explain.depesz.com

PostgreSQL's explain analyze made readable

Result: PZxd

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# exclusive inclusive rows x rows loops node
1. 4,761.016 24,628.966 ↓ 1.3 105,239 1

Hash Left Join (cost=236,127.36..1,860,984.28 rows=83,818 width=3,254) (actual time=4,331.982..24,628.966 rows=105,239 loops=1)

  • Hash Cond: (tca.id_callback_action = ca.id_callback_action)
2. 7,530.009 19,867.254 ↓ 1.3 105,239 1

Nested Loop Left Join (cost=236,119.36..1,845,784.26 rows=83,818 width=3,200) (actual time=4,330.591..19,867.254 rows=105,239 loops=1)

3. 90.654 11,284.855 ↓ 1.3 105,239 1

Hash Left Join (cost=236,107.82..591,619.37 rows=83,818 width=3,120) (actual time=4,330.511..11,284.855 rows=105,239 loops=1)

  • Hash Cond: (t.id_last_follow_up = fu.id_follow_up)
4. 83.523 11,193.937 ↓ 1.3 105,239 1

Hash Left Join (cost=236,106.58..590,650.69 rows=83,818 width=1,572) (actual time=4,330.217..11,193.937 rows=105,239 loops=1)

  • Hash Cond: (v.id_produit = p.id_produit)
5. 76.803 11,110.151 ↓ 1.3 105,239 1

Hash Left Join (cost=236,105.15..589,718.61 rows=83,818 width=1,060) (actual time=4,329.904..11,110.151 rows=105,239 loops=1)

  • Hash Cond: (t.id_ticket = cat.id_ticket)
6. 69.231 10,964.669 ↓ 1.3 105,239 1

Hash Left Join (cost=211,884.74..560,573.71 rows=83,818 width=1,052) (actual time=4,261.193..10,964.669 rows=105,239 loops=1)

  • Hash Cond: (t.id_ticketing_detail = td.id_ticketing_detail)
7. 150.791 10,895.039 ↓ 1.3 105,239 1

Hash Left Join (cost=211,882.97..560,180.29 rows=83,818 width=638) (actual time=4,260.781..10,895.039 rows=105,239 loops=1)

  • Hash Cond: (thi.id_utilisateur = thu.id_utilisateur)
8. 146.663 10,741.790 ↓ 1.3 105,239 1

Nested Loop Left Join (cost=211,699.06..558,424.78 rows=83,818 width=633) (actual time=4,258.274..10,741.790 rows=105,239 loops=1)

9. 115.727 6,175.089 ↓ 1.3 105,239 1

Hash Join (cost=211,698.62..251,774.78 rows=83,818 width=625) (actual time=4,258.160..6,175.089 rows=105,239 loops=1)

  • Hash Cond: (v.id_utilisateur_creation = u3.id_utilisateur)
10. 115.954 6,054.871 ↓ 1.3 105,239 1

Hash Join (cost=211,514.70..250,019.27 rows=83,818 width=621) (actual time=4,253.634..6,054.871 rows=105,239 loops=1)

  • Hash Cond: (t.id_utilisateur_creation = u.id_utilisateur)
11. 79.270 5,936.395 ↓ 1.3 105,239 1

Hash Join (cost=211,330.79..248,263.77 rows=83,818 width=612) (actual time=4,251.089..5,936.395 rows=105,239 loops=1)

  • Hash Cond: (tt.id_ticketing_queue = tq.id_ticketing_queue)
12. 75.903 5,856.825 ↓ 1.3 105,239 1

Hash Join (cost=211,329.49..247,109.98 rows=83,818 width=485) (actual time=4,250.750..5,856.825 rows=105,239 loops=1)

  • Hash Cond: (t.id_ticketing_thematique = tt.id_ticketing_thematique)
13. 74.065 5,780.881 ↓ 1.3 105,239 1

Hash Join (cost=211,327.08..245,955.06 rows=83,818 width=463) (actual time=4,250.675..5,780.881 rows=105,239 loops=1)

  • Hash Cond: (t.id_ticketing_statut = ts.id_ticketing_statut)
14. 88.536 5,706.537 ↓ 1.3 105,239 1

Hash Join (cost=211,325.72..244,801.20 rows=83,818 width=340) (actual time=4,250.362..5,706.537 rows=105,239 loops=1)

  • Hash Cond: (v.id_statut_vente = sv.id_statut_vente)
15. 986.008 5,617.860 ↓ 1.3 105,239 1

Hash Join (cost=211,319.25..243,642.24 rows=83,818 width=301) (actual time=4,250.179..5,617.860 rows=105,239 loops=1)

  • Hash Cond: (ams.id_adresse_manager = sa.id_address_manager)
16. 416.183 416.183 ↑ 1.0 623,768 1

Seq Scan on adresse_manager ams (cost=0.00..16,368.68 rows=623,768 width=37) (actual time=0.003..416.183 rows=623,768 loops=1)

17. 94.981 4,215.669 ↓ 1.3 105,239 1

Hash (cost=207,242.53..207,242.53 rows=83,818 width=272) (actual time=4,215.669..4,215.669 rows=105,239 loops=1)

  • Buckets: 4096 Batches: 4 Memory Usage: 5718kB
18. 189.360 4,120.688 ↓ 1.3 105,239 1

Hash Join (cost=179,561.01..207,242.53 rows=83,818 width=272) (actual time=3,421.615..4,120.688 rows=105,239 loops=1)

  • Hash Cond: (v.id_client = c.id_client)
19. 378.804 3,039.779 ↓ 1.0 105,252 1

Hash Join (cost=140,302.86..157,140.62 rows=104,295 width=252) (actual time=2,529.687..3,039.779 rows=105,252 loops=1)

  • Hash Cond: (sa.id_sale = v.id_vente)
20. 149.388 149.388 ↑ 1.0 426,386 1

Seq Scan on sale_address sa (cost=0.00..7,399.86 rows=426,386 width=8) (actual time=1.203..149.388 rows=426,386 loops=1)

21. 90.555 2,511.587 ↓ 1.0 105,253 1

Hash (cost=135,534.95..135,534.95 rows=104,313 width=248) (actual time=2,511.587..2,511.587 rows=105,253 loops=1)

  • Buckets: 4096 Batches: 4 Memory Usage: 5068kB
22. 239.574 2,421.032 ↓ 1.0 105,253 1

Hash Join (cost=18,368.33..135,534.95 rows=104,313 width=248) (actual time=466.006..2,421.032 rows=105,253 loops=1)

  • Hash Cond: (t.id_vente = v.id_vente)
23. 1,716.231 1,716.231 ↓ 1.0 105,253 1

Seq Scan on ticket t (cost=0.00..106,448.27 rows=104,355 width=228) (actual time=0.031..1,716.231 rows=105,253 loops=1)

  • Filter: (id_ticketing_thematique = ANY ('{320,321,322}'::integer[]))
  • Rows Removed by Filter: 2014912
24. 219.769 465.227 ↑ 1.0 426,459 1

Hash (cost=10,538.59..10,538.59 rows=426,459 width=20) (actual time=465.227..465.227 rows=426,459 loops=1)

  • Buckets: 32768 Batches: 4 Memory Usage: 5332kB
25. 245.458 245.458 ↑ 1.0 426,459 1

Seq Scan on vente v (cost=0.00..10,538.59 rows=426,459 width=20) (actual time=0.018..245.458 rows=426,459 loops=1)

26. 182.008 891.549 ↓ 1.0 335,306 1

Hash (cost=33,108.03..33,108.03 rows=334,970 width=24) (actual time=891.549..891.549 rows=335,306 loops=1)

  • Buckets: 32768 Batches: 2 Memory Usage: 9519kB
27. 709.541 709.541 ↓ 1.0 335,306 1

Seq Scan on client c (cost=0.00..33,108.03 rows=334,970 width=24) (actual time=0.355..709.541 rows=335,306 loops=1)

  • Filter: (id_type_client <> 3)
  • Rows Removed by Filter: 81496
28. 0.065 0.141 ↑ 1.0 154 1

Hash (cost=4.54..4.54 rows=154 width=43) (actual time=0.141..0.141 rows=154 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 12kB
29. 0.076 0.076 ↑ 1.0 154 1

Seq Scan on statut_vente sv (cost=0.00..4.54 rows=154 width=43) (actual time=0.004..0.076 rows=154 loops=1)

30. 0.006 0.279 ↑ 1.0 16 1

Hash (cost=1.16..1.16 rows=16 width=123) (actual time=0.279..0.279 rows=16 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
31. 0.273 0.273 ↑ 1.0 16 1

Seq Scan on ticketing_statut ts (cost=0.00..1.16 rows=16 width=123) (actual time=0.268..0.273 rows=16 loops=1)

32. 0.022 0.041 ↑ 1.0 63 1

Hash (cost=1.63..1.63 rows=63 width=30) (actual time=0.041..0.041 rows=63 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 4kB
33. 0.019 0.019 ↑ 1.0 63 1

Seq Scan on ticketing_thematique tt (cost=0.00..1.63 rows=63 width=30) (actual time=0.006..0.019 rows=63 loops=1)

34. 0.009 0.300 ↑ 1.0 13 1

Hash (cost=1.13..1.13 rows=13 width=135) (actual time=0.300..0.300 rows=13 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
35. 0.291 0.291 ↑ 1.0 13 1

Seq Scan on ticketing_queue tq (cost=0.00..1.13 rows=13 width=135) (actual time=0.290..0.291 rows=13 loops=1)

36. 1.273 2.522 ↑ 1.0 4,663 1

Hash (cost=125.63..125.63 rows=4,663 width=17) (actual time=2.522..2.522 rows=4,663 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 221kB
37. 1.249 1.249 ↑ 1.0 4,663 1

Seq Scan on utilisateur u (cost=0.00..125.63 rows=4,663 width=17) (actual time=0.003..1.249 rows=4,663 loops=1)

38. 1.169 4.491 ↑ 1.0 4,663 1

Hash (cost=125.63..125.63 rows=4,663 width=8) (actual time=4.491..4.491 rows=4,663 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 166kB
39. 3.322 3.322 ↑ 1.0 4,663 1

Seq Scan on utilisateur u3 (cost=0.00..125.63 rows=4,663 width=8) (actual time=0.376..3.322 rows=4,663 loops=1)

40. 4,420.038 4,420.038 ↑ 1.0 1 105,239

Index Scan using ticketing_history_pkey on ticketing_history thi (cost=0.43..3.65 rows=1 width=20) (actual time=0.041..0.042 rows=1 loops=105,239)

  • Index Cond: (id_ticketing_history = t.last_id_ticketing_history)
  • Filter: (id_ticket = t.id_ticket)
41. 1.133 2.458 ↑ 1.0 4,663 1

Hash (cost=125.63..125.63 rows=4,663 width=13) (actual time=2.458..2.458 rows=4,663 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 219kB
42. 1.325 1.325 ↑ 1.0 4,663 1

Seq Scan on utilisateur thu (cost=0.00..125.63 rows=4,663 width=13) (actual time=0.011..1.325 rows=4,663 loops=1)

43. 0.014 0.399 ↑ 1.0 34 1

Hash (cost=1.34..1.34 rows=34 width=422) (actual time=0.399..0.399 rows=34 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 2kB
44. 0.385 0.385 ↑ 1.0 34 1

Seq Scan on ticketing_detail td (cost=0.00..1.34 rows=34 width=422) (actual time=0.377..0.385 rows=34 loops=1)

45. 0.064 68.679 ↑ 1.9 234 1

Hash (cost=24,214.74..24,214.74 rows=454 width=12) (actual time=68.679..68.679 rows=234 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 11kB
46. 0.052 68.615 ↑ 1.9 234 1

Subquery Scan on cat (cost=24,205.66..24,214.74 rows=454 width=12) (actual time=68.515..68.615 rows=234 loops=1)

47. 0.633 68.563 ↑ 1.9 234 1

HashAggregate (cost=24,205.66..24,210.20 rows=454 width=4) (actual time=68.510..68.563 rows=234 loops=1)

  • Group Key: tca_1.id_ticket
48. 66.861 67.930 ↑ 30.8 247 1

Bitmap Heap Scan on ticketing_callback_action tca_1 (cost=179.31..24,167.67 rows=7,597 width=4) (actual time=1.361..67.930 rows=247 loops=1)

  • Recheck Cond: (id_callback_action = 2060)
  • Heap Blocks: exact=240
49. 1.069 1.069 ↑ 30.8 247 1

Bitmap Index Scan on ix_ticketing_callback_action_id_vw_order_error (cost=0.00..177.41 rows=7,597 width=0) (actual time=1.069..1.069 rows=247 loops=1)

  • Index Cond: (id_callback_action = 2060)
50. 0.015 0.263 ↑ 1.0 19 1

Hash (cost=1.19..1.19 rows=19 width=520) (actual time=0.263..0.263 rows=19 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 2kB
51. 0.248 0.248 ↑ 1.0 19 1

Seq Scan on produit p (cost=0.00..1.19 rows=19 width=520) (actual time=0.245..0.248 rows=19 loops=1)

52. 0.009 0.264 ↑ 1.0 11 1

Hash (cost=1.11..1.11 rows=11 width=1,552) (actual time=0.264..0.264 rows=11 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 2kB
53. 0.255 0.255 ↑ 1.0 11 1

Seq Scan on follow_up fu (cost=0.00..1.11 rows=11 width=1,552) (actual time=0.254..0.255 rows=11 loops=1)

54. 0.000 1,052.390 ↑ 1.0 1 105,239

Index Scan using id_chasing_action_pkey on ticketing_callback_action tca (cost=11.53..14.95 rows=1 width=84) (actual time=0.009..0.010 rows=1 loops=105,239)

  • Index Cond: (id_ticketing_callback_action = (SubPlan 1))
55.          

SubPlan (forIndex Scan)

56. 210.478 7,261.491 ↑ 1.0 1 105,239

Aggregate (cost=11.09..11.10 rows=1 width=4) (actual time=0.069..0.069 rows=1 loops=105,239)

57. 7,051.013 7,051.013 ↑ 12.0 1 105,239

Index Scan using ix_ticketing_callback_action_id_ticket on ticketing_callback_action (cost=0.43..11.06 rows=12 width=4) (actual time=0.056..0.067 rows=1 loops=105,239)

  • Index Cond: (id_ticket = t.id_ticket)
  • Filter: (id_callback_action <> ALL ('{60,62}'::integer[]))
  • Rows Removed by Filter: 1
58. 210.478 7,261.491 ↑ 1.0 1 105,239

Aggregate (cost=11.09..11.10 rows=1 width=4) (actual time=0.069..0.069 rows=1 loops=105,239)

59. 7,051.013 7,051.013 ↑ 12.0 1 105,239

Index Scan using ix_ticketing_callback_action_id_ticket on ticketing_callback_action (cost=0.43..11.06 rows=12 width=4) (actual time=0.056..0.067 rows=1 loops=105,239)

  • Index Cond: (id_ticket = t.id_ticket)
  • Filter: (id_callback_action <> ALL ('{60,62}'::integer[]))
  • Rows Removed by Filter: 1
60. 0.100 0.696 ↑ 1.0 178 1

Hash (cost=5.78..5.78 rows=178 width=62) (actual time=0.696..0.696 rows=178 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 17kB
61. 0.596 0.596 ↑ 1.0 178 1

Seq Scan on callback_action ca (cost=0.00..5.78 rows=178 width=62) (actual time=0.015..0.596 rows=178 loops=1)