The previous coding saved pointers into the partitioned table's relcache
entry, but then closed the relcache entry, causing those pointers to
nominally become dangling. Actual trouble would be seen in the field
only if a relcache flush occurred mid-query, but that's hardly out of
the question.
While we could fix this by copying all the data in question at query
start, it seems better to just hold the relcache entry open for the
whole query.
While at it, improve the handling of support-function lookups: do that
once per query not once per pruning test. There's still something to be
desired here, in that we fail to exploit the possibility of caching data
across queries in the fn_extra fields of the relcache's FmgrInfo structs,
which could happen if we just used those structs in-place rather than
copying them. However, combining that with the possibility of per-query
lookups of cross-type comparison functions seems to require changes in the
APIs of a lot of the pruning support functions, so it's too invasive to
consider as part of this patch. A win would ensue only for complex
partition key data types (e.g. arrays), so it may not be worth the
trouble.
David Rowley and Tom Lane
Discussion: https://postgr.es/m/17850.1528755844@sss.pgh.pa.us
The previous coding just ignored pruning constraints that compare a
partition key to a null-valued expression. This is silly, since really
what we can do there is conclude that all partitions are rejected: the
pruning operator is known strict so the comparison must always fail.
This also fixes the logic to not ignore constisnull for a Const comparison
value. That's probably an unreachable case, since the planner would
normally have simplified away a strict operator with a constant-null input.
But this code has no business assuming that.
David Rowley, per a gripe from me
Discussion: https://postgr.es/m/26279.1528670981@sss.pgh.pa.us
The initial coding of the run-time-pruning feature only coped with cases
where the partition key(s) are compared to Params. That is a bit silly;
we can allow it to work with any non-Var-containing stable expression, as
long as we take special care with expressions containing PARAM_EXEC Params.
The code is hardly any longer this way, and it's considerably clearer
(IMO at least). Per gripe from Pavel Stehule.
David Rowley, whacked around a bit by me
Discussion: https://postgr.es/m/CAFj8pRBjrufA3ocDm8o4LPGNye9Y+pm1b9kCwode4X04CULG3g@mail.gmail.com
match_clause_to_partition_key failed to consider COERCION_PATH_ARRAYCOERCE
cases in scalar-op-array expressions, so it was possible to crash the
server easily. To handle this case properly (ie. prune partitions) we
would need to run a bit of executor code during planning. Maybe it can
be improved, but for now let's just not crash. Add a test case that
used to trigger the crash.
Author: Michaël Paquier
match_clause_to_partition_key failed to indicate that operators that
don't have a commutator in a btree opclass are unsupported. It is
possible for this to cause a crash later if such an operator is used in
a scalar-op-array expression. Add a test case that used to the crash.
Author: Amit Langote
One caller of gen_partprune_steps_internal in
match_clause_to_partition_key was too optimistic about the former never
returning an empty step list. Rid it of its innocence. (Having fixed
the bug above, I no longer know how to exploit this, so no test case for
it, but it remained a bug.) Revise code flow a little bit, for
succintness.
Author: Álvaro Herrera
Reported-by: Marina Polyakova
Reviewed-by: Michaël Paquier
Reviewed-by: Amit Langote
Reviewed-by: Álvaro Herrera
Discussion: https://postgr.es/m/ff8f9bfa485ff961d6bb43e54120485b@postgrespro.ru
There's no need to export this function, so don't. Michaël didn't
actually write the patch, but we list him as first author because with a
trivial one like this, intellectual authorship is as important (if not
more) as bit shovelling.
Author: Michaël Paquier, Amit Langote
Discussion: https://postgr.es/m/c91299c4-199b-0f16-339b-a29d6d2a39ee@lab.ntt.co.jp
Instead of doing ExecInitExpr every time a Param needs to be evaluated
in run-time partition pruning, do it once during run-time pruning
set-up and cache the exprstate in PartitionPruneContext, saving a lot of
work.
Author: David Rowley
Reviewed-by: Amit Langote, Álvaro Herrera
Discussion: https://postgr.es/m/CAKJS1f8-x+q-90QAPDu_okhQBV4DPEtPz8CJ=m0940GyT4DA4w@mail.gmail.com
Amit Langote reported that partition prune was unable to work with
arrays, enums, etc, which led him to research the appropriate way to
match query clauses to partition keys: instead of searching for an exact
match of the expression's type, it is better to rely on the fact that
the expression qual has already been resolved to a specific operator,
and that the partition key is linked to a specific operator family.
With that info, it's possible to figure out the strategy and comparison
function to use for the pruning clause in a manner that works reliably
for pseudo-types also.
Include new test cases that demonstrate pruning where pseudotypes are
involved.
Author: Amit Langote, Álvaro Herrera
Discussion: https://postgr.es/m/2b02f1e9-9812-9c41-972d-517bdc0f815d@lab.ntt.co.jp
We were initializing a BMS to merely reference an existing one, which
would cause a double-free (and a crash) when the recursive algorithm
tried to intersect it with an empty one. Fix it by creating a copy at
initialization time.
Reported-by: sqlsmith (by way of Andreas Seltenreich)
Author: Amit Langote
Discussion: https://postgr.es/m/87in923lyw.fsf@ansel.ydns.eu
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
Tom Lane
Alvaro Herrera