Joshua Tolley <eggyknap@gmail.com> writes:
>> >> ALTER TABLE x SET CORRELATION STATISTICS FOR (x.id =3D y.id AND x.id=
2 =3D y.id2)
>> >=20
>> it says X and Y ... the selectivity of joins are what i am most
>> interested in. cross correlation of columns within the same table are
>> just a byproduct. the core thing is: how can i estimate the number
>> of rows returned from a join?
>
> All the discussion of this topic that I've seen has been limited to the s=
ingle
> table case. The hard problem in that case is coming up with something you=
can
> precalculate that will actually be useful during query planning, without
> taking too much disk, memory, CPU, or something else. Expanding the discu=
ssion
> to include join relations certainly still has valid use cases, but is even
> harder, because you've also got to keep track of precisely how the underl=
ying
> relations are joined, so you know in what context the statistics remain v=
alid.
Well I've been proposing to handle the correlation problem in another
way in some past mails here, and I've been trying to write it down too:
http://archives.postgresql.org/pgsql-performance/2009-06/msg00118.php http://tapoueh.org/char10.html#sec13
What I propose is to extend ANALYZE to be able to work on a VIEW too,
rather than just a table. The hard parts seems to be:
a. what stats to record, exploiting the view definition the best we can
b. how to match a user query against the view definitions we have in order to actually use the stats
If you have answers or good ideas=C2=A0:)
Regards,
--=20
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