explain.depesz.com

PostgreSQL's explain analyze made readable

Result: YGyW

Settings
# exclusive inclusive rows x rows loops node
1. 28.347 2,181.853 ↑ 1.5 76,234 1

Group (cost=311,033.34..313,920.24 rows=115,476 width=199) (actual time=2,135.503..2,181.853 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. 88.477 2,153.506 ↑ 1.1 103,913 1

Sort (cost=311,033.34..311,322.03 rows=115,476 width=199) (actual time=2,135.501..2,153.506 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. 20.469 2,065.029 ↑ 1.1 103,913 1

Hash Left Join (cost=242,241.79..290,270.40 rows=115,476 width=199) (actual time=1,992.089..2,065.029 rows=103,913 loops=1)

  • Hash Cond: (bordereau.id_bordereau = avoir_data.id_bordereau)
4. 20.413 2,039.394 ↑ 1.1 103,852 1

Hash Left Join (cost=241,368.19..288,375.31 rows=115,476 width=203) (actual time=1,986.909..2,039.394 rows=103,852 loops=1)

  • Hash Cond: (bordereau.id_film = films.id_film)
5. 32.158 2,015.980 ↑ 1.1 103,852 1

Hash Right Join (cost=240,621.26..286,042.12 rows=115,476 width=189) (actual time=1,983.891..2,015.980 rows=103,852 loops=1)

  • Hash Cond: (encaissement.id_fact = facture.id_fact)
6. 118.643 118.643 ↑ 3.0 58 1

Seq Scan on encaissement (cost=0.00..42,373.10 rows=174 width=4) (actual time=6.844..118.643 rows=58 loops=1)

  • Filter: (id_distri = 42)
  • Rows Removed by Filter: 1,744,590
7. 39.143 1,865.179 ↑ 1.1 103,852 1

Hash (cost=236,132.81..236,132.81 rows=115,476 width=189) (actual time=1,865.179..1,865.179 rows=103,852 loops=1)

  • Buckets: 32,768 Batches: 8 Memory Usage: 2,119kB
8. 12.497 1,826.036 ↑ 1.1 103,852 1

Nested Loop (cost=77,637.63..236,132.81 rows=115,476 width=189) (actual time=507.264..1,826.036 rows=103,852 loops=1)

9. 0.015 0.015 ↑ 1.0 1 1

Index Only Scan using distributeur_pkey on distributeur (cost=0.27..8.29 rows=1 width=0) (actual time=0.012..0.015 rows=1 loops=1)

  • Index Cond: (id_societe = 42)
  • Heap Fetches: 1
10. 25.679 1,813.524 ↑ 1.1 103,852 1

Hash Left Join (cost=77,637.36..234,969.76 rows=115,476 width=189) (actual time=507.248..1,813.524 rows=103,852 loops=1)

  • Hash Cond: (facture.id_societe = societe.id_societe)
11. 32.861 1,785.704 ↑ 1.1 103,852 1

Hash Left Join (cost=77,218.64..232,967.10 rows=115,476 width=183) (actual time=505.102..1,785.704 rows=103,852 loops=1)

  • Hash Cond: (bordereau.screen_id = salles.screen_id)
12. 504.372 1,743.523 ↑ 1.1 103,852 1

Hash Join (cost=76,064.16..230,265.08 rows=115,476 width=156) (actual time=495.765..1,743.523 rows=103,852 loops=1)

  • Hash Cond: (bordereau.id_fact = facture.id_fact)
13. 743.741 743.741 ↑ 1.0 2,764,877 1

Seq Scan on bordereau (cost=0.00..114,102.77 rows=2,766,977 width=16) (actual time=0.057..743.741 rows=2,764,877 loops=1)

14. 18.521 495.410 ↑ 1.0 76,239 1

Hash (cost=73,513.27..73,513.27 rows=77,271 width=144) (actual time=495.410..495.410 rows=76,239 loops=1)

  • Buckets: 32,768 Batches: 4 Memory Usage: 2,181kB
15. 273.059 476.889 ↑ 1.0 76,239 1

Hash Right Join (cost=27,834.05..73,513.27 rows=77,271 width=144) (actual time=58.277..476.889 rows=76,239 loops=1)

  • Hash Cond: (edition_fact.id_fact = facture.id_fact)
16. 146.085 146.085 ↑ 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=0.008..146.085 rows=1,555,354 loops=1)

17. 13.750 57.745 ↑ 1.0 76,239 1

Hash (cost=25,283.17..25,283.17 rows=77,271 width=140) (actual time=57.745..57.745 rows=76,239 loops=1)

  • Buckets: 32,768 Batches: 4 Memory Usage: 2,116kB
18. 27.174 43.995 ↑ 1.0 76,239 1

Bitmap Heap Scan on facture (cost=1,447.28..25,283.17 rows=77,271 width=140) (actual time=21.227..43.995 rows=76,239 loops=1)

  • Recheck Cond: (id_distri = 42)
  • Heap Blocks: exact=13,266
19. 16.821 16.821 ↑ 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=16.821..16.821 rows=76,239 loops=1)

  • Index Cond: (id_distri = 42)
20. 2.237 9.320 ↑ 1.0 16,876 1

Hash (cost=943.53..943.53 rows=16,876 width=35) (actual time=9.320..9.320 rows=16,876 loops=1)

  • Buckets: 32,768 Batches: 1 Memory Usage: 1,373kB
21. 3.336 7.083 ↑ 1.0 16,876 1

Hash Left Join (cost=393.73..943.53 rows=16,876 width=35) (actual time=2.754..7.083 rows=16,876 loops=1)

  • Hash Cond: (salles.id_cinema = cinema.id_cinema)
22. 1.006 1.006 ↑ 1.0 16,876 1

Seq Scan on salles (cost=0.00..317.76 rows=16,876 width=8) (actual time=0.008..1.006 rows=16,876 loops=1)

23. 1.063 2.741 ↑ 1.0 7,410 1

Hash (cost=301.10..301.10 rows=7,410 width=35) (actual time=2.741..2.741 rows=7,410 loops=1)

  • Buckets: 8,192 Batches: 1 Memory Usage: 577kB
24. 1.678 1.678 ↑ 1.0 7,410 1

Seq Scan on cinema (cost=0.00..301.10 rows=7,410 width=35) (actual time=0.004..1.678 rows=7,410 loops=1)

25. 0.398 2.141 ↑ 1.0 4,804 1

Hash (cost=358.17..358.17 rows=4,844 width=6) (actual time=2.141..2.141 rows=4,804 loops=1)

  • Buckets: 8,192 Batches: 1 Memory Usage: 233kB
26. 0.373 1.743 ↑ 1.0 4,804 1

Hash Right Join (cost=228.99..358.17 rows=4,844 width=6) (actual time=0.891..1.743 rows=4,804 loops=1)

  • Hash Cond: (societe_redressement.id_societe = societe.id_societe)
27. 0.491 0.491 ↑ 1.0 52 1

Seq Scan on societe_redressement (cost=0.00..128.46 rows=52 width=6) (actual time=0.007..0.491 rows=52 loops=1)

  • Filter: (id_distri = 42)
  • Rows Removed by Filter: 7,105
28. 0.385 0.879 ↑ 1.0 4,804 1

Hash (cost=168.44..168.44 rows=4,844 width=4) (actual time=0.879..0.879 rows=4,804 loops=1)

  • Buckets: 8,192 Batches: 1 Memory Usage: 233kB
29. 0.494 0.494 ↑ 1.0 4,804 1

Seq Scan on societe (cost=0.00..168.44 rows=4,844 width=4) (actual time=0.004..0.494 rows=4,804 loops=1)

30. 1.536 3.001 ↑ 1.0 13,197 1

Hash (cost=581.97..581.97 rows=13,197 width=22) (actual time=3.001..3.001 rows=13,197 loops=1)

  • Buckets: 16,384 Batches: 1 Memory Usage: 846kB
31. 1.465 1.465 ↑ 1.0 13,197 1

Seq Scan on films (cost=0.00..581.97 rows=13,197 width=22) (actual time=0.005..1.465 rows=13,197 loops=1)

32. 2.304 5.166 ↑ 1.0 26,560 1

Hash (cost=541.60..541.60 rows=26,560 width=4) (actual time=5.166..5.166 rows=26,560 loops=1)

  • Buckets: 32,768 Batches: 1 Memory Usage: 1,190kB
33. 2.862 2.862 ↑ 1.0 26,560 1

Seq Scan on avoir_data (cost=0.00..541.60 rows=26,560 width=4) (actual time=0.005..2.862 rows=26,560 loops=1)

Planning time : 6.065 ms
Execution time : 2,187.211 ms