#	exclusive	inclusive	rows x	rows	loops	node
1.	0.328	24.474	↓ 57.0	171	1	→ Nested Loop Left Join (cost=0.00..13127.98 rows=3 width=177) (actual time=19.764..24.474 rows=171 loops=1)
2.	0.137	23.633	↓ 57.0	171	1	→ Nested Loop Left Join (cost=0.00..13124.70 rows=3 width=182) (actual time=19.746..23.633 rows=171 loops=1)
3.	0.115	22.983	↓ 57.0	171	1	→ Nested Loop (cost=0.00..13121.38 rows=3 width=174) (actual time=19.738..22.983 rows=171 loops=1)
4.	21.594	21.594	↓ 91.0	91	1	→ Index Scan using idx_venda_status_datahorafechamento on venda venda0_ (cost=0.00..13108.56 rows=1 width=123) (actual time=0.861..21.594 rows=91 loops=1) Index Cond: (datahorafechamento >= '2012-04-09 00:00:00'::timestamp without time zone) Filter: ((ecfid = 100001858071::bigint) AND ((coo)::integer <= 31615))
5.	1.274	1.274	↑ 1.5	2	91	→ Index Scan using idx_itemvenda_status_vendaid on itemvenda itens1_ (cost=0.00..12.79 rows=3 width=59) (actual time=0.013..0.014 rows=2 loops=91) Index Cond: ((itens1_.status = 'F'::bpchar) AND (itens1_.vendaid = venda0_.id))
6.	0.513	0.513	↑ 1.0	1	171	→ Index Scan using pk_embalagem on embalagem embalagem2_ (cost=0.00..1.09 rows=1 width=16) (actual time=0.003..0.003 rows=1 loops=171) Index Cond: (itens1_.embalagemid = embalagem2_.id)
7.	0.513	0.513	↑ 1.0	1	171	→ Index Scan using pk_produto on produto produto3_ (cost=0.00..1.08 rows=1 width=11) (actual time=0.003..0.003 rows=1 loops=171) Index Cond: (embalagem2_.produtoid = produto3_.id)

"Nested Loop Left Join  (cost=0.00..13127.98 rows=3 width=177) (actual time=19.764..24.474 rows=171 loops=1)"
"  ->  Nested Loop Left Join  (cost=0.00..13124.70 rows=3 width=182) (actual time=19.746..23.633 rows=171 loops=1)"
"        ->  Nested Loop  (cost=0.00..13121.38 rows=3 width=174) (actual time=19.738..22.983 rows=171 loops=1)"
"              ->  Index Scan using idx_venda_status_datahorafechamento on venda venda0_  (cost=0.00..13108.56 rows=1 width=123) (actual time=0.861..21.594 rows=91 loops=1)"
"                    Index Cond: (datahorafechamento >= '2012-04-09 00:00:00'::timestamp without time zone)"
"                    Filter: ((ecfid = 100001858071::bigint) AND ((coo)::integer <= 31615))"
"              ->  Index Scan using idx_itemvenda_status_vendaid on itemvenda itens1_  (cost=0.00..12.79 rows=3 width=59) (actual time=0.013..0.014 rows=2 loops=91)"
"                    Index Cond: ((itens1_.status = 'F'::bpchar) AND (itens1_.vendaid = venda0_.id))"
"        ->  Index Scan using pk_embalagem on embalagem embalagem2_  (cost=0.00..1.09 rows=1 width=16) (actual time=0.003..0.003 rows=1 loops=171)"
"              Index Cond: (itens1_.embalagemid = embalagem2_.id)"
"  ->  Index Scan using pk_produto on produto produto3_  (cost=0.00..1.08 rows=1 width=11) (actual time=0.003..0.003 rows=1 loops=171)"
"        Index Cond: (embalagem2_.produtoid = produto3_.id)"
"Total runtime: 24.577 ms"

Per node type stats

node type	count	sum of times	% of query
Index Scan	4	23.894 ms	97.6 %
Nested Loop	1	0.115 ms	0.5 %
Nested Loop Left Join	2	0.465 ms	1.9 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
embalagem	1	0.513 ms	2.1 %
Index Scan	1	0.513 ms	100.0 %
itemvenda	1	1.274 ms	5.2 %
Index Scan	1	1.274 ms	100.0 %
produto	1	0.513 ms	2.1 %
Index Scan	1	0.513 ms	100.0 %
venda	1	21.594 ms	88.2 %
Index Scan	1	21.594 ms	100.0 %

explain.depesz.com

A tool for finding a real cause for slow queries.

Result: QQ2Q

Colorize:

Columns visibility:

Per node type stats

Per table stats