explain.depesz.com

PostgreSQL's explain analyze made readable

Result: 5ShP

Settings
# exclusive inclusive rows x rows loops node
1. 1.584 325.201 ↑ 1.0 1,000 1

Limit (cost=0.58..1,945,442.14 rows=1,000 width=12) (actual time=0.080..325.201 rows=1,000 loops=1)

2. 10.372 323.617 ↑ 52.4 1,000 1

Nested Loop (cost=0.58..101,974,210.98 rows=52,417 width=12) (actual time=0.078..323.617 rows=1,000 loops=1)

3. 20.245 20.245 ↑ 52.4 1,000 1

Index Scan Backward using empresas_sucursales_nro_patronal_key on empresas_sucursales (cost=0.29..5,658.86 rows=52,420 width=44) (actual time=0.014..20.245 rows=1,000 loops=1)

  • Filter: (type = 1)
  • Rows Removed by Filter: 148
4. 33.000 33.000 ↑ 1.0 1 1,000

Index Scan using empresas_pk on empresas emp (cost=0.29..0.38 rows=1 width=20) (actual time=0.032..0.033 rows=1 loops=1,000)

  • Index Cond: (id = empresas_sucursales.empresa_id)
  • Filter: (((document)::text <> '0'::text) AND ((document)::text <> ''::text) AND ((document)::text <> '-'::text))
5.          

SubPlan (forNested Loop)

6. 5.000 260.000 ↑ 1.0 1 1,000

Aggregate (cost=1,944.93..1,944.94 rows=1 width=8) (actual time=0.259..0.260 rows=1 loops=1,000)

7. 10.000 255.000 ↑ 60.0 1 1,000

Nested Loop (cost=0.72..1,944.78 rows=60 width=8) (actual time=0.103..0.255 rows=1 loops=1,000)

8. 15.000 15.000 ↑ 1.0 1 1,000

Index Only Scan using empresas_sucursales_nro_patronal_key on empresas_sucursales es (cost=0.29..2.31 rows=1 width=4) (actual time=0.014..0.015 rows=1 loops=1,000)

  • Index Cond: (nro_patronal = empresas_sucursales.nro_patronal)
  • Heap Fetches: 12
9. 59.280 230.000 ↑ 60.0 1 1,000

Index Scan using empleados_npatronal_idx on empleados (cost=0.43..1,941.87 rows=60 width=24) (actual time=0.083..0.230 rows=1 loops=1,000)

  • Index Cond: (npatronal = empresas_sucursales.nro_patronal)
  • Filter: (SubPlan 2)
  • Rows Removed by Filter: 0
10.          

SubPlan (forIndex Scan)

11. 6.208 170.720 ↑ 1.0 1 1,552

Limit (cost=14.15..14.15 rows=1 width=20) (actual time=0.110..0.110 rows=1 loops=1,552)

12. 10.864 164.512 ↑ 1.0 1 1,552

Sort (cost=14.15..14.15 rows=1 width=20) (actual time=0.106..0.106 rows=1 loops=1,552)

  • Sort Key: empleados_movimientos.fecha, empleados_movimientos.id
  • Sort Method: quicksort Memory: 25kB
13. 15.520 153.648 ↑ 1.0 1 1,552

Result (cost=0.43..14.14 rows=1 width=20) (actual time=0.092..0.099 rows=1 loops=1,552)

  • One-Time Filter: (empleados.empresa_id = emp.id)
14. 81.269 138.128 ↑ 1.0 1 1,552

Index Scan using empleados_movimientos_empleado_id_tipo_idx on empleados_movimientos (cost=0.43..14.13 rows=1 width=20) (actual time=0.084..0.089 rows=1 loops=1,552)

  • Index Cond: (empleado_id = empleados.id)
  • Filter: (NOT (SubPlan 1))
  • Rows Removed by Filter: 0
15.          

SubPlan (forIndex Scan)

16. 56.859 56.859 ↓ 0.0 0 1,723

Index Scan using multas_id_registro_multado_idx on multas (cost=0.00..4.02 rows=1 width=8) (actual time=0.033..0.033 rows=0 loops=1,723)

  • Index Cond: (id_registro_multado = empleados_movimientos.id)
  • Filter: ((estado IS NULL) AND (idtipo_multa = 11))
  • Rows Removed by Filter: 0