explain.depesz.com

PostgreSQL's explain analyze made readable

Result: jiCc : Optimization for: Optimization for: plan #CZXl; plan #VexT

Settings

Optimization path:

# exclusive inclusive rows x rows loops node
1. 18.042 8,527.156 ↓ 80.2 1,523 1

Gather (cost=1,000.29..38,911,820.66 rows=19 width=44) (actual time=60.714..8,527.156 rows=1,523 loops=1)

  • Workers Planned: 2
  • Workers Launched: 2
2. 8.161 8,509.114 ↓ 63.5 508 3 / 3

Nested Loop (cost=0.29..38,910,818.76 rows=8 width=44) (actual time=45.792..8,509.114 rows=508 loops=3)

3. 63.409 63.409 ↑ 11.5 344 3 / 3

Parallel Seq Scan on forecast_daily fd (cost=0.00..14,561.80 rows=3,964 width=56) (actual time=19.497..63.409 rows=344 loops=3)

  • Filter: ((forecast_date >= '2018-11-01'::date) AND (forecast_date <= '2019-01-01'::date) AND (nb_hours = 24))
  • Rows Removed by Filter: 234,984
4. 8,437.544 8,437.544 ↑ 1.0 1 1,033 / 3

Index Scan using area_of_implantation_btree_for_date on area_of_implantation ai (cost=0.29..9,812.37 rows=1 width=56) (actual time=17.696..24.504 rows=1 loops=1,033)

  • Index Cond: (fd.forecast_date >= start_date)
  • Filter: ((fd.forecast_date <= COALESCE(end_date, CURRENT_DATE)) AND (area && _st_expand((fd.point)::geography, '100'::double precision)) AND ((fd.point)::geography && _st_expand(area, '100'::double precision)) AND _st_dwithin(area, (fd.point)::geography, '100'::double precision, true))
  • Rows Removed by Filter: 14,675
Planning time : 0.220 ms
Execution time : 8,527.589 ms