#	exclusive	inclusive	rows x	rows	loops	node
1.	0.045	24.827	↑ 1.0	4	1	→ Sort (cost=1,553.74..1,553.75 rows=4 width=25) (actual time=24.826..24.827 rows=4 loops=1) Sort Key: pui.cod_prod_use Sort Method: quicksort Memory: 25kB
2.	2.352	24.782	↑ 1.0	4	1	→ HashAggregate (cost=1,553.66..1,553.70 rows=4 width=25) (actual time=24.781..24.782 rows=4 loops=1) Group Key: pui.cod_prod_use, pui.name
3.	1.911	22.430	↑ 1.1	4,017	1	→ Hash Join (cost=798.35..1,519.47 rows=4,558 width=17) (actual time=11.298..22.430 rows=4,017 loops=1) Hash Cond: (p.cod_prod_use = pui.cod_prod_use)
4.	5.182	20.494	↑ 1.1	4,017	1	→ Hash Join (cost=797.15..1,438.51 rows=4,558 width=4) (actual time=11.263..20.494 rows=4,017 loops=1) Hash Cond: (prod.cod_producto = p.cod_producto)
5.	4.236	4.236	↑ 1.0	15,255	1	→ Seq Scan on productos prod (cost=0.00..538.46 rows=15,286 width=4) (actual time=0.008..4.236 rows=15,255 loops=1)
6.	1.518	11.076	↑ 1.1	4,017	1	→ Hash (cost=740.17..740.17 rows=4,558 width=8) (actual time=11.076..11.076 rows=4,017 loops=1) Buckets: 8192 Batches: 1 Memory Usage: 221kB
7.	9.558	9.558	↑ 1.1	4,017	1	→ Seq Scan on v_productos_es p (cost=0.00..740.17 rows=4,558 width=8) (actual time=0.010..9.558 rows=4,017 loops=1) Filter: ((cod_prod_role = ANY ('{1,2}'::integer[])) AND ((visible_web)::text = 'S'::text)) Rows Removed by Filter: 4421
8.	0.004	0.025	↑ 1.0	4	1	→ Hash (cost=1.15..1.15 rows=4 width=17) (actual time=0.025..0.025 rows=4 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 9kB
9.	0.021	0.021	↑ 1.0	4	1	→ Seq Scan on prods_uses_idioma pui (cost=0.00..1.15 rows=4 width=17) (actual time=0.014..0.021 rows=4 loops=1) Filter: ((cod_idioma)::text = 'es'::text) Rows Removed by Filter: 24

"Sort  (cost=1553.74..1553.75 rows=4 width=25) (actual time=24.826..24.827 rows=4 loops=1)"
"  Sort Key: pui.cod_prod_use"
"  Sort Method: quicksort  Memory: 25kB"
"  ->  HashAggregate  (cost=1553.66..1553.70 rows=4 width=25) (actual time=24.781..24.782 rows=4 loops=1)"
"        Group Key: pui.cod_prod_use, pui.name"
"        ->  Hash Join  (cost=798.35..1519.47 rows=4558 width=17) (actual time=11.298..22.430 rows=4017 loops=1)"
"              Hash Cond: (p.cod_prod_use = pui.cod_prod_use)"
"              ->  Hash Join  (cost=797.15..1438.51 rows=4558 width=4) (actual time=11.263..20.494 rows=4017 loops=1)"
"                    Hash Cond: (prod.cod_producto = p.cod_producto)"
"                    ->  Seq Scan on productos prod  (cost=0.00..538.46 rows=15286 width=4) (actual time=0.008..4.236 rows=15255 loops=1)"
"                    ->  Hash  (cost=740.17..740.17 rows=4558 width=8) (actual time=11.076..11.076 rows=4017 loops=1)"
"                          Buckets: 8192  Batches: 1  Memory Usage: 221kB"
"                          ->  Seq Scan on v_productos_es p  (cost=0.00..740.17 rows=4558 width=8) (actual time=0.010..9.558 rows=4017 loops=1)"
"                                Filter: ((cod_prod_role = ANY ('{1,2}'::integer[])) AND ((visible_web)::text = 'S'::text))"
"                                Rows Removed by Filter: 4421"
"              ->  Hash  (cost=1.15..1.15 rows=4 width=17) (actual time=0.025..0.025 rows=4 loops=1)"
"                    Buckets: 1024  Batches: 1  Memory Usage: 9kB"
"                    ->  Seq Scan on prods_uses_idioma pui  (cost=0.00..1.15 rows=4 width=17) (actual time=0.014..0.021 rows=4 loops=1)"
"                          Filter: ((cod_idioma)::text = 'es'::text)"
"                          Rows Removed by Filter: 24"
"Planning time: 0.742 ms"
"Execution time: 24.923 ms"

Per node type stats

node type	count	sum of times	% of query
Hash	2	1.522 ms	6.1 %
Hash Join	2	7.093 ms	28.6 %
HashAggregate	1	2.352 ms	9.5 %
Seq Scan	3	13.815 ms	55.6 %
Sort	1	0.045 ms	0.2 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
prods_uses_idioma	1	0.021 ms	0.1 %
Seq Scan	1	0.021 ms	100.0 %
productos	1	4.236 ms	17.1 %
Seq Scan	1	4.236 ms	100.0 %
v_productos_es	1	9.558 ms	38.5 %
Seq Scan	1	9.558 ms	100.0 %

explain.depesz.com

PostgreSQL's explain analyze made readable

Result: CXnm : Optimization for: plan #pkK9

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Per node type stats

Per table stats