explain.depesz.com

PostgreSQL's explain analyze made readable

Result: zM9j

Settings
# exclusive inclusive rows x rows loops node
1. 2.533 607.707 ↓ 821.0 821 1

Sort (cost=7,507.16..7,507.16 rows=1 width=714) (actual time=607.674..607.707 rows=821 loops=1)

  • Sort Key: t4.open DESC, t4.term_score DESC, t4.merchant_short_id
  • Sort Method: quicksort Memory: 834kB
2. 0.151 605.174 ↓ 821.0 821 1

Subquery Scan on t4 (cost=7,506.92..7,507.15 rows=1 width=714) (actual time=604.478..605.174 rows=821 loops=1)

  • Filter: (t4.catalog_items_rn <= 100)
  • Rows Removed by Filter: 36
3. 0.506 605.023 ↓ 857.0 857 1

WindowAgg (cost=7,506.92..7,507.04 rows=1 width=758) (actual time=604.476..605.023 rows=857 loops=1)

4. 0.923 604.517 ↓ 857.0 857 1

Sort (cost=7,506.92..7,506.93 rows=1 width=616) (actual time=604.471..604.517 rows=857 loops=1)

  • Sort Key: t2.merchant_id, (NULLIF((ts_rank_cd(catalog_item.fts, q.tsquery))::double precision, '0'::double precision))
  • Sort Method: quicksort Memory: 851kB
5. 1.345 603.594 ↓ 857.0 857 1

Nested Loop (cost=1,094.16..7,506.91 rows=1 width=616) (actual time=129.155..603.594 rows=857 loops=1)

6. 0.003 0.003 ↑ 1.0 1 1

Function Scan on q (cost=0.00..0.10 rows=1 width=32) (actual time=0.003..0.003 rows=1 loops=1)

7. 0.705 602.246 ↓ 122.4 857 1

Nested Loop (cost=1,094.16..7,506.11 rows=7 width=737) (actual time=129.139..602.246 rows=857 loops=1)

8. 0.086 118.193 ↓ 15.7 282 1

Subquery Scan on t2 (cost=720.16..732.98 rows=18 width=445) (actual time=117.108..118.193 rows=282 loops=1)

  • Filter: (t2.group_rn <= 1)
  • Rows Removed by Filter: 6
9. 0.908 118.107 ↓ 5.3 288 1

WindowAgg (cost=720.16..727.45 rows=54 width=502) (actual time=117.107..118.107 rows=288 loops=1)

10. 0.646 117.199 ↓ 5.3 288 1

Sort (cost=720.16..720.29 rows=54 width=429) (actual time=117.097..117.199 rows=288 loops=1)

  • Sort Key: merc.group_id, (COALESCE((true), false)) DESC, d.distance, t.delivery_fee, (((merc.evaluations #>> '{IFOOD,avg}'::text[]))::real) DESC, merc.merchant_short_id
  • Sort Method: quicksort Memory: 225kB
11. 0.438 116.553 ↓ 5.3 288 1

Nested Loop (cost=119.49..718.60 rows=54 width=429) (actual time=109.207..116.553 rows=288 loops=1)

12. 0.376 114.675 ↓ 5.3 288 1

Nested Loop Left Join (cost=119.23..707.14 rows=54 width=602) (actual time=108.980..114.675 rows=288 loops=1)

  • Filter: COALESCE((true), false)
  • Rows Removed by Filter: 320
13. 0.418 111.867 ↓ 5.6 608 1

Nested Loop (cost=118.79..606.79 rows=108 width=601) (actual time=108.939..111.867 rows=608 loops=1)

14. 0.103 109.298 ↓ 6.6 717 1

Subquery Scan on t (cost=118.38..130.09 rows=108 width=30) (actual time=108.916..109.298 rows=717 loops=1)

  • Filter: (t.mode <> 'EXCLUSION'::delivery_mode)
  • Rows Removed by Filter: 19
15. 0.152 109.195 ↓ 6.8 736 1

Unique (cost=118.38..118.92 rows=109 width=46) (actual time=108.914..109.195 rows=736 loops=1)

16. 0.429 109.043 ↓ 6.8 746 1

Sort (cost=118.38..118.65 rows=109 width=46) (actual time=108.913..109.043 rows=746 loops=1)

  • Sort Key: dels.owner_id, ((dels.mode <> 'EXCLUSION'::delivery_mode)), dels.zipcode COLLATE "C", dels.priority
  • Sort Method: quicksort Memory: 83kB
17. 0.380 108.614 ↓ 6.8 746 1

Nested Loop (cost=0.98..114.69 rows=109 width=46) (actual time=0.197..108.614 rows=746 loops=1)

18. 105.598 105.598 ↓ 659.0 659 1

Index Scan using polygons_geom_idx on polygons pol (cost=0.55..4.90 rows=1 width=16) (actual time=0.187..105.598 rows=659 loops=1)

  • Index Cond: (geom && '0101000020E61000008EDF2582828647C06D945055FCDA36C0'::geometry)
  • Filter: _st_intersects(geom, '0101000020E61000008EDF2582828647C06D945055FCDA36C0'::geometry)
  • Rows Removed by Filter: 226
19. 2.636 2.636 ↑ 110.0 1 659

Index Scan using deliveries_pol_id_idx on deliveries dels (cost=0.43..98.51 rows=110 width=61) (actual time=0.004..0.004 rows=1 loops=659)

  • Index Cond: (pol_id = pol.pol_id)
20. 2.151 2.151 ↑ 1.0 1 717

Index Scan using merchants_pkey on merchants merc (cost=0.42..4.41 rows=1 width=587) (actual time=0.003..0.003 rows=1 loops=717)

  • Index Cond: (merchant_id = t.owner_id)
21. 2.432 2.432 ↓ 0.0 0 608

Index Only Scan using merchant_shifts_pkey on merchant_shifts shift (cost=0.43..0.83 rows=1 width=31) (actual time=0.004..0.004 rows=0 loops=608)

  • Index Cond: ((merchant_short_id = merc.merchant_short_id) AND (dow = (date_part('dow'::text, timezone((merc.timezone)::text, now())))::integer))
  • Filter: (shift_range @> timerange((timezone((merc.timezone)::text, now()))::time without time zone, (timezone((merc.timezone)::text, now()))::time without time zone, '[]'::text))
  • Rows Removed by Filter: 0
  • Heap Fetches: 330
22. 1.440 1.440 ↑ 1.0 1 288

Function Scan on round d (cost=0.26..0.36 rows=1 width=32) (actual time=0.005..0.005 rows=1 loops=288)

23. 2.256 483.348 ↓ 3.0 3 282

Bitmap Heap Scan on catalog_items catalog_item (cost=374.00..376.18 rows=1 width=724) (actual time=1.709..1.714 rows=3 loops=282)

  • Recheck Cond: ((merchant_short_id = t2.merchant_short_id) AND (fts @@@ q.tsquery))
  • Filter: (((range_of_times IS NULL) OR ((timezone((t2.timezone)::text, to_timestamp((trunc((date_part('epoch'::text, now()) / '900'::double precision)) * '900'::double precision))))::time without time zone = ANY (range_of_times))) AND (date_part('dow'::text, now()) = ANY ((COALESCE(days, '{0,1,2,3,4,5,6}'::integer[]))::double precision[])))
  • Rows Removed by Filter: 0
  • Heap Blocks: exact=637
24. 481.092 481.092 ↓ 3.0 3 282

Bitmap Index Scan on catalog_items_merchant_short_id_fts_idx (cost=0.00..374.00 rows=1 width=0) (actual time=1.706..1.706 rows=3 loops=282)

  • Index Cond: ((merchant_short_id = t2.merchant_short_id) AND (fts @@@ q.tsquery))