"Andrus" <kobruleht2@xxxxxx> writes:
> explain analyze SELECT sum(xxx)
> FROM dok JOIN rid USING (dokumnr)
> WHERE dok.kuupaev BETWEEN '2008-04-01' AND '2008-04-30'
> "Hash Join (cost=29584.84..308259.32 rows=142686 width=0) (actual
> time=68510.748..96932.174 rows=117883 loops=1)"
> " Hash Cond: ("outer".dokumnr = "inner".dokumnr)"
> " -> Seq Scan on rid (cost=0.00..195599.68 rows=3217368 width=4) (actual
> time=17.130..56572.857 rows=3247363 loops=1)"
> " -> Hash (cost=29243.76..29243.76 rows=53231 width=4) (actual
> time=15878.782..15878.782 rows=44685 loops=1)"
> " -> Index Scan using dok_kuupaev_idx on dok (cost=0.00..29243.76
> rows=53231 width=4) (actual time=47.102..15651.059 rows=44685 loops=1)"
> " Index Cond: ((kuupaev >= '2008-04-01'::date) AND (kuupaev <=
> '2008-04-30'::date))"
> "Total runtime: 97364.282 ms"
> Query performs seq scan over 3.2 million of rows.
There isn't anything particularly wrong with that plan. The alternative
that you seem to be wishing for would involve ~50000 index probes into
"rid", which is hardly going to be free.
You could try reducing random_page_cost to push the planner in the
direction of preferring the indexscan solution, but whether this is
actually better in your situation remains to be seen.
regards, tom lane
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