On Sat, Dec 19, 2009 at 12:49 PM, Hitoshi Harada <umi.tan...@gmail.com> wrote: > 2009/10/20 Andrew Gierth <and...@tao11.riddles.org.uk>: >> Right now, the only way pg can plan this is to do a hashjoin or >> mergejoin of the _entire content of big1 and big2_ and join the >> result against "small" (again in a hashjoin or mergejoin plan). >> This becomes excessively slow compared to the "ideal" plan: >> >> nested loop >> seqscan on small >> nested loop >> indexscan on big1 where id=small.id >> indexscan on big2 where id=small.id (or big1.id which is equiv) >> >> (The same argument applies if "small" is not actually small but has >> restriction clauses) > > I have a similar issue on my mind, but is this the same as the topic? > > SELECT ... FROM small INNER JOIN (SELECT ... FROM large GROUP BY > large.id) agged ON small.id = agged.id WHERE small.id IN (bla bla bla) > > The ideal plan is SeqScan on small with filtering sub query aggregate > on large by small.id but the actual plan is full aggregate on large > since the planner doesn't push down outer qual to aggregate node. The > output will discard almost all of agged's output.
I just tried this and it works for me. create table foo (id serial, name varchar, primary key (id)); create table bar (id serial, foo_id integer references foo (id), name varchar, primary key (id)); insert into foo (name) select random()::varchar from generate_series(1,1000); insert into bar (foo_id, name) select (g%10)+1, random()::varchar from generate_series(1,10000) g; explain select * from foo inner join (select foo_id, sum(1) from bar group by 1) x on foo.id = x.foo_id where x.foo_id = 1; ...Robert -- Sent via pgsql-hackers mailing list (pgsql-hackers@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-hackers
