explain.depesz.com

PostgreSQL's explain analyze made readable

Result: TCKp : 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: 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; plan #jPAj

Settings

Optimization path:

# exclusive inclusive rows x rows loops node
1. 0.070 238.527 ↓ 26.0 26 1

Sort (cost=4,156.56..4,156.56 rows=1 width=220) (actual time=238.520..238.527 rows=26 loops=1)

  • Sort Key: (sum(b.cost)) DESC
  • Sort Method: quicksort Memory: 38kB
2. 0.234 238.457 ↓ 26.0 26 1

Nested Loop Left Join (cost=3,406.27..4,156.55 rows=1 width=220) (actual time=157.936..238.457 rows=26 loops=1)

3. 0.048 238.119 ↓ 26.0 26 1

Nested Loop Left Join (cost=3,405.99..4,156.07 rows=1 width=140) (actual time=157.920..238.119 rows=26 loops=1)

4. 0.129 175.905 ↓ 26.0 26 1

Nested Loop (cost=219.57..230.40 rows=1 width=116) (actual time=134.107..175.905 rows=26 loops=1)

  • Join Filter: (b.imb_id = widgets.imb_id)
  • Rows Removed by Join Filter: 1118
5. 25.930 174.190 ↓ 26.0 26 1

GroupAggregate (cost=2.67..2.69 rows=1 width=20) (actual time=133.948..174.190 rows=26 loops=1)

  • Group Key: widgets.imb_id
6. 54.973 148.260 ↓ 230,242.0 230,242 1

Sort (cost=2.67..2.67 rows=1 width=12) (actual time=131.745..148.260 rows=230,242 loops=1)

  • Sort Key: widgets.imb_id
  • Sort Method: quicksort Memory: 16937kB
7. 93.287 93.287 ↓ 230,242.0 230,242 1

Index Scan using widgets_date_idx on widgets (cost=0.44..2.66 rows=1 width=12) (actual time=0.034..93.287 rows=230,242 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. 1.494 1.586 ↑ 3.3 44 26

HashAggregate (cost=216.90..224.46 rows=144 width=100) (actual time=0.011..0.061 rows=44 loops=26)

  • Group Key: b.imb_id
  • Filter: (sum(b.ts_clicks) > 0)
9. 0.092 0.092 ↑ 3.5 44 1

Index Scan using boosts_pkey on campaigns b (cost=0.29..208.71 rows=156 width=36) (actual time=0.056..0.092 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. 0.096 62.166 ↑ 1.0 1 26

Hash Join (cost=3,186.42..3,925.66 rows=1 width=28) (actual time=2.391..2.391 rows=1 loops=26)

  • Hash Cond: ((d1.imb_id = campaigns.imb_id) AND (d1.date = (max(campaigns.date))))
11. 39.702 39.702 ↑ 29.3 3 26

Index Scan using boosts_pkey on campaigns d1 (cost=0.29..718.62 rows=88 width=32) (actual time=1.516..1.527 rows=3 loops=26)

  • Index Cond: (b.imb_id = imb_id)
  • Filter: (bid IS NOT NULL)
  • Rows Removed by Filter: 4
12. 0.133 22.368 ↓ 1.1 978 1

Hash (cost=3,172.18..3,172.18 rows=930 width=8) (actual time=22.368..22.368 rows=978 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 47kB
13. 15.271 22.235 ↓ 1.1 978 1

HashAggregate (cost=3,153.58..3,162.88 rows=930 width=8) (actual time=22.131..22.235 rows=978 loops=1)

  • Group Key: campaigns.imb_id
14. 6.964 6.964 ↑ 1.0 94,344 1

Seq Scan on campaigns (cost=0.00..2,681.72 rows=94,372 width=8) (actual time=0.014..6.964 rows=94,344 loops=1)

15. 0.104 0.104 ↓ 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=0.004..0.004 rows=0 loops=26)

  • Index Cond: (imb_id = b.imb_id)
Planning time : 1.239 ms
Execution time : 240.912 ms