> Aggregate (cost=5975.66..5975.66 rows=1 width=131) (actual
time=1264.12..1264.13 rows=1 loops=1)
> -> Hash Join (cost=5958.18..5975.58 rows=35 width=131) (actual
time=1205.90..1262.46 rows=1606 loops=1)
> -> Hash Join (cost=5956.30..5972.99 rows=35 width=127) (actual
time=1197.85..1248.93 rows=1606 loops=1)
2)
> emep=> explain analyze select count(*) from EmissionsView ,
DataSetsView where DataSetsView.setid = EmissionsView.setid and
DataSetsView.setid = '4614' ;
> NOTICE: QUERY PLAN:
>
> Aggregate (cost=91660.36..91660.36 rows=1 width=131) (actual
time=64414.80..64414.80 rows=1 loops=1)
> -> Hash Join (cost=2732.23..91660.35 rows=3 width=131) (actual
time=58428.47..64413.14 rows=1606 loops=1)
> -> Nested Loop (cost=2719.53..91058.61 rows=117798 width=103)
(actual time=49523.50..63005.67 rows=1025405 loops=1)
I think here is the difference, in the first case you are performing
hash-join from 33000 rows, in second case it is from 1M rows, so it is
wasting time on hashing, it seems that 1st conditions are more restrictive
than the second one. I mean there are less 4614 on EmissionsView than on
DataSetsView
Regards
