Up to now we've not worried much about joins where the join key is a
relation's CTID column, reasoning that storing a table's CTIDs in some
other table would be pretty useless. However, there are use-cases for
this sort of query involving self-joins, so that argument doesn't really
hold water.
With larger relations, a merge or hash join is desirable. We had a btree
opclass for type "tid", allowing merge joins on CTID, but no hash opclass
so that hash joins weren't possible. Add the missing infrastructure.
This also potentially enables hash aggregation on "tid", though the
use-cases for that aren't too clear.
Discussion: https://postgr.es/m/1853.1545453106@sss.pgh.pa.us
Up to now we've not worried much about joins where the join key is a
relation's CTID column, reasoning that storing a table's CTIDs in some
other table would be pretty useless. However, there are use-cases for
this sort of query involving self-joins, so that argument doesn't really
hold water.
This patch allows generating plans for joins on CTID that use a nestloop
with inner TidScan, similar to what we might do with an index on the join
column. This is the most efficient way to join when the outer side of
the nestloop is expected to yield relatively few rows.
This change requires upgrading tidpath.c and the generated TidPaths
to work with RestrictInfos instead of bare qual clauses, but that's
long-postponed technical debt anyway.
Discussion: https://postgr.es/m/17443.1545435266@sss.pgh.pa.us
TidScan plan nodes were not systematically tested before. These additions
raise the LOC coverage number for the basic regression tests from 52% to
92% in nodeTidscan.c, and from 60% to 93% in tidpath.c.
Andres Freund, tweaked a bit by me
Discussion: https://postgr.es/m/20170320062511.hp5qeurtxrwsvfxr@alap3.anarazel.de
