations do drop catalog locks, so standardize
on that choice.
Discussion: https://postgr.es/m/19958.1544122124@sss.pgh.pa.us
postgres_fdw's postgresGetForeignPlan() assumes without checking that the
outer_plan it's given for a join relation must have a NestLoop, MergeJoin,
or HashJoin node at the top. That's been wrong at least since commit
4bbf6edfb (which could cause insertion of a Sort node on top) and it seems
like a pretty unsafe thing to Just Assume even without that.
Through blind good fortune, this doesn't seem to have any worse
consequences today than strange EXPLAIN output, but it's clearly trouble
waiting to happen.
To fix, test the node type explicitly before touching Join-specific
fields, and avoid jamming the new tlist into a node type that can't
do projection. Export a new support function from createplan.c
to avoid building low-level knowledge about the latter into FDWs.
Back-patch to 9.6 where the faulty coding was added. Note that the
associated regression test cases don't show any changes before v11,
apparently because the tests back-patched with 4bbf6edfb don't actually
exercise the problem case before then (there's no top-level Sort
in those plans).
Discussion: https://postgr.es/m/8946.1544644803@sss.pgh.pa.us
In the wake of commit f2343653f, we no longer need some fields that
were used before to control executor lock acquisitions:
* PlannedStmt.nonleafResultRelations can go away entirely.
* partitioned_rels can go away from Append, MergeAppend, and ModifyTable.
However, ModifyTable still needs to know the RT index of the partition
root table if any, which was formerly kept in the first entry of that
list. Add a new field "rootRelation" to remember that. rootRelation is
partly redundant with nominalRelation, in that if it's set it will have
the same value as nominalRelation. However, the latter field has a
different purpose so it seems best to keep them distinct.
Amit Langote, reviewed by David Rowley and Jesper Pedersen,
and whacked around a bit more by me
Discussion: https://postgr.es/m/468c85d9-540e-66a2-1dde-fec2b741e688@lab.ntt.co.jp
Allowing sub-select containing LIMIT/OFFSET in workers can lead to
inconsistent results at the top-level as there is no guarantee that the
row order will be fully deterministic. The fix is to prohibit pushing
LIMIT/OFFSET within sub-selects to workers.
Reported-by: Andrew Fletcher
Bug: 15324
Author: Amit Kapila
Reviewed-by: Dilip Kumar
Backpatch-through: 9.6
Discussion: https://postgr.es/m/153417684333.10284.11356259990921828616@wrigleys.postgresql.org
nodeWindowAgg.c failed to cope with the possibility that no ordering
columns are defined in the window frame for GROUPS mode or RANGE OFFSET
mode, leading to assertion failures or odd errors, as reported by Masahiko
Sawada and Lukas Eder. In RANGE OFFSET mode, an ordering column is really
required, so add an Assert about that. In GROUPS mode, the code would
work, except that the node initialization code wasn't in sync with the
execution code about when to set up tuplestore read pointers and spare
slots. Fix the latter for consistency's sake (even though I think the
changes described below make the out-of-sync cases unreachable for now).
Per SQL spec, a single ordering column is required for RANGE OFFSET mode,
and at least one ordering column is required for GROUPS mode. The parser
enforced the former but not the latter; add a check for that.
We were able to reach the no-ordering-column cases even with fully spec
compliant queries, though, because the planner would drop partitioning
and ordering columns from the generated plan if they were redundant with
earlier columns according to the redundant-pathkey logic, for instance
"PARTITION BY x ORDER BY y" in the presence of a "WHERE x=y" qual.
While in principle that's an optimization that could save some pointless
comparisons at runtime, it seems unlikely to be meaningful in the real
world. I think this behavior was not so much an intentional optimization
as a side-effect of an ancient decision to construct the plan node's
ordering-column info by reverse-engineering the PathKeys of the input
path. If we give up redundant-column removal then it takes very little
code to generate the plan node info directly from the WindowClause,
ensuring that we have the expected number of ordering columns in all
cases. (If anyone does complain about this, the planner could perhaps
be taught to remove redundant columns only when it's safe to do so,
ie *not* in RANGE OFFSET mode. But I doubt anyone ever will.)
With these changes, the WindowAggPath.winpathkeys field is not used for
anything anymore, so remove it.
The test cases added here are not actually very interesting given the
removal of the redundant-column-removal logic, but they would represent
important corner cases if anyone ever tries to put that back.
Tom Lane and Masahiko Sawada. Back-patch to v11 where RANGE OFFSET
and GROUPS modes were added.
Discussion: https://postgr.es/m/CAD21AoDrWqycq-w_+Bx1cjc+YUhZ11XTj9rfxNiNDojjBx8Fjw@mail.gmail.com
Discussion: https://postgr.es/m/153086788677.17476.8002640580496698831@wrigleys.postgresql.org
find_appinfos_by_relids had quite a large overhead when the number of
items in the append_rel_list was high, as it had to trawl through the
append_rel_list looking for AppendRelInfos belonging to the given
childrelids. Since there can only be a single AppendRelInfo for each
child rel, it seems much better to store an array in PlannerInfo which
indexes these by child relid, making the function O(1) rather than O(N).
This function was only called once inside the planner, so just replace
that call with a lookup to the new array. find_childrel_appendrelinfo
is now unused and thus removed.
This fixes a planner performance regression new to v11 reported by
Thomas Reiss.
Author: David Rowley
Reported-by: Thomas Reiss
Reviewed-by: Ashutosh Bapat
Reviewed-by: Álvaro Herrera
Discussion: https://postgr.es/m/94dd7a4b-5e50-0712-911d-2278e055c622@dalibo.com
This controls both plan-time and execution-time new-style partition
pruning. While finer-grain control is possible (maybe using an enum GUC
instead of boolean), there doesn't seem to be much need for that.
This new parameter controls partition pruning for all queries:
trivially, SELECT queries that affect partitioned tables are naturally
under its control since they are using the new technology. However,
while UPDATE/DELETE queries do not use the new code, we make the new GUC
control their behavior also (stealing control from
constraint_exclusion), because it is more natural, and it leads to a
more natural transition to the future in which those queries will also
use the new pruning code.
Constraint exclusion still controls pruning for regular inheritance
situations (those not involving partitioned tables).
Author: David Rowley
Review: Amit Langote, Ashutosh Bapat, Justin Pryzby, David G. Johnston
Discussion: https://postgr.es/m/CAKJS1f_0HwsxJG9m+nzU+CizxSdGtfe6iF_ykPYBiYft302DCw@mail.gmail.com
On further reflection, commit e5d83995e didn't go far enough: pretty much
everywhere in the planner that examines a clause's is_pushed_down flag
ought to be changed to use the more complicated behavior where we also
check the clause's required_relids. Otherwise we could make incorrect
decisions about whether, say, a clause is safe to use as a hash clause.
Some (many?) of these places are safe as-is, either because they are
never reached while considering a parameterized path, or because there
are additional checks that would reject a pushed-down clause anyway.
However, it seems smarter to just code them all the same way rather
than rely on easily-broken reasoning of that sort.
In support of that, invent a new macro RINFO_IS_PUSHED_DOWN that should
be used in place of direct tests on the is_pushed_down flag.
Like the previous patch, back-patch to all supported branches.
Discussion: https://postgr.es/m/f8128b11-c5bf-3539-48cd-234178b2314d@proxel.se
In some cases a clause attached to an outer join can be pushed down into
the outer join's RHS even though the clause is not degenerate --- this
can happen if we choose to make a parameterized path for the RHS. If
the clause ends up attached to a lower outer join, we'd misclassify it
as being a "join filter" not a plain "filter" condition at that node,
leading to wrong query results.
To fix, teach extract_actual_join_clauses to examine each join clause's
required_relids, not just its is_pushed_down flag. (The latter now
seems vestigial, or at least in need of rethinking, but we won't do
anything so invasive as redefining it in a bug-fix patch.)
This has been wrong since we introduced parameterized paths in 9.2,
though it's evidently hard to hit given the lack of previous reports.
The test case used here involves a lateral function call, and I think
that a lateral reference may be required to get the planner to select
a broken plan; though I wouldn't swear to that. In any case, even if
LATERAL is needed to trigger the bug, it still affects all supported
branches, so back-patch to all.
Per report from Andreas Karlsson. Thanks to Andrew Gierth for
preliminary investigation.
Discussion: https://postgr.es/m/f8128b11-c5bf-3539-48cd-234178b2314d@proxel.se
We need to call expand_function_arguments() to expand named and default
arguments.
In PL/pgSQL, we also need to deal with named and default INOUT arguments
when receiving the output values into variables.
Author: Pavel Stehule <pavel.stehule@gmail.com>
This reverts commits d204ef6377,
83454e3c2b and a few more commits thereafter
(complete list at the end) related to MERGE feature.
While the feature was fully functional, with sufficient test coverage and
necessary documentation, it was felt that some parts of the executor and
parse-analyzer can use a different design and it wasn't possible to do that in
the available time. So it was decided to revert the patch for PG11 and retry
again in the future.
Thanks again to all reviewers and bug reporters.
List of commits reverted, in reverse chronological order:
f1464c5380 Improve parse representation for MERGE
ddb4158579 MERGE syntax diagram correction
530e69e59b Allow cpluspluscheck to pass by renaming variable
01b88b4df5 MERGE minor errata
3af7b2b0d4 MERGE fix variable warning in non-assert builds
a5d86181ec MERGE INSERT allows only one VALUES clause
4b2d44031f MERGE post-commit review
4923550c20 Tab completion for MERGE
aa3faa3c7a WITH support in MERGE
83454e3c2b New files for MERGE
d204ef6377 MERGE SQL Command following SQL:2016
Author: Pavan Deolasee
Reviewed-by: Michael Paquier
Existing partition pruning is only able to work at plan time, for query
quals that appear in the parsed query. This is good but limiting, as
there can be parameters that appear later that can be usefully used to
further prune partitions.
This commit adds support for pruning subnodes of Append which cannot
possibly contain any matching tuples, during execution, by evaluating
Params to determine the minimum set of subnodes that can possibly match.
We support more than just simple Params in WHERE clauses. Support
additionally includes:
1. Parameterized Nested Loop Joins: The parameter from the outer side of the
join can be used to determine the minimum set of inner side partitions to
scan.
2. Initplans: Once an initplan has been executed we can then determine which
partitions match the value from the initplan.
Partition pruning is performed in two ways. When Params external to the plan
are found to match the partition key we attempt to prune away unneeded Append
subplans during the initialization of the executor. This allows us to bypass
the initialization of non-matching subplans meaning they won't appear in the
EXPLAIN or EXPLAIN ANALYZE output.
For parameters whose value is only known during the actual execution
then the pruning of these subplans must wait. Subplans which are
eliminated during this stage of pruning are still visible in the EXPLAIN
output. In order to determine if pruning has actually taken place, the
EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never
executed due to the elimination of the partition then the execution
timing area will state "(never executed)". Whereas, if, for example in
the case of parameterized nested loops, the number of loops stated in
the EXPLAIN ANALYZE output for certain subplans may appear lower than
others due to the subplan having been scanned fewer times. This is due
to the list of matching subnodes having to be evaluated whenever a
parameter which was found to match the partition key changes.
This commit required some additional infrastructure that permits the
building of a data structure which is able to perform the translation of
the matching partition IDs, as returned by get_matching_partitions, into
the list index of a subpaths list, as exist in node types such as
Append, MergeAppend and ModifyTable. This allows us to translate a list
of clauses into a Bitmapset of all the subpath indexes which must be
included to satisfy the clause list.
Author: David Rowley, based on an earlier effort by Beena Emerson
Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi,
Jesper Pedersen
Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
Add a new module backend/partitioning/partprune.c, implementing a more
sophisticated algorithm for partition pruning. The new module uses each
partition's "boundinfo" for pruning instead of constraint exclusion,
based on an idea proposed by Robert Haas of a "pruning program": a list
of steps generated from the query quals which are run iteratively to
obtain a list of partitions that must be scanned in order to satisfy
those quals.
At present, this targets planner-time partition pruning, but there exist
further patches to apply partition pruning at execution time as well.
This commit also moves some definitions from include/catalog/partition.h
to a new file include/partitioning/partbounds.h, in an attempt to
rationalize partitioning related code.
Authors: Amit Langote, David Rowley, Dilip Kumar
Reviewers: Robert Haas, Kyotaro Horiguchi, Ashutosh Bapat, Jesper Pedersen.
Discussion: https://postgr.es/m/098b9c71-1915-1a2a-8d52-1a7a50ce79e8@lab.ntt.co.jp
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 other require multiple PL statements.
e.g.
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 and partitioned tables, including
column and row security enforcement, as well as support for
row, statement and transition triggers.
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 statically from PL/pgSQL.
MERGE does not yet support inheritance, write rules,
RETURNING clauses, updatable views or foreign tables.
MERGE follows SQL Standard per the most recent SQL:2016.
Includes full tests and documentation, including full
isolation tests to demonstrate the concurrent behavior.
This version written from scratch in 2017 by Simon Riggs,
using docs and tests originally written in 2009. Later work
from Pavan Deolasee has been both complex and deep, leaving
the lead author credit now in his hands.
Extensive discussion of concurrency from Peter Geoghegan,
with thanks for the time and effort contributed.
Various issues reported via sqlsmith by Andreas Seltenreich
Authors: Pavan Deolasee, Simon Riggs
Reviewer: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs
Discussion:
https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.comhttps://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
Since commit 7012b132d0, postgres_fdw
has been able to push down the toplevel aggregation operation to the
remote server. Commit e2f1eb0ee3 made
it possible to break down the toplevel aggregation into one
aggregate per partition. This commit lets postgres_fdw push down
aggregation in that case just as it does at the top level.
In order to make this work, this commit adds an additional argument
to the GetForeignUpperPaths FDW API. A matching argument is added
to the signature for create_upper_paths_hook. Third-party code using
either of these will need to be updated.
Also adjust create_foreignscan_plan() so that it picks up the correct
set of relids in this case.
Jeevan Chalke, reviewed by Ashutosh Bapat and by me and with some
adjustments by me. The larger patch series of which this patch is a
part was also reviewed and tested by Antonin Houska, Rajkumar
Raghuwanshi, David Rowley, Dilip Kumar, Konstantin Knizhnik, Pascal
Legrand, and Rafia Sabih.
Discussion: http://postgr.es/m/CAM2+6=V64_xhstVHie0Rz=KPEQnLJMZt_e314P0jaT_oJ9MR8A@mail.gmail.com
Discussion: http://postgr.es/m/CAM2+6=XPWujjmj5zUaBTGDoB38CemwcPmjkRy0qOcsQj_V+2sQ@mail.gmail.com
If the partition keys of input relation are part of the GROUP BY
clause, all the rows belonging to a given group come from a single
partition. This allows aggregation/grouping over a partitioned
relation to be broken down * into aggregation/grouping on each
partition. This should be no worse, and often better, than the normal
approach.
If the GROUP BY clause does not contain all the partition keys, we can
still perform partial aggregation for each partition and then finalize
aggregation after appending the partial results. This is less certain
to be a win, but it's still useful.
Jeevan Chalke, Ashutosh Bapat, Robert Haas. The larger patch series
of which this patch is a part was also reviewed and tested by Antonin
Houska, Rajkumar Raghuwanshi, David Rowley, Dilip Kumar, Konstantin
Knizhnik, Pascal Legrand, and Rafia Sabih.
Discussion: http://postgr.es/m/CAM2+6=V64_xhstVHie0Rz=KPEQnLJMZt_e314P0jaT_oJ9MR8A@mail.gmail.com
One of the things canonicalize_qual() does is to remove constant-NULL
subexpressions of top-level AND/OR clauses. It does that on the assumption
that what it's given is a top-level WHERE clause, so that NULL can be
treated like FALSE. Although this is documented down inside a subroutine
of canonicalize_qual(), it wasn't mentioned in the documentation of that
function itself, and some callers hadn't gotten that memo.
Notably, commit d007a9505 caused get_relation_constraints() to apply
canonicalize_qual() to CHECK constraints. That allowed constraint
exclusion to misoptimize situations in which a CHECK constraint had a
provably-NULL subclause, as seen in the regression test case added here,
in which a child table that should be scanned is not. (Although this
thinko is ancient, the test case doesn't fail before 9.2, for reasons
I've not bothered to track down in detail. There may be related cases
that do fail before that.)
More recently, commit f0e44751d added an independent bug by applying
canonicalize_qual() to index expressions, which is even sillier since
those might not even be boolean. If they are, though, I think this
could lead to making incorrect index entries for affected index
expressions in v10. I haven't attempted to prove that though.
To fix, add an "is_check" parameter to canonicalize_qual() to specify
whether it should assume WHERE or CHECK semantics, and make it perform
NULL-elimination accordingly. Adjust the callers to apply the right
semantics, or remove the call entirely in cases where it's not known
that the expression has one or the other semantics. I also removed
the call in some cases involving partition expressions, where it should
be a no-op because such expressions should be canonical already ...
and was a no-op, independently of whether it could in principle have
done something, because it was being handed the qual in implicit-AND
format which isn't what it expects. In HEAD, add an Assert to catch
that type of mistake in future.
This represents an API break for external callers of canonicalize_qual().
While that's intentional in HEAD to make such callers think about which
case applies to them, it seems like something we probably wouldn't be
thanked for in released branches. Hence, in released branches, the
extra parameter is added to a new function canonicalize_qual_ext(),
and canonicalize_qual() is a wrapper that retains its old behavior.
Patch by me with suggestions from Dean Rasheed. Back-patch to all
supported branches.
Discussion: https://postgr.es/m/24475.1520635069@sss.pgh.pa.us
Commit b08df9cab left things rather poorly documented as far as the
exact semantics of "clause_is_check" mode went. Also, that mode did
not really work correctly for predicate_refuted_by; although given the
lack of specification as to what it should do, as well as the lack
of any actual use-case, that's perhaps not surprising.
Rename "clause_is_check" to "weak" proof mode, and provide specifications
for what it should do. I defined weak refutation as meaning "truth of A
implies non-truth of B", which makes it possible to use the mode in the
part of relation_excluded_by_constraints that checks for mutually
contradictory WHERE clauses. Fix up several places that did things wrong
for that definition. (As far as I can see, these errors would only lead
to failure-to-prove, not incorrect claims of proof, making them not
serious bugs even aside from the fact that v10 contains no use of this
mode. So there seems no need for back-patching.)
In addition, teach predicate_refuted_by_recurse that it can use
predicate_implied_by_recurse after all when processing a strong NOT-clause,
so long as it asks for the correct proof strength. This is an optimization
that could have been included in commit b08df9cab, but wasn't.
Also, simplify and generalize the logic that checks for whether nullness of
the argument of IS [NOT] NULL would force overall nullness of the predicate
or clause. (This results in a change in the partition_prune test's output,
as it is now able to prune an all-nulls partition that it did not recognize
before.)
In passing, in PartConstraintImpliedByRelConstraint, remove bogus
conversion of the constraint list to explicit-AND form and then right back
again; that accomplished nothing except forcing a useless extra level of
recursion inside predicate_implied_by.
Discussion: https://postgr.es/m/5983.1520487191@sss.pgh.pa.us
Up until now, we've abused grouped_rel->partial_pathlist as a place to
store partial paths that have been partially aggregate, but that's
really not correct, because a partial path for a relation is supposed
to be one which produces the correct results with the addition of only
a Gather or Gather Merge node, and these paths also require a Finalize
Aggregate step. Instead, add a new partially_group_rel which can hold
either partial paths (which need to be gathered and then have
aggregation finalized) or non-partial paths (which only need to have
aggregation finalized). This allows us to reuse generate_gather_paths
for partially_grouped_rel instead of writing new code, so that this
patch actually basically no net new code while making things cleaner,
simplifying things for pending patches for partition-wise aggregate.
Robert Haas and Jeevan Chalke. The larger patch series of which this
patch is a part was also reviewed and tested by Antonin Houska,
Rajkumar Raghuwanshi, David Rowley, Dilip Kumar, Konstantin Knizhnik,
Pascal Legrand, Rafia Sabih, and me.
Discussion: http://postgr.es/m/CA+TgmobrzFYS3+U8a_BCy3-hOvh5UyJbC18rEcYehxhpw5=ETA@mail.gmail.com
Discussion: http://postgr.es/m/CA+TgmoZyQEjdBNuoG9-wC5GQ5GrO4544Myo13dVptvx+uLg9uQ@mail.gmail.com
Given overlapping or partially redundant join clauses, for example
t1 JOIN t2 ON t1.a = t2.x AND t1.b = t2.x
the planner's EquivalenceClass machinery will ordinarily refactor the
clauses as "t1.a = t1.b AND t1.a = t2.x", so that join processing doesn't
see multiple references to the same EquivalenceClass in a list of join
equality clauses. However, if the join is outer, it's incorrect to derive
a restriction clause on the outer side from the join conditions, so the
clause refactoring does not happen and we end up with overlapping join
conditions. The code that attempted to deal with such cases had several
subtle bugs, which could result in "left and right pathkeys do not match in
mergejoin" or "outer pathkeys do not match mergeclauses" planner errors,
if the selected join plan type was a mergejoin. (It does not appear that
any actually incorrect plan could have been emitted.)
The core of the problem really was failure to recognize that the outer and
inner relations' pathkeys have different relationships to the mergeclause
list. A join's mergeclause list is constructed by reference to the outer
pathkeys, so it will always be ordered the same as the outer pathkeys, but
this cannot be presumed true for the inner pathkeys. If the inner sides of
the mergeclauses contain multiple references to the same EquivalenceClass
({t2.x} in the above example) then a simplistic rendering of the required
inner sort order is like "ORDER BY t2.x, t2.x", but the pathkey machinery
recognizes that the second sort column is redundant and throws it away.
The mergejoin planning code failed to account for that behavior properly.
One error was to try to generate cut-down versions of the mergeclause list
from cut-down versions of the inner pathkeys in the same way as the initial
construction of the mergeclause list from the outer pathkeys was done; this
could lead to choosing a mergeclause list that fails to match the outer
pathkeys. The other problem was that the pathkey cross-checking code in
create_mergejoin_plan treated the inner and outer pathkey lists
identically, whereas actually the expectations for them must be different.
That led to false "pathkeys do not match" failures in some cases, and in
principle could have led to failure to detect bogus plans in other cases,
though there is no indication that such bogus plans could be generated.
Reported by Alexander Kuzmenkov, who also reviewed this patch. This has
been broken for years (back to around 8.3 according to my testing), so
back-patch to all supported branches.
Discussion: https://postgr.es/m/5dad9160-4632-0e47-e120-8e2082000c01@postgrespro.ru
To make this work, tuplesort.c and logtape.c must also support
parallelism, so this patch adds that infrastructure and then applies
it to the particular case of parallel btree index builds. Testing
to date shows that this can often be 2-3x faster than a serial
index build.
The model for deciding how many workers to use is fairly primitive
at present, but it's better than not having the feature. We can
refine it as we get more experience.
Peter Geoghegan with some help from Rushabh Lathia. While Heikki
Linnakangas is not an author of this patch, he wrote other patches
without which this feature would not have been possible, and
therefore the release notes should possibly credit him as an author
of this feature. Reviewed by Claudio Freire, Heikki Linnakangas,
Thomas Munro, Tels, Amit Kapila, me.
Discussion: http://postgr.es/m/CAM3SWZQKM=Pzc=CAHzRixKjp2eO5Q0Jg1SoFQqeXFQ647JiwqQ@mail.gmail.com
Discussion: http://postgr.es/m/CAH2-Wz=AxWqDoVvGU7dq856S4r6sJAj6DBn7VMtigkB33N5eyg@mail.gmail.com
When an UPDATE causes a row to no longer match the partition
constraint, try to move it to a different partition where it does
match the partition constraint. In essence, the UPDATE is split into
a DELETE from the old partition and an INSERT into the new one. This
can lead to surprising behavior in concurrency scenarios because
EvalPlanQual rechecks won't work as they normally did; the known
problems are documented. (There is a pending patch to improve the
situation further, but it needs more review.)
Amit Khandekar, reviewed and tested by Amit Langote, David Rowley,
Rajkumar Raghuwanshi, Dilip Kumar, Amul Sul, Thomas Munro, Álvaro
Herrera, Amit Kapila, and me. A few final revisions by me.
Discussion: http://postgr.es/m/CAJ3gD9do9o2ccQ7j7+tSgiE1REY65XRiMb=yJO3u3QhyP8EEPQ@mail.gmail.com
Introduce parallel-aware hash joins that appear in EXPLAIN plans as Parallel
Hash Join with Parallel Hash. While hash joins could already appear in
parallel queries, they were previously always parallel-oblivious and had a
partial subplan only on the outer side, meaning that the work of the inner
subplan was duplicated in every worker.
After this commit, the planner will consider using a partial subplan on the
inner side too, using the Parallel Hash node to divide the work over the
available CPU cores and combine its results in shared memory. If the join
needs to be split into multiple batches in order to respect work_mem, then
workers process different batches as much as possible and then work together
on the remaining batches.
The advantages of a parallel-aware hash join over a parallel-oblivious hash
join used in a parallel query are that it:
* avoids wasting memory on duplicated hash tables
* avoids wasting disk space on duplicated batch files
* divides the work of building the hash table over the CPUs
One disadvantage is that there is some communication between the participating
CPUs which might outweigh the benefits of parallelism in the case of small
hash tables. This is avoided by the planner's existing reluctance to supply
partial plans for small scans, but it may be necessary to estimate
synchronization costs in future if that situation changes. Another is that
outer batch 0 must be written to disk if multiple batches are required.
A potential future advantage of parallel-aware hash joins is that right and
full outer joins could be supported, since there is a single set of matched
bits for each hashtable, but that is not yet implemented.
A new GUC enable_parallel_hash is defined to control the feature, defaulting
to on.
Author: Thomas Munro
Reviewed-By: Andres Freund, Robert Haas
Tested-By: Rafia Sabih, Prabhat Sahu
Discussion:
https://postgr.es/m/CAEepm=2W=cOkiZxcg6qiFQP-dHUe09aqTrEMM7yJDrHMhDv_RA@mail.gmail.comhttps://postgr.es/m/CAEepm=37HKyJ4U6XOLi=JgfSHM3o6B-GaeO-6hkOmneTDkH+Uw@mail.gmail.com
When we create an Append node, we can spread out the workers over the
subplans instead of piling on to each subplan one at a time, which
should typically be a bit more efficient, both because the startup
cost of any plan executed entirely by one worker is paid only once and
also because of reduced contention. We can also construct Append
plans using a mix of partial and non-partial subplans, which may allow
for parallelism in places that otherwise couldn't support it.
Unfortunately, this patch doesn't handle the important case of
parallelizing UNION ALL by running each branch in a separate worker;
the executor infrastructure is added here, but more planner work is
needed.
Amit Khandekar, Robert Haas, Amul Sul, reviewed and tested by
Ashutosh Bapat, Amit Langote, Rafia Sabih, Amit Kapila, and
Rajkumar Raghuwanshi.
Discussion: http://postgr.es/m/CAJ3gD9dy0K_E8r727heqXoBmWZ83HwLFwdcaSSmBQ1+S+vRuUQ@mail.gmail.com
rewriteTargetListUD's processing is dependent on the relkind of the query's
target table. That was fine at the time it was made to act that way, even
for queries on inheritance trees, because all tables in an inheritance tree
would necessarily be plain tables. However, the 9.5 feature addition
allowing some members of an inheritance tree to be foreign tables broke the
assumption that rewriteTargetListUD's output tlist could be applied to all
child tables with nothing more than column-number mapping. This led to
visible failures if foreign child tables had row-level triggers, and would
also break in cases where child tables belonged to FDWs that used methods
other than CTID for row identification.
To fix, delay running rewriteTargetListUD until after the planner has
expanded inheritance, so that it is applied separately to the (already
mapped) tlist for each child table. We can conveniently call it from
preprocess_targetlist. Refactor associated code slightly to avoid the
need to heap_open the target relation multiple times during
preprocess_targetlist. (The APIs remain a bit ugly, particularly around
the point of which steps scribble on parse->targetList and which don't.
But avoiding such scribbling would require a change in FDW callback APIs,
which is more pain than it's worth.)
Also fix ExecModifyTable to ensure that "tupleid" is reset to NULL when
we transition from rows providing a CTID to rows that don't. (That's
really an independent bug, but it manifests in much the same cases.)
Add a regression test checking one manifestation of this problem, which
was that row-level triggers on a foreign child table did not work right.
Back-patch to 9.5 where the problem was introduced.
Etsuro Fujita, reviewed by Ildus Kurbangaliev and Ashutosh Bapat
Discussion: https://postgr.es/m/20170514150525.0346ba72@postgrespro.ru
For some reason, we have never accounted for either the evaluation cost
or the selectivity of filter conditions attached to Agg and Group nodes
(which, in practice, are always conditions from a HAVING clause).
Applying our regular selectivity logic to post-grouping conditions is a
bit bogus, but it's surely better than taking the selectivity as 1.0.
Perhaps someday the extended-statistics mechanism can be taught to provide
statistics that would help us in getting non-default estimates here.
Per a gripe from Benjamin Coutu. This is surely a bug fix, but I'm
hesitant to back-patch because of the prospect of destabilizing existing
plan choices. Given that it took us this long to notice the bug, it's
probably not hurting too many people in the field.
Discussion: https://postgr.es/m/20968.1509486337@sss.pgh.pa.us
If the operator is a strict btree equality operator, and X isn't volatile,
then the clause must yield true for any non-null value of X, or null if X
is null. At top level of a WHERE clause, we can ignore the distinction
between false and null results, so it's valid to simplify the clause to
"X IS NOT NULL". This is a useful improvement mainly because we'll get
a far better selectivity estimate in most cases.
Because such cases seldom arise in well-written queries, it is unappetizing
to expend a lot of planner cycles looking for them ... but it turns out
that there's a place we can shoehorn this in practically for free, because
equivclass.c already has to detect and reject candidate equivalences of the
form X = X. That doesn't catch every place that it would be valid to
simplify to X IS NOT NULL, but it catches the typical case. Working harder
doesn't seem justified.
Patch by me, reviewed by Petr Jelinek
Discussion: https://postgr.es/m/CAMjNa7cC4X9YR-vAJS-jSYCajhRDvJQnN7m2sLH1wLh-_Z2bsw@mail.gmail.com
Instead of joining two partitioned tables in their entirety we can, if
it is an equi-join on the partition keys, join the matching partitions
individually. This involves teaching the planner about "other join"
rels, which are related to regular join rels in the same way that
other member rels are related to baserels. This can use significantly
more CPU time and memory than regular join planning, because there may
now be a set of "other" rels not only for every base relation but also
for every join relation. In most practical cases, this probably
shouldn't be a problem, because (1) it's probably unusual to join many
tables each with many partitions using the partition keys for all
joins and (2) if you do that scenario then you probably have a big
enough machine to handle the increased memory cost of planning and (3)
the resulting plan is highly likely to be better, so what you spend in
planning you'll make up on the execution side. All the same, for now,
turn this feature off by default.
Currently, we can only perform joins between two tables whose
partitioning schemes are absolutely identical. It would be nice to
cope with other scenarios, such as extra partitions on one side or the
other with no match on the other side, but that will have to wait for
a future patch.
Ashutosh Bapat, reviewed and tested by Rajkumar Raghuwanshi, Amit
Langote, Rafia Sabih, Thomas Munro, Dilip Kumar, Antonin Houska, Amit
Khandekar, and by me. A few final adjustments by me.
Discussion: http://postgr.es/m/CAFjFpRfQ8GrQvzp3jA2wnLqrHmaXna-urjm_UY9BqXj=EaDTSA@mail.gmail.com
Discussion: http://postgr.es/m/CAFjFpRcitjfrULr5jfuKWRPsGUX0LQ0k8-yG0Qw2+1LBGNpMdw@mail.gmail.com
Instead of duplicating the logic to search for a matching
ParamPathInfo in multiple places, factor it out into a separate
function.
Pass only the relevant bits of the PartitionKey to
partition_bounds_equal instead of the whole thing, because
partition-wise join will want to call this without having a
PartitionKey available.
Adjust allow_star_schema_join and calc_nestloop_required_outer
to take relevant Relids rather than the entire Path, because
partition-wise join will want to call it with the top-parent
relids to determine whether a child join is allowable.
Ashutosh Bapat. Review and testing of the larger patch set of which
this is a part by Amit Langote, Rajkumar Raghuwanshi, Rafia Sabih,
Thomas Munro, Dilip Kumar, and me.
Discussion: http://postgr.es/m/CA+TgmobQK80vtXjAsPZWWXd7c8u13G86gmuLupN+uUJjA+i4nA@mail.gmail.com
Currently, child relations are always base relations, so when we
translate parent relids to child relids, we only need to translate
a singler relid. However, the proposed partition-wise join feature
will create child joins, which will mean we need to translate a set
of parent relids to the corresponding child relids. This is
preliminary refactoring to make that possible.
Ashutosh Bapat. Review and testing of the larger patch set of which
this is a part by Amit Langote, Rajkumar Raghuwanshi, Rafia Sabih,
Thomas Munro, Dilip Kumar, and me. Some adjustments, mostly
cosmetic, by me.
Discussion: http://postgr.es/m/CA+TgmobQK80vtXjAsPZWWXd7c8u13G86gmuLupN+uUJjA+i4nA@mail.gmail.com
Don't move parenthesized lines to the left, even if that means they
flow past the right margin.
By default, BSD indent lines up statement continuation lines that are
within parentheses so that they start just to the right of the preceding
left parenthesis. However, traditionally, if that resulted in the
continuation line extending to the right of the desired right margin,
then indent would push it left just far enough to not overrun the margin,
if it could do so without making the continuation line start to the left of
the current statement indent. That makes for a weird mix of indentations
unless one has been completely rigid about never violating the 80-column
limit.
This behavior has been pretty universally panned by Postgres developers.
Hence, disable it with indent's new -lpl switch, so that parenthesized
lines are always lined up with the preceding left paren.
This patch is much less interesting than the first round of indent
changes, but also bulkier, so I thought it best to separate the effects.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
Change pg_bsd_indent to follow upstream rules for placement of comments
to the right of code, and remove pgindent hack that caused comments
following #endif to not obey the general rule.
Commit e3860ffa4d wasn't actually using
the published version of pg_bsd_indent, but a hacked-up version that
tried to minimize the amount of movement of comments to the right of
code. The situation of interest is where such a comment has to be
moved to the right of its default placement at column 33 because there's
code there. BSD indent has always moved right in units of tab stops
in such cases --- but in the previous incarnation, indent was working
in 8-space tab stops, while now it knows we use 4-space tabs. So the
net result is that in about half the cases, such comments are placed
one tab stop left of before. This is better all around: it leaves
more room on the line for comment text, and it means that in such
cases the comment uniformly starts at the next 4-space tab stop after
the code, rather than sometimes one and sometimes two tabs after.
Also, ensure that comments following #endif are indented the same
as comments following other preprocessor commands such as #else.
That inconsistency turns out to have been self-inflicted damage
from a poorly-thought-through post-indent "fixup" in pgindent.
This patch is much less interesting than the first round of indent
changes, but also bulkier, so I thought it best to separate the effects.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
The new indent version includes numerous fixes thanks to Piotr Stefaniak.
The main changes visible in this commit are:
* Nicer formatting of function-pointer declarations.
* No longer unexpectedly removes spaces in expressions using casts,
sizeof, or offsetof.
* No longer wants to add a space in "struct structname *varname", as
well as some similar cases for const- or volatile-qualified pointers.
* Declarations using PG_USED_FOR_ASSERTS_ONLY are formatted more nicely.
* Fixes bug where comments following declarations were sometimes placed
with no space separating them from the code.
* Fixes some odd decisions for comments following case labels.
* Fixes some cases where comments following code were indented to less
than the expected column 33.
On the less good side, it now tends to put more whitespace around typedef
names that are not listed in typedefs.list. This might encourage us to
put more effort into typedef name collection; it's not really a bug in
indent itself.
There are more changes coming after this round, having to do with comment
indentation and alignment of lines appearing within parentheses. I wanted
to limit the size of the diffs to something that could be reviewed without
one's eyes completely glazing over, so it seemed better to split up the
changes as much as practical.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
In a CHECK clause, a null result means true, whereas in a WHERE clause
it means false. predtest.c provided different functions depending on
which set of semantics applied to the predicate being proved, but had
no option to control what a null meant in the clauses provided as
axioms. Add one.
Use that in the partitioning code when figuring out whether the
validation scan on a new partition can be skipped. Rip out the
old logic that attempted (not very successfully) to compensate
for the absence of the necessary support in predtest.c.
Ashutosh Bapat and Robert Haas, reviewed by Amit Langote and
incorporating feedback from Tom Lane.
Discussion: http://postgr.es/m/CAFjFpReT_kq_uwU_B8aWDxR7jNGE=P0iELycdq5oupi=xSQTOw@mail.gmail.com
I'd always assumed that backend/optimizer/geqo/'s remarkably poor
showing on code coverage metrics was because we weren't exercising
it much in the regression tests. But it turns out that a good chunk
of the problem is that there's a bunch of code that is physically
unreachable (because the calls to it are #ifdef'd out in geqo_main.c)
but is being built anyway. Making the called code have #if guards
similar to the calling code saves a couple of kilobytes of executable
size and should make the coverage numbers more reflective of reality.
It's arguable that we should just delete all the unused recombination
mechanisms altogether, but I didn't feel a need to go that far today.
If the inner relation can be proven unique, that is it can have no more
than one matching row for any row of the outer query, then we might as
well implement the semijoin as a plain inner join, allowing substantially
more freedom to the planner. This is a form of outer join strength
reduction, but it can't be implemented in reduce_outer_joins() because
we don't have enough info about the individual relations at that stage.
Instead do it much like remove_useless_joins(): once we've built base
relations, we can make another pass over the SpecialJoinInfo list and
get rid of any entries representing reducible semijoins.
This is essentially a followon to the inner-unique patch (commit 9c7f5229a)
and makes use of the proof machinery that that patch created. We need only
minor refactoring of innerrel_is_unique's API to support this usage.
Per performance complaint from Teodor Sigaev.
Discussion: https://postgr.es/m/f994fc98-389f-4a46-d1bc-c42e05cb43ed@sigaev.ru
If there can certainly be no more than one matching inner row for a given
outer row, then the executor can move on to the next outer row as soon as
it's found one match; there's no need to continue scanning the inner
relation for this outer row. This saves useless scanning in nestloop
and hash joins. In merge joins, it offers the opportunity to skip
mark/restore processing, because we know we have not advanced past the
first possible match for the next outer row.
Of course, the devil is in the details: the proof of uniqueness must
depend only on joinquals (not otherquals), and if we want to skip
mergejoin mark/restore then it must depend only on merge clauses.
To avoid adding more planning overhead than absolutely necessary,
the present patch errs in the conservative direction: there are cases
where inner_unique or skip_mark_restore processing could be used, but
it will not do so because it's not sure that the uniqueness proof
depended only on "safe" clauses. This could be improved later.
David Rowley, reviewed and rather heavily editorialized on by me
Discussion: https://postgr.es/m/CAApHDvqF6Sw-TK98bW48TdtFJ+3a7D2mFyZ7++=D-RyPsL76gw@mail.gmail.com
Follow on patch in the multi-variate statistics patch series.
CREATE STATISTICS s1 WITH (dependencies) ON (a, b) FROM t;
ANALYZE;
will collect dependency stats on (a, b) and then use the measured
dependency in subsequent query planning.
Commit 7b504eb282 added
CREATE STATISTICS with n-distinct coefficients. These are now
specified using the mutually exclusive option WITH (ndistinct).
Author: Tomas Vondra, David Rowley
Reviewed-by: Kyotaro HORIGUCHI, Álvaro Herrera, Dean Rasheed, Robert Haas
and many other comments and contributions
Discussion: https://postgr.es/m/56f40b20-c464-fad2-ff39-06b668fac47c@2ndquadrant.com
Currently, the only type of child relation is an "other member rel",
which is the child of a baserel, but in the future joins and even
upper relations may have child rels. To facilitate that, introduce
macros that test to test for particular RelOptKind values, and use
them in various places where they help to clarify the sense of a test.
(For example, a test may allow RELOPT_OTHER_MEMBER_REL either because
it intends to allow child rels, or because it intends to allow simple
rels.)
Also, remove find_childrel_top_parent, which will not work for a
child rel that is not a baserel. Instead, add a new RelOptInfo
member top_parent_relids to track the same kind of information in a
more generic manner.
Ashutosh Bapat, slightly tweaked by me. Review and testing of the
patch set from which this was taken by Rajkumar Raghuwanshi and Rafia
Sabih.
Discussion: http://postgr.es/m/CA+TgmoagTnF2yqR3PT2rv=om=wJiZ4-A+ATwdnriTGku1CLYxA@mail.gmail.com
A QueryEnvironment concept is added, which allows new types of
objects to be passed into queries from parsing on through
execution. At this point, the only thing implemented is a
collection of EphemeralNamedRelation objects -- relations which
can be referenced by name in queries, but do not exist in the
catalogs. The only type of ENR implemented is NamedTuplestore, but
provision is made to add more types fairly easily.
An ENR can carry its own TupleDesc or reference a relation in the
catalogs by relid.
Although these features can be used without SPI, convenience
functions are added to SPI so that ENRs can easily be used by code
run through SPI.
The initial use of all this is going to be transition tables in
AFTER triggers, but that will be added to each PL as a separate
commit.
An incidental effect of this patch is to produce a more informative
error message if an attempt is made to modify the contents of a CTE
from a referencing DML statement. No tests previously covered that
possibility, so one is added.
Kevin Grittner and Thomas Munro
Reviewed by Heikki Linnakangas, David Fetter, and Thomas Munro
with valuable comments and suggestions from many others
copyObject() is declared to return void *, which allows easily assigning
the result independent of the input, but it loses all type checking.
If the compiler supports typeof or something similar, cast the result to
the input type. This creates a greater amount of type safety. In some
cases, where the result is assigned to a generic type such as Node * or
Expr *, new casts are now necessary, but in general casts are now
unnecessary in the normal case and indicate that something unusual is
happening.
Reviewed-by: Mark Dilger <hornschnorter@gmail.com>
This extends the Aggregate node with two new features: HashAggregate
can now run multiple hashtables concurrently, and a new strategy
MixedAggregate populates hashtables while doing sorted grouping.
The planner will now attempt to save as many sorts as possible when
planning grouping sets queries, while not exceeding work_mem for the
estimated combined sizes of all hashtables used. No SQL-level changes
are required. There should be no user-visible impact other than the
new EXPLAIN output and possible changes to result ordering when ORDER
BY was not used (which affected a few regression tests). The
enable_hashagg option is respected.
Author: Andrew Gierth
Reviewers: Mark Dilger, Andres Freund
Discussion: https://postgr.es/m/87vatszyhj.fsf@news-spur.riddles.org.uk
Partitioned tables do not contain any data; only their unpartitioned
descendents need to be scanned. However, the partitioned tables still
need to be locked, even though they're not scanned. To make that
work, Append and MergeAppend relations now need to carry a list of
(unscanned) partitioned relations that must be locked, and InitPlan
must lock all partitioned result relations.
Aside from the obvious advantage of avoiding some work at execution
time, this has two other advantages. First, it may improve the
planner's decision-making in some cases since the empty relation
might throw things off. Second, it paves the way to getting rid of
the storage for partitioned tables altogether.
Amit Langote, reviewed by me.
Discussion: http://postgr.es/m/6837c359-45c4-8044-34d1-736756335a15@lab.ntt.co.jp
