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Allow partitionwise joins in more cases.

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Previously, the partitionwise join technique only allowed partitionwise
join when input partitioned tables had exactly the same partition
bounds.  This commit extends the technique to some cases when the tables
have different partition bounds, by using an advanced partition-matching
algorithm introduced by this commit.  For both the input partitioned
tables, the algorithm checks whether every partition of one input
partitioned table only matches one partition of the other input
partitioned table at most, and vice versa.  In such a case the join
between the tables can be broken down into joins between the matching
partitions, so the algorithm produces the pairs of the matching
partitions, plus the partition bounds for the join relation, to allow
partitionwise join for computing the join.  Currently, the algorithm
works for list-partitioned and range-partitioned tables, but not
hash-partitioned tables.  See comments in partition_bounds_merge().

Ashutosh Bapat and Etsuro Fujita, most of regression tests by Rajkumar
Raghuwanshi, some of the tests by Mark Dilger and Amul Sul, reviewed by
Dmitry Dolgov and Amul Sul, with additional review at various points by
Ashutosh Bapat, Mark Dilger, Robert Haas, Antonin Houska, Amit Langote,
Justin Pryzby, and Tomas Vondra

Discussion: https://postgr.es/m/CAFjFpRdjQvaUEV5DJX3TW6pU5eq54NCkadtxHX2JiJG_GvbrCA@mail.gmail.com
This commit is contained in:
Etsuro Fujita
2020-04-08 10:25:00 +09:00
parent 41a194f491
commit c8434d64ce
11 changed files with 5390 additions and 81 deletions
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6
doc/src/sgml/config.sgml
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@ -4749,9 +4749,9 @@ ANY <replaceable class="parameter">num_sync</replaceable> ( <replaceable class="
which allows a join between partitioned tables to be performed by
joining the matching partitions. Partitionwise join currently applies
only when the join conditions include all the partition keys, which
must be of the same data type and have exactly matching sets of child
partitions. Because partitionwise join planning can use significantly
more CPU time and memory during planning, the default is
must be of the same data type and have one-to-one matching sets of
child partitions. Because partitionwise join planning can use
significantly more CPU time and memory during planning, the default is
<literal>off</literal>.
</para>
</listitem>