explain.depesz.com

PostgreSQL's explain analyze made readable

Result: NX5 : Optimization for: Optimization for: Optimization for: Optimization for: Optimization for: plan #LaHU; plan #IaEQ; plan #ewLA; plan #ZqOR; plan #SdSy

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Optimization path:

Optimization(s) for this plan:

# exclusive inclusive rows x rows loops node
1. 0.029 734.216 ↑ 32.8 15 1

Sort (cost=45,315.91..45,317.14 rows=492 width=220) (actual time=734.214..734.216 rows=15 loops=1)

  • Sort Key: (sum(b.cost)) DESC
  • Sort Method: quicksort Memory: 32kB
2. 0.106 734.187 ↑ 32.8 15 1

Hash Left Join (cost=43,845.15..45,293.92 rows=492 width=220) (actual time=731.383..734.187 rows=15 loops=1)

  • Hash Cond: (b.imb_id = names.imb_id)
3. 0.023 732.378 ↑ 32.8 15 1

Hash Join (cost=43,798.71..45,229.65 rows=492 width=140) (actual time=729.636..732.378 rows=15 loops=1)

  • Hash Cond: (b.imb_id = imb.imb_id)
4. 0.084 29.752 ↑ 3.3 44 1

Hash Right Join (cost=3,383.39..4,796.81 rows=144 width=124) (actual time=27.023..29.752 rows=44 loops=1)

  • Hash Cond: (d1.imb_id = b.imb_id)
5. 0.539 29.421 ↓ 4.5 580 1

Nested Loop (cost=3,155.70..4,568.43 rows=128 width=28) (actual time=26.735..29.421 rows=580 loops=1)

6. 15.895 26.926 ↓ 1.1 978 1

HashAggregate (cost=3,155.41..3,164.71 rows=930 width=8) (actual time=26.722..26.926 rows=978 loops=1)

  • Group Key: campaigns.imb_id
7. 11.031 11.031 ↓ 1.0 94,443 1

Seq Scan on campaigns (cost=0.00..2,683.27 rows=94,427 width=8) (actual time=0.014..11.031 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 0.247 ↑ 3.3 44 1

Hash (cost=225.90..225.90 rows=144 width=100) (actual time=0.247..0.247 rows=44 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 14kB
10. 0.102 0.235 ↑ 3.3 44 1

HashAggregate (cost=216.90..224.46 rows=144 width=100) (actual time=0.209..0.235 rows=44 loops=1)

  • Group Key: b.imb_id
  • Filter: (sum(b.ts_clicks) > 0)
11. 0.133 0.133 ↓ 1.0 157 1

Index Scan using boosts_pkey on campaigns b (cost=0.29..208.71 rows=156 width=36) (actual time=0.058..0.133 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. 0.011 702.603 ↑ 31.1 22 1

Hash (cost=40,406.77..40,406.77 rows=684 width=20) (actual time=702.603..702.603 rows=22 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 10kB
13. 0.006 702.592 ↑ 31.1 22 1

Subquery Scan on imb (cost=40,393.09..40,406.77 rows=684 width=20) (actual time=702.586..702.592 rows=22 loops=1)

14. 2.155 702.586 ↑ 31.1 22 1

HashAggregate (cost=40,393.09..40,399.93 rows=684 width=20) (actual time=702.582..702.586 rows=22 loops=1)

  • Group Key: widgets.imb_id
15. 700.431 700.431 ↑ 21.6 11,206 1

Index Scan using widgets_date_idx on widgets (cost=0.44..38,580.70 rows=241,652 width=12) (actual time=74.975..700.431 rows=11,206 loops=1)

  • Index Cond: ((date >= '2019-06-06'::date) AND (date <= '2019-06-11'::date))
  • Filter: (source_id = 12)
  • Rows Removed by Filter: 1383344
16. 0.356 1.703 ↑ 1.0 1,486 1

Hash (cost=27.86..27.86 rows=1,486 width=43) (actual time=1.703..1.703 rows=1,486 loops=1)

  • Buckets: 2048 Batches: 1 Memory Usage: 114kB
17. 1.347 1.347 ↑ 1.0 1,486 1

Seq Scan on campaign_names_groups names (cost=0.00..27.86 rows=1,486 width=43) (actual time=0.381..1.347 rows=1,486 loops=1)

Planning time : 5.851 ms
Execution time : 734.817 ms