explain.depesz.com

PostgreSQL's explain analyze made readable

Result: IMEN : 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

Settings

Optimization path:

Optimization(s) for this plan:

# exclusive inclusive rows x rows loops node
1. 0.030 764.685 ↑ 18.9 26 1

Sort (cost=12,050.22..12,051.45 rows=492 width=220) (actual time=764.682..764.685 rows=26 loops=1)

  • Sort Key: (sum(b.cost)) DESC
  • Sort Method: quicksort Memory: 38kB
2. 0.094 764.655 ↑ 18.9 26 1

Hash Left Join (cost=10,579.45..12,028.22 rows=492 width=220) (actual time=762.298..764.655 rows=26 loops=1)

  • Hash Cond: (b.imb_id = names.imb_id)
3. 0.022 764.115 ↑ 18.9 26 1

Hash Join (cost=10,533.02..11,963.95 rows=492 width=140) (actual time=761.829..764.115 rows=26 loops=1)

  • Hash Cond: (b.imb_id = imb.imb_id)
4. 0.078 26.164 ↑ 3.3 44 1

Hash Right Join (cost=3,383.39..4,796.81 rows=144 width=124) (actual time=23.855..26.164 rows=44 loops=1)

  • Hash Cond: (d1.imb_id = b.imb_id)
5. 0.158 25.881 ↓ 4.5 580 1

Nested Loop (cost=3,155.70..4,568.43 rows=128 width=28) (actual time=23.604..25.881 rows=580 loops=1)

6. 15.329 23.767 ↓ 1.1 978 1

HashAggregate (cost=3,155.41..3,164.71 rows=930 width=8) (actual time=23.590..23.767 rows=978 loops=1)

  • Group Key: campaigns.imb_id
7. 8.438 8.438 ↓ 1.0 94,443 1

Seq Scan on campaigns (cost=0.00..2,683.27 rows=94,427 width=8) (actual time=0.014..8.438 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 0.205 ↑ 3.3 44 1

Hash (cost=225.90..225.90 rows=144 width=100) (actual time=0.205..0.205 rows=44 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 14kB
10. 0.088 0.193 ↑ 3.3 44 1

HashAggregate (cost=216.90..224.46 rows=144 width=100) (actual time=0.167..0.193 rows=44 loops=1)

  • Group Key: b.imb_id
  • Filter: (sum(b.ts_clicks) > 0)
11. 0.105 0.105 ↓ 1.0 157 1

Index Scan using boosts_pkey on campaigns b (cost=0.29..208.71 rows=156 width=36) (actual time=0.040..0.105 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. 0.013 737.929 ↑ 26.3 26 1

Hash (cost=7,141.09..7,141.09 rows=683 width=20) (actual time=737.929..737.929 rows=26 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 10kB
13. 0.002 737.916 ↑ 26.3 26 1

Subquery Scan on imb (cost=7,127.43..7,141.09 rows=683 width=20) (actual time=737.910..737.916 rows=26 loops=1)

14. 338.927 737.914 ↑ 26.3 26 1

HashAggregate (cost=7,127.43..7,134.26 rows=683 width=20) (actual time=737.909..737.914 rows=26 loops=1)

  • Group Key: widgets.imb_id
15. 398.987 398.987 ↓ 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=0.026..398.987 rows=1,383,231 loops=1)

  • Index Cond: ((date >= '2019-06-06'::date) AND (date <= '2019-06-11'::date) AND (source_id = 30))
16. 0.232 0.446 ↑ 1.0 1,486 1

Hash (cost=27.86..27.86 rows=1,486 width=43) (actual time=0.446..0.446 rows=1,486 loops=1)

  • Buckets: 2048 Batches: 1 Memory Usage: 114kB
17. 0.214 0.214 ↑ 1.0 1,486 1

Seq Scan on campaign_names_groups names (cost=0.00..27.86 rows=1,486 width=43) (actual time=0.020..0.214 rows=1,486 loops=1)

Planning time : 4.908 ms
Execution time : 764.958 ms