explain.depesz.com

PostgreSQL's explain analyze made readable

Result: VGlE : Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: plan #LaHU; plan #IaEQ; plan #ewLA; plan #ZqOR; plan #SdSy; plan #NX5; plan #AAo9; plan #IMEN; plan #VYE1; plan #l3H2

Settings

Optimization path:

Optimization(s) for this plan:

# exclusive inclusive rows x rows loops node
1. 0.025 716.317 ↑ 18.9 26 1

Sort (cost=12,050.22..12,051.45 rows=492 width=220) (actual time=716.315..716.317 rows=26 loops=1)

  • Sort Key: (sum(b.cost)) DESC
  • Sort Method: quicksort Memory: 38kB
2. 0.081 716.292 ↑ 18.9 26 1

Hash Left Join (cost=10,579.45..12,028.22 rows=492 width=220) (actual time=714.172..716.292 rows=26 loops=1)

  • Hash Cond: (b.imb_id = names.imb_id)
3. 0.023 715.861 ↑ 18.9 26 1

Hash Join (cost=10,533.02..11,963.95 rows=492 width=140) (actual time=713.794..715.861 rows=26 loops=1)

  • Hash Cond: (b.imb_id = imb.imb_id)
4. 0.070 29.931 ↑ 3.3 44 1

Hash Right Join (cost=3,383.39..4,796.81 rows=144 width=124) (actual time=27.843..29.931 rows=44 loops=1)

  • Hash Cond: (d1.imb_id = b.imb_id)
5. 0.001 29.658 ↓ 4.5 580 1

Nested Loop (cost=3,155.70..4,568.43 rows=128 width=28) (actual time=27.555..29.658 rows=580 loops=1)

6. 18.762 27.701 ↓ 1.1 978 1

HashAggregate (cost=3,155.41..3,164.71 rows=930 width=8) (actual time=27.543..27.701 rows=978 loops=1)

  • Group Key: campaigns.imb_id
7. 8.939 8.939 ↓ 1.0 94,443 1

Seq Scan on campaigns (cost=0.00..2,683.27 rows=94,427 width=8) (actual time=0.010..8.939 rows=94,443 loops=1)

8. 1.956 1.956 ↑ 1.0 1 978

Index Scan using boosts_pkey on campaigns d1 (cost=0.29..1.49 rows=1 width=32) (actual time=0.002..0.002 rows=1 loops=978)

  • Index Cond: ((date = (max(campaigns.date))) AND (imb_id = campaigns.imb_id))
  • Filter: (bid IS NOT NULL)
  • Rows Removed by Filter: 0
9. 0.012 0.203 ↑ 3.3 44 1

Hash (cost=225.90..225.90 rows=144 width=100) (actual time=0.203..0.203 rows=44 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 14kB
10. 0.092 0.191 ↑ 3.3 44 1

HashAggregate (cost=216.90..224.46 rows=144 width=100) (actual time=0.166..0.191 rows=44 loops=1)

  • Group Key: b.imb_id
  • Filter: (sum(b.ts_clicks) > 0)
11. 0.099 0.099 ↓ 1.0 157 1

Index Scan using boosts_pkey on campaigns b (cost=0.29..208.71 rows=156 width=36) (actual time=0.037..0.099 rows=157 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: 226
12. 0.012 685.907 ↑ 26.3 26 1

Hash (cost=7,141.09..7,141.09 rows=683 width=20) (actual time=685.907..685.907 rows=26 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 10kB
13. 0.002 685.895 ↑ 26.3 26 1

Subquery Scan on imb (cost=7,127.43..7,141.09 rows=683 width=20) (actual time=685.889..685.895 rows=26 loops=1)

14. 317.657 685.893 ↑ 26.3 26 1

HashAggregate (cost=7,127.43..7,134.26 rows=683 width=20) (actual time=685.888..685.893 rows=26 loops=1)

  • Group Key: widgets.imb_id
15. 368.236 368.236 ↓ 300.1 1,383,231 1

Index Scan using widgets_date_source_id_idx on widgets (cost=0.44..7,092.86 rows=4,609 width=12) (actual time=0.019..368.236 rows=1,383,231 loops=1)

  • Index Cond: ((date >= '2019-06-06'::date) AND (date <= '2019-06-11'::date) AND (source_id = 30))
16. 0.197 0.350 ↑ 1.0 1,486 1

Hash (cost=27.86..27.86 rows=1,486 width=43) (actual time=0.350..0.350 rows=1,486 loops=1)

  • Buckets: 2048 Batches: 1 Memory Usage: 114kB
17. 0.153 0.153 ↑ 1.0 1,486 1

Seq Scan on campaign_names_groups names (cost=0.00..27.86 rows=1,486 width=43) (actual time=0.018..0.153 rows=1,486 loops=1)

Planning time : 0.882 ms
Execution time : 716.537 ms