explain.depesz.com

A tool for finding a real cause for slow queries.

Result: Unm

options
# exclusive inclusive rows x rows loops node
1. 0.046 1.417 ↑ 1.0 1 1
→

HashAggregate (cost=49.96..50.08 rows=1 width=65) (actual time=1.417..1.417 rows=1 loops=1)

  • Filter: (sum(COALESCE(total.fis_qtd_servicos, 0::bigint)) > 0::numeric)
2.          

CTE total
3. 0.179 0.209 ↓ 1.1 145 1
→

HashAggregate (cost=4.77..6.48 rows=137 width=12) (actual time=0.157..0.209 rows=145 loops=1)

4. 0.030 0.030 ↑ 1.0 158 1
→

Seq Scan on fiscalizacao_operacoes_consolidado (cost=0.00..3.58 rows=158 width=12) (actual time=0.004..0.030 rows=158 loops=1)

5.          

CTE vincendas_mais_10
6. 0.032 0.079 ↓ 1.1 23 1
→

HashAggregate (cost=4.15..4.40 rows=20 width=12) (actual time=0.071..0.079 rows=23 loops=1)

7. 0.047 0.047 ↑ 1.0 23 1
→

Seq Scan on fiscalizacao_operacoes_consolidado (cost=0.00..3.98 rows=23 width=12) (actual time=0.013..0.047 rows=23 loops=1)

  • Filter: (fis_tipo_vencimento = 'Vincendas Mais 10 Dias'::text)
8.          

CTE vincendas_ate_10
9. 0.001 0.035 ↓ 0.0 0 1
→

HashAggregate (cost=3.98..3.99 rows=1 width=12) (actual time=0.035..0.035 rows=0 loops=1)

10. 0.034 0.034 ↓ 0.0 0 1
→

Seq Scan on fiscalizacao_operacoes_consolidado (cost=0.00..3.98 rows=1 width=12) (actual time=0.034..0.034 rows=0 loops=1)

  • Filter: (fis_tipo_vencimento = 'Vincendas Menos 10 Dias'::text)
11.          

CTE vencidas
12. 0.157 0.219 ↓ 1.1 128 1
→

HashAggregate (cost=4.99..6.46 rows=118 width=12) (actual time=0.173..0.219 rows=128 loops=1)

13. 0.062 0.062 ↑ 1.0 135 1
→

Seq Scan on fiscalizacao_operacoes_consolidado (cost=0.00..3.98 rows=135 width=12) (actual time=0.004..0.062 rows=135 loops=1)

  • Filter: (fis_tipo_vencimento = 'Vencidas'::text)
14.          

CTE devolvidas_cso
15. 0.150 0.202 ↓ 1.1 126 1
→

HashAggregate (cost=4.94..6.32 rows=111 width=12) (actual time=0.157..0.202 rows=126 loops=1)

16. 0.052 0.052 ↑ 1.0 128 1
→

Seq Scan on fiscalizacao_operacoes_consolidado (cost=0.00..3.98 rows=128 width=12) (actual time=0.005..0.052 rows=128 loops=1)

  • Filter: (fis_cd_identificacao = 9)
17. 0.016 1.371 ↓ 1.5 3 1
→

Hash Left Join (cost=13.62..22.20 rows=2 width=65) (actual time=1.351..1.371 rows=3 loops=1)

  • Hash Cond: (((d.prefdep)::bpchar = (vencidas.fis_prefixo)::bpchar) AND (tipos.tipo_m = vencidas.fis_mercado))
18. 0.004 0.982 ↓ 1.5 3 1
→

Nested Loop Left Join (cost=9.49..18.04 rows=2 width=89) (actual time=0.965..0.982 rows=3 loops=1)

  • Join Filter: (((vincendas_ate_10.fis_prefixo)::bpchar = (d.prefdep)::bpchar) AND (vincendas_ate_10.fis_mercado = tipos.tipo_m))
19. 0.015 0.942 ↓ 1.5 3 1
→

Hash Left Join (cost=9.49..17.98 rows=2 width=81) (actual time=0.928..0.942 rows=3 loops=1)

  • Hash Cond: (((d.prefdep)::bpchar = (devolvidas_cso.fis_prefixo)::bpchar) AND (tipos.tipo_m = devolvidas_cso.fis_mercado))
20. 0.018 0.574 ↓ 1.5 3 1
→

Hash Left Join (cost=5.61..14.07 rows=2 width=73) (actual time=0.562..0.574 rows=3 loops=1)

  • Hash Cond: (((d.prefdep)::bpchar = (total.fis_prefixo)::bpchar) AND (tipos.tipo_m = total.fis_mercado))
21. 0.017 0.179 ↓ 1.5 3 1
→

Hash Left Join (cost=0.81..9.25 rows=2 width=65) (actual time=0.170..0.179 rows=3 loops=1)

  • Hash Cond: (((d.prefdep)::bpchar = (vincendas_mais_10.fis_prefixo)::bpchar) AND (tipos.tipo_m = vincendas_mais_10.fis_mercado))
22. 0.004 0.052 ↓ 1.5 3 1
→

Nested Loop Left Join (cost=0.11..8.53 rows=2 width=57) (actual time=0.045..0.052 rows=3 loops=1)

23. 0.025 0.025 ↑ 1.0 1 1
→

Index Scan using tbldependenciasbr_pkey on tbldependenciasbr d (cost=0.00..8.28 rows=1 width=25) (actual time=0.024..0.025 rows=1 loops=1)

  • Index Cond: ((prefdep)::text = '8477'::text)
24. 0.006 0.023 ↓ 1.5 3 1
→

Subquery Scan on tipos (cost=0.11..0.23 rows=2 width=32) (actual time=0.018..0.023 rows=3 loops=1)

  • Filter: (tipos.tipo_m = ANY ('{VJ,JM,ES}'::text[]))
25. 0.009 0.017 ↑ 1.0 5 1
→

HashAggregate (cost=0.11..0.16 rows=5 width=0) (actual time=0.015..0.017 rows=5 loops=1)

26. 0.002 0.008 ↑ 1.0 5 1
→

Append (cost=0.00..0.10 rows=5 width=0) (actual time=0.002..0.008 rows=5 loops=1)

27. 0.001 0.002 ↑ 1.0 1 1
→

Subquery Scan on "*SELECT* 1" (cost=0.00..0.02 rows=1 width=0) (actual time=0.001..0.002 rows=1 loops=1)

28. 0.001 0.001 ↑ 1.0 1 1
→

Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.001..0.001 rows=1 loops=1)

29. 0.001 0.001 ↑ 1.0 1 1
→

Subquery Scan on "*SELECT* 2" (cost=0.00..0.02 rows=1 width=0) (actual time=0.001..0.001 rows=1 loops=1)

30. 0.000 0.000 ↑ 1.0 1 1
→

Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.000 rows=1 loops=1)

31. 0.001 0.001 ↑ 1.0 1 1
→

Subquery Scan on "*SELECT* 3" (cost=0.00..0.02 rows=1 width=0) (actual time=0.001..0.001 rows=1 loops=1)

32. 0.000 0.000 ↑ 1.0 1 1
→

Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.000 rows=1 loops=1)

33. 0.001 0.001 ↑ 1.0 1 1
→

Subquery Scan on "*SELECT* 4" (cost=0.00..0.02 rows=1 width=0) (actual time=0.001..0.001 rows=1 loops=1)

34. 0.000 0.000 ↑ 1.0 1 1
→

Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.000 rows=1 loops=1)

35. 0.001 0.001 ↑ 1.0 1 1
→

Subquery Scan on "*SELECT* 5" (cost=0.00..0.02 rows=1 width=0) (actual time=0.001..0.001 rows=1 loops=1)

36. 0.000 0.000 ↑ 1.0 1 1
→

Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.000 rows=1 loops=1)

37. 0.012 0.110 ↓ 1.1 23 1
→

Hash (cost=0.40..0.40 rows=20 width=72) (actual time=0.110..0.110 rows=23 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 2kB
38. 0.098 0.098 ↓ 1.1 23 1
→

CTE Scan on vincendas_mais_10 (cost=0.00..0.40 rows=20 width=72) (actual time=0.074..0.098 rows=23 loops=1)

39. 0.067 0.377 ↓ 1.1 145 1
→

Hash (cost=2.74..2.74 rows=137 width=72) (actual time=0.377..0.377 rows=145 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 7kB
40. 0.310 0.310 ↓ 1.1 145 1
→

CTE Scan on total (cost=0.00..2.74 rows=137 width=72) (actual time=0.159..0.310 rows=145 loops=1)

41. 0.061 0.353 ↓ 1.1 126 1
→

Hash (cost=2.22..2.22 rows=111 width=72) (actual time=0.353..0.353 rows=126 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 6kB
42. 0.292 0.292 ↓ 1.1 126 1
→

CTE Scan on devolvidas_cso (cost=0.00..2.22 rows=111 width=72) (actual time=0.158..0.292 rows=126 loops=1)

43. 0.036 0.036 ↓ 0.0 0 3
→

CTE Scan on vincendas_ate_10 (cost=0.00..0.02 rows=1 width=72) (actual time=0.012..0.012 rows=0 loops=3)

44. 0.063 0.373 ↓ 1.1 128 1
→

Hash (cost=2.36..2.36 rows=118 width=72) (actual time=0.373..0.373 rows=128 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 6kB
45. 0.310 0.310 ↓ 1.1 128 1
→

CTE Scan on vencidas (cost=0.00..2.36 rows=118 width=72) (actual time=0.174..0.310 rows=128 loops=1)