explain.depesz.com

PostgreSQL's explain analyze made readable

Result: 24iQ

Settings
# exclusive inclusive rows x rows loops node
1. 27.661 2,158.673 ↑ 1.5 76,234 1

Group (cost=311,033.34..313,920.24 rows=115,476 width=199) (actual time=2,113.762..2,158.673 rows=76,234 loops=1)

  • Group Key: facture.id_fact, edition_fact.mode_envoi, films.nom_film, societe_redressement.redressement, societe_redressement.liquidation, societe.id_societe, cinema.liv_ville, cinema.liv_dep, cinema.nom_cinema
2. 87.194 2,131.012 ↑ 1.1 103,913 1

Sort (cost=311,033.34..311,322.03 rows=115,476 width=199) (actual time=2,113.757..2,131.012 rows=103,913 loops=1)

  • Sort Key: facture.id_fact, edition_fact.mode_envoi, films.nom_film, societe_redressement.redressement, societe_redressement.liquidation, societe.id_societe, cinema.liv_ville, cinema.liv_dep, cinema.nom_cinema
  • Sort Method: external merge Disk: 13,584kB
3. 19.686 2,043.818 ↑ 1.1 103,913 1

Hash Left Join (cost=242,241.79..290,270.40 rows=115,476 width=199) (actual time=1,972.435..2,043.818 rows=103,913 loops=1)

  • Hash Cond: (bordereau.id_bordereau = avoir_data.id_bordereau)
4. 20.051 2,018.498 ↑ 1.1 103,852 1

Hash Left Join (cost=241,368.19..288,375.31 rows=115,476 width=203) (actual time=1,966.787..2,018.498 rows=103,852 loops=1)

  • Hash Cond: (bordereau.id_film = films.id_film)
5. 31.754 1,994.927 ↑ 1.1 103,852 1

Hash Right Join (cost=240,621.26..286,042.12 rows=115,476 width=189) (actual time=1,963.224..1,994.927 rows=103,852 loops=1)

  • Hash Cond: (encaissement.id_fact = facture.id_fact)
6. 118.529 118.529 ↑ 3.0 58 1

Seq Scan on encaissement (cost=0.00..42,373.10 rows=174 width=4) (actual time=7.124..118.529 rows=58 loops=1)

  • Filter: (id_distri = 42)
  • Rows Removed by Filter: 1,744,590
7. 39.066 1,844.644 ↑ 1.1 103,852 1

Hash (cost=236,132.81..236,132.81 rows=115,476 width=189) (actual time=1,844.644..1,844.644 rows=103,852 loops=1)

  • Buckets: 32,768 Batches: 8 Memory Usage: 2,119kB
8. 11.947 1,805.578 ↑ 1.1 103,852 1

Nested Loop (cost=77,637.63..236,132.81 rows=115,476 width=189) (actual time=482.846..1,805.578 rows=103,852 loops=1)

9. 0.016 0.016 ↑ 1.0 1 1

Index Only Scan using distributeur_pkey on distributeur (cost=0.27..8.29 rows=1 width=0) (actual time=0.013..0.016 rows=1 loops=1)

  • Index Cond: (id_societe = 42)
  • Heap Fetches: 1
10. 26.207 1,793.615 ↑ 1.1 103,852 1

Hash Left Join (cost=77,637.36..234,969.76 rows=115,476 width=189) (actual time=482.832..1,793.615 rows=103,852 loops=1)

  • Hash Cond: (facture.id_societe = societe.id_societe)
11. 33.343 1,765.240 ↑ 1.1 103,852 1

Hash Left Join (cost=77,218.64..232,967.10 rows=115,476 width=183) (actual time=480.655..1,765.240 rows=103,852 loops=1)

  • Hash Cond: (bordereau.screen_id = salles.screen_id)
12. 507.941 1,722.024 ↑ 1.1 103,852 1

Hash Join (cost=76,064.16..230,265.08 rows=115,476 width=156) (actual time=470.765..1,722.024 rows=103,852 loops=1)

  • Hash Cond: (bordereau.id_fact = facture.id_fact)
13. 743.839 743.839 ↑ 1.0 2,764,877 1

Seq Scan on bordereau (cost=0.00..114,102.77 rows=2,766,977 width=16) (actual time=0.071..743.839 rows=2,764,877 loops=1)

14. 19.034 470.244 ↑ 1.0 76,239 1

Hash (cost=73,513.27..73,513.27 rows=77,271 width=144) (actual time=470.244..470.244 rows=76,239 loops=1)

  • Buckets: 32,768 Batches: 4 Memory Usage: 2,181kB
15. 268.479 451.210 ↑ 1.0 76,239 1

Hash Right Join (cost=27,834.05..73,513.27 rows=77,271 width=144) (actual time=37.395..451.210 rows=76,239 loops=1)

  • Hash Cond: (edition_fact.id_fact = facture.id_fact)
16. 146.046 146.046 ↑ 1.0 1,555,354 1

Seq Scan on edition_fact (cost=0.00..25,460.54 rows=1,555,354 width=8) (actual time=0.014..146.046 rows=1,555,354 loops=1)

17. 11.272 36.685 ↑ 1.0 76,239 1

Hash (cost=25,283.17..25,283.17 rows=77,271 width=140) (actual time=36.685..36.685 rows=76,239 loops=1)

  • Buckets: 32,768 Batches: 4 Memory Usage: 2,116kB
18. 20.890 25.413 ↑ 1.0 76,239 1

Bitmap Heap Scan on facture (cost=1,447.28..25,283.17 rows=77,271 width=140) (actual time=6.128..25.413 rows=76,239 loops=1)

  • Recheck Cond: (id_distri = 42)
  • Heap Blocks: exact=13,266
19. 4.523 4.523 ↑ 1.0 76,239 1

Bitmap Index Scan on idx_facture_id_distri (cost=0.00..1,427.96 rows=77,271 width=0) (actual time=4.523..4.523 rows=76,239 loops=1)

  • Index Cond: (id_distri = 42)
20. 2.387 9.873 ↑ 1.0 16,876 1

Hash (cost=943.53..943.53 rows=16,876 width=35) (actual time=9.873..9.873 rows=16,876 loops=1)

  • Buckets: 32,768 Batches: 1 Memory Usage: 1,373kB
21. 3.655 7.486 ↑ 1.0 16,876 1

Hash Left Join (cost=393.73..943.53 rows=16,876 width=35) (actual time=2.761..7.486 rows=16,876 loops=1)

  • Hash Cond: (salles.id_cinema = cinema.id_cinema)
22. 1.085 1.085 ↑ 1.0 16,876 1

Seq Scan on salles (cost=0.00..317.76 rows=16,876 width=8) (actual time=0.009..1.085 rows=16,876 loops=1)

23. 1.003 2.746 ↑ 1.0 7,410 1

Hash (cost=301.10..301.10 rows=7,410 width=35) (actual time=2.746..2.746 rows=7,410 loops=1)

  • Buckets: 8,192 Batches: 1 Memory Usage: 577kB
24. 1.743 1.743 ↑ 1.0 7,410 1

Seq Scan on cinema (cost=0.00..301.10 rows=7,410 width=35) (actual time=0.005..1.743 rows=7,410 loops=1)

25. 0.411 2.168 ↑ 1.0 4,804 1

Hash (cost=358.17..358.17 rows=4,844 width=6) (actual time=2.168..2.168 rows=4,804 loops=1)

  • Buckets: 8,192 Batches: 1 Memory Usage: 233kB
26. 0.367 1.757 ↑ 1.0 4,804 1

Hash Right Join (cost=228.99..358.17 rows=4,844 width=6) (actual time=0.909..1.757 rows=4,804 loops=1)

  • Hash Cond: (societe_redressement.id_societe = societe.id_societe)
27. 0.493 0.493 ↑ 1.0 52 1

Seq Scan on societe_redressement (cost=0.00..128.46 rows=52 width=6) (actual time=0.008..0.493 rows=52 loops=1)

  • Filter: (id_distri = 42)
  • Rows Removed by Filter: 7,105
28. 0.394 0.897 ↑ 1.0 4,804 1

Hash (cost=168.44..168.44 rows=4,844 width=4) (actual time=0.897..0.897 rows=4,804 loops=1)

  • Buckets: 8,192 Batches: 1 Memory Usage: 233kB
29. 0.503 0.503 ↑ 1.0 4,804 1

Seq Scan on societe (cost=0.00..168.44 rows=4,844 width=4) (actual time=0.005..0.503 rows=4,804 loops=1)

30. 1.609 3.520 ↑ 1.0 13,197 1

Hash (cost=581.97..581.97 rows=13,197 width=22) (actual time=3.520..3.520 rows=13,197 loops=1)

  • Buckets: 16,384 Batches: 1 Memory Usage: 846kB
31. 1.911 1.911 ↑ 1.0 13,197 1

Seq Scan on films (cost=0.00..581.97 rows=13,197 width=22) (actual time=0.010..1.911 rows=13,197 loops=1)

32. 2.510 5.634 ↑ 1.0 26,560 1

Hash (cost=541.60..541.60 rows=26,560 width=4) (actual time=5.634..5.634 rows=26,560 loops=1)

  • Buckets: 32,768 Batches: 1 Memory Usage: 1,190kB
33. 3.124 3.124 ↑ 1.0 26,560 1

Seq Scan on avoir_data (cost=0.00..541.60 rows=26,560 width=4) (actual time=0.008..3.124 rows=26,560 loops=1)

Planning time : 2.023 ms
Execution time : 2,164.159 ms