Please ignore this post. I accidentally double posted here and on the
performance mailing list. I think this belongs on the performance list.
Sorry for the noise.
Jann
Am 23.08.10 06:05, schrieb Jann Röder:
> I have two tables:
> A: ItemID (PK), IsssueID (Indexed)
> B: ItemID (FK), IndexNumber : PK(ItemID, IndexNumber)
>
> Both tables have several million columns, but B has much more than A.
>
> Now if I run
>
> SELECT A.ItemID FROM A, B WHERE A.ItemID = B.itemID AND A.issueID =
> <some id>
>
> The query takes extremely long (several hours). I ran EXPLAIN and got:
>
> "Hash Join (cost=516.66..17710110.47 rows=8358225 width=16)"
> " Hash Cond: ((b.itemid)::bpchar = a.itemid)"
> " -> Seq Scan on b (cost=0.00..15110856.68 rows=670707968 width=16)"
> " -> Hash (cost=504.12..504.12 rows=1003 width=16)"
> " -> Index Scan using idx_issueid on a (cost=0.00..504.12
> rows=1003 width=16)"
> " Index Cond: (issueid = 'A1983PW823'::bpchar)"
>
> Now we see the problem is the seq scan on B. However there are only a
> handful of rows in A that match a specific issueID. So my question is
> why doesn't it just check for each of the ItemIDs that have the correct
> IssueID in A if there is a matching itemID in B. This should be really
> fast because ItemID in B is indexed since it is part of the primary key.
>
> What is the reason for postgres not doing this, is there a way I can
> make it do that? I'm using postgresql 8.4.4 and yes, I did run ANALYZE
> on the entire DB.
>
> Thanks a lot,
> Jann
>
>
