explain.depesz.com

PostgreSQL's explain analyze made readable

Result: QDCV

Settings
# exclusive inclusive rows x rows loops node
1. 28.148 2,506.925 ↑ 1.5 76,234 1

Group (cost=327,930.15..330,817.05 rows=115,476 width=199) (actual time=2,462.266..2,506.925 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. 87.941 2,478.777 ↑ 1.1 104,878 1

Sort (cost=327,930.15..328,218.84 rows=115,476 width=199) (actual time=2,462.264..2,478.777 rows=104,878 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: 13,720kB
3. 23.862 2,390.836 ↑ 1.1 104,878 1

Hash Left Join (cost=242,241.79..307,167.21 rows=115,476 width=199) (actual time=1,858.785..2,390.836 rows=104,878 loops=1)

  • Hash Cond: (bordereau.id_bordereau = avoir_data.id_bordereau)
4. 20.441 2,361.864 ↑ 1.1 104,817 1

Hash Left Join (cost=241,368.19..305,272.12 rows=115,476 width=203) (actual time=1,853.664..2,361.864 rows=104,817 loops=1)

  • Hash Cond: (bordereau.id_film = films.id_film)
5. 306.689 2,338.394 ↑ 1.1 104,817 1

Hash Right Join (cost=240,621.26..302,938.93 rows=115,476 width=189) (actual time=1,850.622..2,338.394 rows=104,817 loops=1)

  • Hash Cond: (encaissement.id_fact = facture.id_fact)
6. 181.931 181.931 ↑ 1.0 1,744,648 1

Seq Scan on encaissement (cost=0.00..38,011.48 rows=1,744,648 width=4) (actual time=0.015..181.931 rows=1,744,648 loops=1)

7. 39.247 1,849.774 ↑ 1.1 103,852 1

Hash (cost=236,132.81..236,132.81 rows=115,476 width=189) (actual time=1,849.774..1,849.774 rows=103,852 loops=1)

  • Buckets: 32,768 Batches: 8 Memory Usage: 2,119kB
8. 11.688 1,810.527 ↑ 1.1 103,852 1

Nested Loop (cost=77,637.63..236,132.81 rows=115,476 width=189) (actual time=490.406..1,810.527 rows=103,852 loops=1)

9. 0.023 0.023 ↑ 1.0 1 1

Index Only Scan using distributeur_pkey on distributeur (cost=0.27..8.29 rows=1 width=0) (actual time=0.020..0.023 rows=1 loops=1)

  • Index Cond: (id_societe = 42)
  • Heap Fetches: 1
10. 25.956 1,798.816 ↑ 1.1 103,852 1

Hash Left Join (cost=77,637.36..234,969.76 rows=115,476 width=189) (actual time=490.382..1,798.816 rows=103,852 loops=1)

  • Hash Cond: (facture.id_societe = societe.id_societe)
11. 32.124 1,770.565 ↑ 1.1 103,852 1

Hash Left Join (cost=77,218.64..232,967.10 rows=115,476 width=183) (actual time=488.074..1,770.565 rows=103,852 loops=1)

  • Hash Cond: (bordereau.screen_id = salles.screen_id)
12. 504.102 1,728.652 ↑ 1.1 103,852 1

Hash Join (cost=76,064.16..230,265.08 rows=115,476 width=156) (actual time=478.263..1,728.652 rows=103,852 loops=1)

  • Hash Cond: (bordereau.id_fact = facture.id_fact)
13. 746.790 746.790 ↑ 1.0 2,764,877 1

Seq Scan on bordereau (cost=0.00..114,102.77 rows=2,766,977 width=16) (actual time=0.014..746.790 rows=2,764,877 loops=1)

14. 19.488 477.760 ↑ 1.0 76,239 1

Hash (cost=73,513.27..73,513.27 rows=77,271 width=144) (actual time=477.759..477.760 rows=76,239 loops=1)

  • Buckets: 32,768 Batches: 4 Memory Usage: 2,181kB
15. 270.926 458.272 ↑ 1.0 76,239 1

Hash Right Join (cost=27,834.05..73,513.27 rows=77,271 width=144) (actual time=41.597..458.272 rows=76,239 loops=1)

  • Hash Cond: (edition_fact.id_fact = facture.id_fact)
16. 146.481 146.481 ↑ 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=0.012..146.481 rows=1,555,354 loops=1)

17. 11.202 40.865 ↑ 1.0 76,239 1

Hash (cost=25,283.17..25,283.17 rows=77,271 width=140) (actual time=40.865..40.865 rows=76,239 loops=1)

  • Buckets: 32,768 Batches: 4 Memory Usage: 2,116kB
18. 25.108 29.663 ↑ 1.0 76,239 1

Bitmap Heap Scan on facture (cost=1,447.28..25,283.17 rows=77,271 width=140) (actual time=6.164..29.663 rows=76,239 loops=1)

  • Recheck Cond: (id_distri = 42)
  • Heap Blocks: exact=13,266
19. 4.555 4.555 ↑ 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=4.555..4.555 rows=76,239 loops=1)

  • Index Cond: (id_distri = 42)
20. 2.329 9.789 ↑ 1.0 16,876 1

Hash (cost=943.53..943.53 rows=16,876 width=35) (actual time=9.789..9.789 rows=16,876 loops=1)

  • Buckets: 32,768 Batches: 1 Memory Usage: 1,373kB
21. 3.391 7.460 ↑ 1.0 16,876 1

Hash Left Join (cost=393.73..943.53 rows=16,876 width=35) (actual time=3.051..7.460 rows=16,876 loops=1)

  • Hash Cond: (salles.id_cinema = cinema.id_cinema)
22. 1.046 1.046 ↑ 1.0 16,876 1

Seq Scan on salles (cost=0.00..317.76 rows=16,876 width=8) (actual time=0.016..1.046 rows=16,876 loops=1)

23. 1.036 3.023 ↑ 1.0 7,410 1

Hash (cost=301.10..301.10 rows=7,410 width=35) (actual time=3.023..3.023 rows=7,410 loops=1)

  • Buckets: 8,192 Batches: 1 Memory Usage: 577kB
24. 1.987 1.987 ↑ 1.0 7,410 1

Seq Scan on cinema (cost=0.00..301.10 rows=7,410 width=35) (actual time=0.005..1.987 rows=7,410 loops=1)

25. 0.424 2.295 ↑ 1.0 4,804 1

Hash (cost=358.17..358.17 rows=4,844 width=6) (actual time=2.295..2.295 rows=4,804 loops=1)

  • Buckets: 8,192 Batches: 1 Memory Usage: 233kB
26. 0.406 1.871 ↑ 1.0 4,804 1

Hash Right Join (cost=228.99..358.17 rows=4,844 width=6) (actual time=0.989..1.871 rows=4,804 loops=1)

  • Hash Cond: (societe_redressement.id_societe = societe.id_societe)
27. 0.489 0.489 ↑ 1.0 52 1

Seq Scan on societe_redressement (cost=0.00..128.46 rows=52 width=6) (actual time=0.008..0.489 rows=52 loops=1)

  • Filter: (id_distri = 42)
  • Rows Removed by Filter: 7,105
28. 0.406 0.976 ↑ 1.0 4,804 1

Hash (cost=168.44..168.44 rows=4,844 width=4) (actual time=0.976..0.976 rows=4,804 loops=1)

  • Buckets: 8,192 Batches: 1 Memory Usage: 233kB
29. 0.570 0.570 ↑ 1.0 4,804 1

Seq Scan on societe (cost=0.00..168.44 rows=4,844 width=4) (actual time=0.005..0.570 rows=4,804 loops=1)

30. 1.575 3.029 ↑ 1.0 13,197 1

Hash (cost=581.97..581.97 rows=13,197 width=22) (actual time=3.029..3.029 rows=13,197 loops=1)

  • Buckets: 16,384 Batches: 1 Memory Usage: 846kB
31. 1.454 1.454 ↑ 1.0 13,197 1

Seq Scan on films (cost=0.00..581.97 rows=13,197 width=22) (actual time=0.004..1.454 rows=13,197 loops=1)

32. 2.298 5.110 ↑ 1.0 26,560 1

Hash (cost=541.60..541.60 rows=26,560 width=4) (actual time=5.109..5.110 rows=26,560 loops=1)

  • Buckets: 32,768 Batches: 1 Memory Usage: 1,190kB
33. 2.812 2.812 ↑ 1.0 26,560 1

Seq Scan on avoir_data (cost=0.00..541.60 rows=26,560 width=4) (actual time=0.006..2.812 rows=26,560 loops=1)

Planning time : 3.018 ms
Execution time : 2,512.198 ms