From: | Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us> |
---|---|
To: | Gregory Stark <stark(at)enterprisedb(dot)com> |
Cc: | "pgsql-hackers list" <pgsql-hackers(at)postgresql(dot)org> |
Subject: | Re: New style of hash join proposal |
Date: | 2008-03-17 22:32:57 |
Message-ID: | 116.1205793177@sss.pgh.pa.us |
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Gregory Stark <stark(at)enterprisedb(dot)com> writes:
> "Tom Lane" <tgl(at)sss(dot)pgh(dot)pa(dot)us> writes:
>> I already demonstrated that we could.
> We seem to be talking past each other. The plan you showed is analogous but
> using a plain old index scan.
That's only because that seemed like the appropriate thing for the given
case's statistics. [ fiddles with example... ]
regression=# explain select * from tenk1 a where thousand in (select f1 from int4_tbl b);
QUERY PLAN
------------------------------------------------------------------------------------------
Nested Loop (cost=5.39..198.81 rows=51 width=244)
-> HashAggregate (cost=1.06..1.11 rows=5 width=4)
-> Seq Scan on int4_tbl b (cost=0.00..1.05 rows=5 width=4)
-> Bitmap Heap Scan on tenk1 a (cost=4.33..39.41 rows=10 width=244)
Recheck Cond: (a.thousand = b.f1)
-> Bitmap Index Scan on tenk1_thous_tenthous (cost=0.00..4.33 rows=10 width=0)
Index Cond: (a.thousand = b.f1)
(7 rows)
regards, tom lane
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