Dimitri wrote:
> any idea if there is a more optimal execution plan possible for this query:
>
> select S.REF as stref, S.NAME as stnm, H.HORDER as hord, H.BEGIN_DATE as hbeg,
> H.END_DATE as hend, H.NOTE as hnote
> from HISTORY H, STAT S
> where S.REF = H.REF_STAT
> and H.REF_OBJECT = '0000000001'
> order by H.HORDER ;
>
> EXPLAIN ANALYZE output on 8.4:
> QUERY PLAN
>
------------------------------------------------------------------------------------------------------------------------------------------------
> Sort (cost=4549.75..4555.76 rows=2404 width=176) (actual
> time=1.341..1.343 rows=20 loops=1)
> Sort Key: h.horder
> Sort Method: quicksort Memory: 30kB
> -> Hash Join (cost=33.50..4414.75 rows=2404 width=176) (actual
> time=1.200..1.232 rows=20 loops=1)
> Hash Cond: (h.ref_stat = s.ref)
> -> Index Scan using history_ref_idx on history h
> (cost=0.00..4348.20 rows=2404 width=135) (actual time=0.042..0.052
> rows=20 loops=1)
> Index Cond: (ref_object = '0000000001'::bpchar)
> -> Hash (cost=21.00..21.00 rows=1000 width=45) (actual
> time=1.147..1.147 rows=1000 loops=1)
> -> Seq Scan on stat s (cost=0.00..21.00 rows=1000
> width=45) (actual time=0.005..0.325 rows=1000 loops=1)
> Total runtime: 1.442 ms
> (10 rows)
>
> Table HISTORY contains 200M rows, only 20 needed
> Table STAT contains 1000 rows, only 20 needed to be joined to HISTORY values.
The bad doesn't look too bad to me, although the planner is
over-estimating the number of matches in the history table (2404 vs 20).
That's a bit surprising given how simple the predicate is. Make sure
you've ANALYZEd the table. If that's not enough, you can try to increase
the statistics target for ref_object column, ie. ALTER TABLE history
ALTER COLUMN ref_object SET STATISTICS 500. That might give you a
different plan, maybe with a nested loop join instead of hash join,
which might be faster in this case.
--
Heikki Linnakangas
EnterpriseDB http://www.enterprisedb.com
