explain.depesz.com

PostgreSQL's explain analyze made readable

Result: lcKC : 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: 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; plan #WFzh; plan #w8W

Settings

Optimization path:

# exclusive inclusive rows x rows loops node
1. 0.059 174.409 ↓ 15.0 15 1

Sort (cost=4,156.56..4,156.56 rows=1 width=220) (actual time=174.403..174.409 rows=15 loops=1)

  • Sort Key: (sum(b.cost)) DESC
  • Sort Method: quicksort Memory: 32kB
2. 0.172 174.350 ↓ 15.0 15 1

Nested Loop Left Join (cost=3,406.27..4,156.55 rows=1 width=220) (actual time=145.174..174.350 rows=15 loops=1)

3. 0.025 174.118 ↓ 15.0 15 1

Nested Loop Left Join (cost=3,405.99..4,156.07 rows=1 width=140) (actual time=145.152..174.118 rows=15 loops=1)

4. 0.102 109.203 ↓ 15.0 15 1

Nested Loop (cost=219.57..230.40 rows=1 width=116) (actual time=106.129..109.203 rows=15 loops=1)

  • Join Filter: (b.imb_id = widgets.imb_id)
  • Rows Removed by Join Filter: 953
5. 2.135 107.539 ↓ 22.0 22 1

GroupAggregate (cost=2.67..2.69 rows=1 width=20) (actual time=104.266..107.539 rows=22 loops=1)

  • Group Key: widgets.imb_id
6. 3.946 105.404 ↓ 11,206.0 11,206 1

Sort (cost=2.67..2.67 rows=1 width=12) (actual time=104.258..105.404 rows=11,206 loops=1)

  • Sort Key: widgets.imb_id
  • Sort Method: quicksort Memory: 910kB
7. 101.458 101.458 ↓ 11,206.0 11,206 1

Index Scan using widgets_date_idx on widgets (cost=0.44..2.66 rows=1 width=12) (actual time=69.844..101.458 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: 278082
8. 1.414 1.562 ↑ 3.3 44 22

HashAggregate (cost=216.90..224.46 rows=144 width=100) (actual time=0.012..0.071 rows=44 loops=22)

  • Group Key: b.imb_id
  • Filter: (sum(b.ts_clicks) > 0)
9. 0.148 0.148 ↑ 3.5 44 1

Index Scan using boosts_pkey on campaigns b (cost=0.29..208.71 rows=156 width=36) (actual time=0.073..0.148 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. 0.201 64.890 ↑ 1.0 1 15

Hash Join (cost=3,186.42..3,925.66 rows=1 width=28) (actual time=4.324..4.326 rows=1 loops=15)

  • Hash Cond: ((d1.imb_id = campaigns.imb_id) AND (d1.date = (max(campaigns.date))))
11. 28.050 28.050 ↑ 2.4 37 15

Index Scan using boosts_pkey on campaigns d1 (cost=0.29..718.62 rows=88 width=32) (actual time=1.666..1.870 rows=37 loops=15)

  • Index Cond: (b.imb_id = imb_id)
  • Filter: (bid IS NOT NULL)
  • Rows Removed by Filter: 7
12. 0.223 36.639 ↓ 1.1 978 1

Hash (cost=3,172.18..3,172.18 rows=930 width=8) (actual time=36.639..36.639 rows=978 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 47kB
13. 24.994 36.416 ↓ 1.1 978 1

HashAggregate (cost=3,153.58..3,162.88 rows=930 width=8) (actual time=36.215..36.416 rows=978 loops=1)

  • Group Key: campaigns.imb_id
14. 11.422 11.422 ↑ 1.0 94,344 1

Seq Scan on campaigns (cost=0.00..2,681.72 rows=94,372 width=8) (actual time=0.025..11.422 rows=94,344 loops=1)

15. 0.060 0.060 ↑ 1.0 1 15

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=1 loops=15)

  • Index Cond: (imb_id = b.imb_id)
Planning time : 1.686 ms
Execution time : 175.151 ms