explain.depesz.com

PostgreSQL's explain analyze made readable

Result: DUWt

Settings
# exclusive inclusive rows x rows loops node
1. 12,990.187 12,990.187 ↓ 40.9 21,612,912 1

CTE Scan on metricas (cost=15,992.88..26,552.88 rows=528,000 width=100) (actual time=238.376..12,990.187 rows=21,612,912 loops=1)

2.          

CTE info_dataset

3. 226.368 228.345 ↓ 4.9 257 1

Nested Loop (cost=0.84..45.48 rows=52 width=754) (actual time=1.401..228.345 rows=257 loops=1)

4. 0.063 1.720 ↓ 4.9 257 1

Nested Loop (cost=0.56..22.05 rows=52 width=436) (actual time=0.598..1.720 rows=257 loops=1)

5. 0.122 0.122 ↑ 1.0 1 1

Index Scan using eo_fk_cc_idx on evento_operacao eo (cost=0.28..1.40 rows=1 width=595) (actual time=0.015..0.122 rows=1 loops=1)

  • Index Cond: (cd_cliente = 2)
  • Filter: (cd_id = 17,660)
  • Rows Removed by Filter: 142
6. 0.042 1.535 ↓ 85.7 257 1

Append (cost=0.28..20.62 rows=3 width=444) (actual time=0.581..1.535 rows=257 loops=1)

7. 1.493 1.493 ↓ 85.7 257 1

Index Scan using ddn_trecho2_pkey on ddn_trecho2 tot (cost=0.28..20.61 rows=3 width=444) (actual time=0.574..1.493 rows=257 loops=1)

  • Index Cond: ((cd_cliente = 2) AND (cd_id = ANY (eo.vl_trechos_arr)))
  • Filter: ((dt_created)::date >= '2020-07-02'::date)
  • Rows Removed by Filter: 242
8. 0.257 0.257 ↑ 1.0 1 257

Index Scan using cdt_equipamento_pkey on cdt_equipamento eq (cost=0.28..0.35 rows=1 width=11) (actual time=0.001..0.001 rows=1 loops=257)

  • Index Cond: (cd_id = tot.cd_id_equipamento)
9.          

CTE metricas

10. 1,533.102 7,129.547 ↓ 40.9 21,612,912 1

Append (cost=5.72..15,947.40 rows=528,000 width=100) (actual time=238.375..7,129.547 rows=21,612,912 loops=1)

11. 0.000 234.534 ↓ 0.0 0 1

Subquery Scan on d (cost=5.72..501.71 rows=33,000 width=100) (actual time=234.534..234.534 rows=0 loops=1)

12. 0.001 234.534 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=234.534..234.534 rows=0 loops=1)

13. 0.002 234.533 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=234.533..234.533 rows=0 loops=1)

  • Group Key: a.campo
14. 0.413 234.531 ↓ 0.0 0 1

Subquery Scan on a (cost=0.00..5.56 rows=33 width=64) (actual time=234.531..234.531 rows=0 loops=1)

  • Filter: (a.campo <= '0'::numeric)
  • Rows Removed by Filter: 5,123
15. 1.785 234.118 ↓ 51.2 5,123 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=1.431..234.118 rows=5,123 loops=1)

16. 3.294 232.333 ↓ 51.2 5,123 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=1.429..232.333 rows=5,123 loops=1)

17. 229.039 229.039 ↓ 255.0 255 1

CTE Scan on info_dataset ds (cost=0.00..1.30 rows=1 width=32) (actual time=1.407..229.039 rows=255 loops=1)

  • Filter: ((massa IS NOT NULL) AND (jsonb_typeof(massa) = 'object'::text))
  • Rows Removed by Filter: 2
18. 0.001 3.007 ↓ 0.0 0 1

Subquery Scan on d_1 (cost=5.72..501.71 rows=33,000 width=100) (actual time=3.007..3.007 rows=0 loops=1)

19. 0.000 3.006 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=3.006..3.006 rows=0 loops=1)

20. 0.002 3.006 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=3.006..3.006 rows=0 loops=1)

  • Group Key: a_1.campo
21. 0.192 3.004 ↓ 0.0 0 1

Subquery Scan on a_1 (cost=0.00..5.56 rows=33 width=64) (actual time=3.004..3.004 rows=0 loops=1)

  • Filter: (a_1.campo <= '0'::numeric)
  • Rows Removed by Filter: 2,716
22. 0.907 2.812 ↓ 27.2 2,716 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.018..2.812 rows=2,716 loops=1)

23. 1.772 1.905 ↓ 27.2 2,716 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.016..1.905 rows=2,716 loops=1)

24. 0.133 0.133 ↓ 257.0 257 1

CTE Scan on info_dataset ds_1 (cost=0.00..1.30 rows=1 width=32) (actual time=0.004..0.133 rows=257 loops=1)

  • Filter: ((rpm IS NOT NULL) AND (jsonb_typeof(rpm) = 'object'::text))
25. 499.772 1,345.638 ↓ 163.7 5,403,228 1

Subquery Scan on d_2 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.832..1,345.638 rows=5,403,228 loops=1)

26. 845.036 845.866 ↓ 163.7 5,403,228 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.831..845.866 rows=5,403,228 loops=1)

27. 0.070 0.830 ↑ 33.0 1 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.828..0.830 rows=1 loops=1)

  • Group Key: a_2.campo
28. 0.033 0.760 ↓ 7.8 257 1

Subquery Scan on a_2 (cost=0.00..5.56 rows=33 width=64) (actual time=0.008..0.760 rows=257 loops=1)

  • Filter: (a_2.campo <= '0'::numeric)
29. 0.090 0.727 ↓ 2.6 257 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.006..0.727 rows=257 loops=1)

30. 0.548 0.637 ↓ 2.6 257 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.005..0.637 rows=257 loops=1)

31. 0.089 0.089 ↓ 257.0 257 1

CTE Scan on info_dataset ds_2 (cost=0.00..1.30 rows=1 width=32) (actual time=0.001..0.089 rows=257 loops=1)

  • Filter: ((umidade IS NOT NULL) AND (jsonb_typeof(umidade) = 'object'::text))
32. 0.001 0.142 ↓ 0.0 0 1

Subquery Scan on d_3 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.142..0.142 rows=0 loops=1)

33. 0.000 0.141 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.141..0.141 rows=0 loops=1)

34. 0.001 0.141 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.141..0.141 rows=0 loops=1)

  • Group Key: a_3.campo
35. 0.001 0.140 ↓ 0.0 0 1

Subquery Scan on a_3 (cost=0.00..5.56 rows=33 width=64) (actual time=0.140..0.140 rows=0 loops=1)

  • Filter: (a_3.campo <= '0'::numeric)
36. 0.000 0.139 ↓ 0.0 0 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.139..0.139 rows=0 loops=1)

37. 0.001 0.139 ↓ 0.0 0 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.139..0.139 rows=0 loops=1)

38. 0.138 0.138 ↓ 0.0 0 1

CTE Scan on info_dataset ds_3 (cost=0.00..1.30 rows=1 width=32) (actual time=0.138..0.138 rows=0 loops=1)

  • Filter: ((vazao_ha IS NOT NULL) AND (jsonb_typeof(vazao_ha) = 'object'::text))
  • Rows Removed by Filter: 257
39. 0.001 0.070 ↓ 0.0 0 1

Subquery Scan on d_4 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.070..0.070 rows=0 loops=1)

40. 0.000 0.069 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.069..0.069 rows=0 loops=1)

41. 0.001 0.069 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.069..0.069 rows=0 loops=1)

  • Group Key: a_4.campo
42. 0.000 0.068 ↓ 0.0 0 1

Subquery Scan on a_4 (cost=0.00..5.56 rows=33 width=64) (actual time=0.068..0.068 rows=0 loops=1)

  • Filter: (a_4.campo <= '0'::numeric)
43. 0.001 0.068 ↓ 0.0 0 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.068..0.068 rows=0 loops=1)

44. 0.000 0.067 ↓ 0.0 0 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.067..0.067 rows=0 loops=1)

45. 0.067 0.067 ↓ 0.0 0 1

CTE Scan on info_dataset ds_4 (cost=0.00..1.30 rows=1 width=32) (actual time=0.067..0.067 rows=0 loops=1)

  • Filter: ((vazao_min IS NOT NULL) AND (jsonb_typeof(vazao_min) = 'object'::text))
  • Rows Removed by Filter: 257
46. 0.000 2.485 ↓ 0.0 0 1

Subquery Scan on d_5 (cost=5.72..501.71 rows=33,000 width=100) (actual time=2.485..2.485 rows=0 loops=1)

47. 0.000 2.485 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=2.485..2.485 rows=0 loops=1)

48. 0.002 2.485 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=2.485..2.485 rows=0 loops=1)

  • Group Key: a_5.campo
49. 0.157 2.483 ↓ 0.0 0 1

Subquery Scan on a_5 (cost=0.00..5.56 rows=33 width=64) (actual time=2.483..2.483 rows=0 loops=1)

  • Filter: (a_5.campo <= '0'::numeric)
  • Rows Removed by Filter: 2,202
50. 0.724 2.326 ↓ 22.0 2,202 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.032..2.326 rows=2,202 loops=1)

51. 1.522 1.602 ↓ 22.0 2,202 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.028..1.602 rows=2,202 loops=1)

52. 0.080 0.080 ↓ 257.0 257 1

CTE Scan on info_dataset ds_5 (cost=0.00..1.30 rows=1 width=32) (actual time=0.002..0.080 rows=257 loops=1)

  • Filter: ((velocidade IS NOT NULL) AND (jsonb_typeof(velocidade) = 'object'::text))
53. 499.186 1,335.965 ↓ 163.7 5,403,228 1

Subquery Scan on d_6 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.837..1,335.965 rows=5,403,228 loops=1)

54. 835.943 836.779 ↓ 163.7 5,403,228 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.836..836.779 rows=5,403,228 loops=1)

55. 0.074 0.836 ↑ 33.0 1 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.834..0.836 rows=1 loops=1)

  • Group Key: a_6.campo
56. 0.037 0.762 ↓ 7.8 257 1

Subquery Scan on a_6 (cost=0.00..5.56 rows=33 width=64) (actual time=0.007..0.762 rows=257 loops=1)

  • Filter: (a_6.campo <= '0'::numeric)
57. 0.094 0.725 ↓ 2.6 257 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.006..0.725 rows=257 loops=1)

58. 0.551 0.631 ↓ 2.6 257 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.005..0.631 rows=257 loops=1)

59. 0.080 0.080 ↓ 257.0 257 1

CTE Scan on info_dataset ds_6 (cost=0.00..1.30 rows=1 width=32) (actual time=0.001..0.080 rows=257 loops=1)

  • Filter: ((temperatura IS NOT NULL) AND (jsonb_typeof(temperatura) = 'object'::text))
60. 499.171 1,335.511 ↓ 163.7 5,403,228 1

Subquery Scan on d_7 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.941..1,335.511 rows=5,403,228 loops=1)

61. 835.400 836.340 ↓ 163.7 5,403,228 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.940..836.340 rows=5,403,228 loops=1)

62. 0.072 0.940 ↑ 33.0 1 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.938..0.940 rows=1 loops=1)

  • Group Key: a_7.campo
63. 0.033 0.868 ↓ 7.8 257 1

Subquery Scan on a_7 (cost=0.00..5.56 rows=33 width=64) (actual time=0.046..0.868 rows=257 loops=1)

  • Filter: (a_7.campo <= '0'::numeric)
64. 0.095 0.835 ↓ 2.6 257 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.045..0.835 rows=257 loops=1)

65. 0.585 0.740 ↓ 2.6 257 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.039..0.740 rows=257 loops=1)

66. 0.155 0.155 ↓ 257.0 257 1

CTE Scan on info_dataset ds_7 (cost=0.00..1.30 rows=1 width=32) (actual time=0.006..0.155 rows=257 loops=1)

  • Filter: ((ponto_orvalho IS NOT NULL) AND (jsonb_typeof(ponto_orvalho) = 'object'::text))
67. 0.000 0.148 ↓ 0.0 0 1

Subquery Scan on d_8 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.148..0.148 rows=0 loops=1)

68. 0.001 0.148 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.147..0.148 rows=0 loops=1)

69. 0.002 0.147 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.147..0.147 rows=0 loops=1)

  • Group Key: a_8.campo
70. 0.000 0.145 ↓ 0.0 0 1

Subquery Scan on a_8 (cost=0.00..5.56 rows=33 width=64) (actual time=0.145..0.145 rows=0 loops=1)

  • Filter: (a_8.campo <= '0'::numeric)
71. 0.001 0.145 ↓ 0.0 0 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.145..0.145 rows=0 loops=1)

72. 0.001 0.144 ↓ 0.0 0 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.144..0.144 rows=0 loops=1)

73. 0.143 0.143 ↓ 0.0 0 1

CTE Scan on info_dataset ds_8 (cost=0.00..1.30 rows=1 width=32) (actual time=0.143..0.143 rows=0 loops=1)

  • Filter: ((consumo_inst IS NOT NULL) AND (jsonb_typeof(consumo_inst) = 'object'::text))
  • Rows Removed by Filter: 257
74. 0.001 0.079 ↓ 0.0 0 1

Subquery Scan on d_9 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.079..0.079 rows=0 loops=1)

75. 0.000 0.078 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.078..0.078 rows=0 loops=1)

76. 0.001 0.078 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.078..0.078 rows=0 loops=1)

  • Group Key: a_9.campo
77. 0.001 0.077 ↓ 0.0 0 1

Subquery Scan on a_9 (cost=0.00..5.56 rows=33 width=64) (actual time=0.077..0.077 rows=0 loops=1)

  • Filter: (a_9.campo <= '0'::numeric)
78. 0.000 0.076 ↓ 0.0 0 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.076..0.076 rows=0 loops=1)

79. 0.000 0.076 ↓ 0.0 0 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.076..0.076 rows=0 loops=1)

80. 0.076 0.076 ↓ 0.0 0 1

CTE Scan on info_dataset ds_9 (cost=0.00..1.30 rows=1 width=32) (actual time=0.076..0.076 rows=0 loops=1)

  • Filter: ((pressao_bomba IS NOT NULL) AND (jsonb_typeof(pressao_bomba) = 'object'::text))
  • Rows Removed by Filter: 257
81. 502.997 1,338.390 ↓ 163.7 5,403,228 1

Subquery Scan on d_10 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.868..1,338.390 rows=5,403,228 loops=1)

82. 834.527 835.393 ↓ 163.7 5,403,228 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.867..835.393 rows=5,403,228 loops=1)

83. 0.070 0.866 ↑ 33.0 1 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.865..0.866 rows=1 loops=1)

  • Group Key: a_10.campo
84. 0.031 0.796 ↓ 7.8 257 1

Subquery Scan on a_10 (cost=0.00..5.56 rows=33 width=64) (actual time=0.041..0.796 rows=257 loops=1)

  • Filter: (a_10.campo <= '0'::numeric)
85. 0.100 0.765 ↓ 2.6 257 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.040..0.765 rows=257 loops=1)

86. 0.579 0.665 ↓ 2.6 257 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.034..0.665 rows=257 loops=1)

87. 0.086 0.086 ↓ 257.0 257 1

CTE Scan on info_dataset ds_10 (cost=0.00..1.30 rows=1 width=32) (actual time=0.002..0.086 rows=257 loops=1)

  • Filter: ((umidade_graos IS NOT NULL) AND (jsonb_typeof(umidade_graos) = 'object'::text))
88. 0.001 0.166 ↓ 0.0 0 1

Subquery Scan on d_11 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.165..0.166 rows=0 loops=1)

89. 0.001 0.165 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.165..0.165 rows=0 loops=1)

90. 0.001 0.164 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.164..0.164 rows=0 loops=1)

  • Group Key: a_11.campo
91. 0.001 0.163 ↓ 0.0 0 1

Subquery Scan on a_11 (cost=0.00..5.56 rows=33 width=64) (actual time=0.163..0.163 rows=0 loops=1)

  • Filter: (a_11.campo <= '0'::numeric)
92. 0.000 0.162 ↓ 0.0 0 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.162..0.162 rows=0 loops=1)

93. 0.001 0.162 ↓ 0.0 0 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.161..0.162 rows=0 loops=1)

94. 0.161 0.161 ↓ 0.0 0 1

CTE Scan on info_dataset ds_11 (cost=0.00..1.30 rows=1 width=32) (actual time=0.161..0.161 rows=0 loops=1)

  • Filter: ((rendimento_oper IS NOT NULL) AND (jsonb_typeof(rendimento_oper) = 'object'::text))
  • Rows Removed by Filter: 257
95. 0.000 0.086 ↓ 0.0 0 1

Subquery Scan on d_12 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.086..0.086 rows=0 loops=1)

96. 0.001 0.086 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.086..0.086 rows=0 loops=1)

97. 0.001 0.085 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.085..0.085 rows=0 loops=1)

  • Group Key: a_12.campo
98. 0.000 0.084 ↓ 0.0 0 1

Subquery Scan on a_12 (cost=0.00..5.56 rows=33 width=64) (actual time=0.084..0.084 rows=0 loops=1)

  • Filter: (a_12.campo <= '0'::numeric)
99. 0.001 0.084 ↓ 0.0 0 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.084..0.084 rows=0 loops=1)

100. 0.000 0.083 ↓ 0.0 0 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.083..0.083 rows=0 loops=1)

101. 0.083 0.083 ↓ 0.0 0 1

CTE Scan on info_dataset ds_12 (cost=0.00..1.30 rows=1 width=32) (actual time=0.083..0.083 rows=0 loops=1)

  • Filter: ((velocidade_vento IS NOT NULL) AND (jsonb_typeof(velocidade_vento) = 'object'::text))
  • Rows Removed by Filter: 257
102. 0.000 0.074 ↓ 0.0 0 1

Subquery Scan on d_13 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.074..0.074 rows=0 loops=1)

103. 0.001 0.074 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.074..0.074 rows=0 loops=1)

104. 0.001 0.073 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.073..0.073 rows=0 loops=1)

  • Group Key: a_13.campo
105. 0.001 0.072 ↓ 0.0 0 1

Subquery Scan on a_13 (cost=0.00..5.56 rows=33 width=64) (actual time=0.071..0.072 rows=0 loops=1)

  • Filter: (a_13.campo <= '0'::numeric)
106. 0.000 0.071 ↓ 0.0 0 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.071..0.071 rows=0 loops=1)

107. 0.001 0.071 ↓ 0.0 0 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.071..0.071 rows=0 loops=1)

108. 0.070 0.070 ↓ 0.0 0 1

CTE Scan on info_dataset ds_13 (cost=0.00..1.30 rows=1 width=32) (actual time=0.070..0.070 rows=0 loops=1)

  • Filter: ((temperatura_motor IS NOT NULL) AND (jsonb_typeof(temperatura_motor) = 'object'::text))
  • Rows Removed by Filter: 257
109. 0.000 0.074 ↓ 0.0 0 1

Subquery Scan on d_14 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.074..0.074 rows=0 loops=1)

110. 0.001 0.074 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.074..0.074 rows=0 loops=1)

111. 0.001 0.073 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.073..0.073 rows=0 loops=1)

  • Group Key: a_14.campo
112. 0.000 0.072 ↓ 0.0 0 1

Subquery Scan on a_14 (cost=0.00..5.56 rows=33 width=64) (actual time=0.072..0.072 rows=0 loops=1)

  • Filter: (a_14.campo <= '0'::numeric)
113. 0.000 0.072 ↓ 0.0 0 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.072..0.072 rows=0 loops=1)

114. 0.000 0.072 ↓ 0.0 0 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.072..0.072 rows=0 loops=1)

115. 0.072 0.072 ↓ 0.0 0 1

CTE Scan on info_dataset ds_14 (cost=0.00..1.30 rows=1 width=32) (actual time=0.072..0.072 rows=0 loops=1)

  • Filter: ((qtde_sementes_metros IS NOT NULL) AND (jsonb_typeof(qtde_sementes_metros) = 'object'::text))
  • Rows Removed by Filter: 257
116. 0.001 0.076 ↓ 0.0 0 1

Subquery Scan on d_15 (cost=5.72..501.71 rows=33,000 width=100) (actual time=0.076..0.076 rows=0 loops=1)

117. 0.001 0.075 ↓ 0.0 0 1

ProjectSet (cost=5.72..171.71 rows=33,000 width=128) (actual time=0.075..0.075 rows=0 loops=1)

118. 0.001 0.074 ↓ 0.0 0 1

HashAggregate (cost=5.72..6.13 rows=33 width=64) (actual time=0.074..0.074 rows=0 loops=1)

  • Group Key: a_15.campo
119. 0.000 0.073 ↓ 0.0 0 1

Subquery Scan on a_15 (cost=0.00..5.56 rows=33 width=64) (actual time=0.073..0.073 rows=0 loops=1)

  • Filter: (a_15.campo <= '0'::numeric)
120. 0.001 0.073 ↓ 0.0 0 1

Result (cost=0.00..4.31 rows=100 width=64) (actual time=0.073..0.073 rows=0 loops=1)

121. 0.000 0.072 ↓ 0.0 0 1

ProjectSet (cost=0.00..1.81 rows=100 width=32) (actual time=0.072..0.072 rows=0 loops=1)

122. 0.072 0.072 ↓ 0.0 0 1

CTE Scan on info_dataset ds_15 (cost=0.00..1.30 rows=1 width=32) (actual time=0.072..0.072 rows=0 loops=1)

  • Filter: ((qtde_sementes_ha IS NOT NULL) AND (jsonb_typeof(qtde_sementes_ha) = 'object'::text))
  • Rows Removed by Filter: 257
Planning time : 2.084 ms
Execution time : 13,932.951 ms