|
Hi,
I have query where I do two
inline queries (which involves grouping) and then join them with an outer
join.
The individual queries run in 50-300 ms. However
the optimizer is choosing a nested loop to join them rather than a Hash
join
causing the complete query to take 500+ seconds. It
expects that it will get 1 row out from each of the sources, but here is
gets
several thousand rows.
Is there any way I can get a hash join used on the
outer join, while preserving the nested loops.
explain analyze
select o1.objaddr, o1.fieldname, o1.objsig, o1.totmem, o1.cnt, o2.totmem, o2.cnt from ( select min(ao.objaddr) as objaddr, count(*) as cnt, sum(ao.totmem) as totmem, ao.objsig, ar.fieldname, ao.objtype from jam_heapobj ao, jam_heaprel ar where ar.heap_id = 1 and ar.parentaddr = 0 and ar.fieldname = 'K' and ao.heap_id = ar.heap_id and ao.objaddr = ar.childaddr group by ao.objsig, ar.fieldname, ao.objtype) o1 left outer join (select min(bo.objaddr) as objaddr, count(*) as cnt, sum(bo.totmem) as totmem, bo.objsig, br.fieldname, bo.objtype from jam_heapobj bo, jam_heaprel br where br.heap_id = 0 and br.parentaddr = 0 and br.fieldname = 'K' and bo.heap_id = br.heap_id and bo.objaddr = br.childaddr group by bo.objsig, br.fieldname, bo.objtype) o2 on ( o2.objsig = o1.objsig and o2.objtype = o1.objtype and o2.fieldname = o1.fieldname) order by o1.totmem - coalesce(o2.totmem,0) desc; Sort (cost=16305.41..16305.42 rows=1
width=562) (actual time=565997.769..566016.255 rows=6115 loops=1)
Sort Key: (o1.totmem - COALESCE(o2.totmem, 0::bigint)) ->Nested Loop Left Join (cost=16305.22..16305.40 rows=1 width=562) (actual time=612.631..565896.047 rows=6115 loops=1) Join Filter: ((("inner".objsig)::text = ("outer".objsig)::text) AND (("inner".objtype)::text = ("outer".objtype)::text) AND (("inner".fieldname)::text = ("outer".fieldname)::text)) ->Subquery Scan o1 (cost=12318.12..12318.15 rows=1 width=514) (actual time=309.659..413.311 rows=6115 loops=1) ->HashAggregate (cost=12318.12..12318.14 rows=1 width=54) (actual time=309.649..367.206 rows=6115 loops=1) ->Nested Loop (cost=0.00..12317.90 rows=10 width=54) (actual time=0.243..264.116 rows=6338 loops=1) ->Index Scan using jam_heaprel_n1 on jam_heaprel ar (cost=0.00..12275.00 rows=7 width=19) (actual time=0.176..35.780 rows=6338 loops=1) Index Cond: ((heap_id = 1) AND (parentaddr = 0)) Filter: ((fieldname)::text = 'K'::text) ->Index Scan using jam_heapobj_u1 on jam_heapobj ao (cost=0.00..6.10 rows=2 width=51) (actual time=0.019..0.022 rows=1 loops=6338) Index Cond: ((ao.heap_id = 1) AND (ao.objaddr = "outer".childaddr)) ->Subquery Scan o2 (cost=3987.10..3987.13 rows=1 width=514) (actual time=0.062..75.171 rows=6038 loops=6115) ->HashAggregate (cost=3987.10..3987.12 rows=1 width=54) (actual time=0.056..36.469 rows=6038 loops=6115) ->Nested Loop (cost=0.00..3987.05 rows=2 width=54) (actual time=0.145..257.876 rows=6259 loops=1) ->Index Scan using jam_heaprel_n1 on jam_heaprel br (cost=0.00..3974.01 rows=3 width=19) (actual time=0.074..35.124 rows=6259 loops=1) Index Cond: ((heap_id = 0) AND (parentaddr = 0)) Filter: ((fieldname)::text = 'K'::text) ->Index Scan using jam_heapobj_u1 on jam_heapobj bo (cost=0.00..4.33 rows=1 width=51) (actual time=0.018..0.022 rows=1 loops=6259) Index Cond: ((bo.heap_id = 0) AND (bo.objaddr = "outer".childaddr)) Total runtime: 566044.187 ms (21 rows) Regards,
Virag
|
