explain.depesz.com

PostgreSQL's explain analyze made readable

Result: jPAj : Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: plan #jjT8; plan #R0k; plan #RqOF; plan #yjc; plan #fWeZ; plan #X2Wd; plan #DsHq; plan #PaBF; plan #TNrF; plan #DhCf; plan #snUU; plan #RqED; plan #YYF; plan #rV1N

Settings

Optimization path:

Optimization(s) for this plan:

# exclusive inclusive rows x rows loops node
1. 0.161 226.658 ↓ 26.0 26 1

Sort (cost=4,156.56..4,156.56 rows=1 width=220) (actual time=226.649..226.658 rows=26 loops=1)

  • Sort Key: (sum(b.cost)) DESC
  • Sort Method: quicksort Memory: 38kB
2. 0.315 226.497 ↓ 26.0 26 1

Nested Loop Left Join (cost=3,406.27..4,156.55 rows=1 width=220) (actual time=137.075..226.497 rows=26 loops=1)

3. 0.065 226.052 ↓ 26.0 26 1

Nested Loop Left Join (cost=3,405.99..4,156.07 rows=1 width=140) (actual time=137.047..226.052 rows=26 loops=1)

4. 0.196 149.781 ↓ 26.0 26 1

Nested Loop (cost=219.57..230.40 rows=1 width=116) (actual time=107.324..149.781 rows=26 loops=1)

  • Join Filter: (b.imb_id = widgets.imb_id)
  • Rows Removed by Join Filter: 1118
5. 27.681 147.297 ↓ 26.0 26 1

GroupAggregate (cost=2.67..2.69 rows=1 width=20) (actual time=107.075..147.297 rows=26 loops=1)

  • Group Key: widgets.imb_id
6. 43.425 119.616 ↓ 160,496.0 160,496 1

Sort (cost=2.67..2.67 rows=1 width=12) (actual time=104.397..119.616 rows=160,496 loops=1)

  • Sort Key: widgets.imb_id
  • Sort Method: quicksort Memory: 13668kB
7. 76.191 76.191 ↓ 160,496.0 160,496 1

Index Scan using widgets_date_idx on widgets (cost=0.44..2.66 rows=1 width=12) (actual time=0.045..76.191 rows=160,496 loops=1)

  • Index Cond: ((date >= '2019-06-06'::date) AND (date <= '2019-06-11'::date))
  • Filter: (source_id = 30)
  • Rows Removed by Filter: 11319
8. 2.182 2.288 ↑ 3.3 44 26

HashAggregate (cost=216.90..224.46 rows=144 width=100) (actual time=0.014..0.088 rows=44 loops=26)

  • Group Key: b.imb_id
  • Filter: (sum(b.ts_clicks) > 0)
9. 0.106 0.106 ↑ 3.5 44 1

Index Scan using boosts_pkey on campaigns b (cost=0.29..208.71 rows=156 width=36) (actual time=0.054..0.106 rows=44 loops=1)

  • Index Cond: ((date >= '2019-06-06'::date) AND (date <= '2019-06-11'::date))
  • Filter: ((ts_id IS NOT NULL) AND (cost > '0'::double precision))
  • Rows Removed by Filter: 240
10. 0.151 76.206 ↑ 1.0 1 26

Hash Join (cost=3,186.42..3,925.66 rows=1 width=28) (actual time=2.930..2.931 rows=1 loops=26)

  • Hash Cond: ((d1.imb_id = campaigns.imb_id) AND (d1.date = (max(campaigns.date))))
11. 48.854 48.854 ↑ 29.3 3 26

Index Scan using boosts_pkey on campaigns d1 (cost=0.29..718.62 rows=88 width=32) (actual time=1.865..1.879 rows=3 loops=26)

  • Index Cond: (b.imb_id = imb_id)
  • Filter: (bid IS NOT NULL)
  • Rows Removed by Filter: 4
12. 0.237 27.201 ↓ 1.1 978 1

Hash (cost=3,172.18..3,172.18 rows=930 width=8) (actual time=27.201..27.201 rows=978 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 47kB
13. 17.719 26.964 ↓ 1.1 978 1

HashAggregate (cost=3,153.58..3,162.88 rows=930 width=8) (actual time=26.756..26.964 rows=978 loops=1)

  • Group Key: campaigns.imb_id
14. 9.245 9.245 ↑ 1.0 94,344 1

Seq Scan on campaigns (cost=0.00..2,681.72 rows=94,372 width=8) (actual time=0.016..9.245 rows=94,344 loops=1)

15. 0.130 0.130 ↓ 0.0 0 26

Index Scan using campaign_names_pk on campaign_names_groups names (cost=0.28..0.45 rows=1 width=43) (actual time=0.005..0.005 rows=0 loops=26)

  • Index Cond: (imb_id = b.imb_id)
Planning time : 1.244 ms
Execution time : 228.379 ms