explain.depesz.com

PostgreSQL's explain analyze made readable

Result: U0ij

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# exclusive inclusive rows x rows loops node
1. 4,164.271 18,706.798 ↓ 1.0 98,049 1

Hash Left Join (cost=286,602.49..2,067,747.07 rows=95,376 width=3,765) (actual time=4,133.502..18,706.798 rows=98,049 loops=1)

  • Hash Cond: (tca.id_callback_action = ca.id_callback_action)
2. 1,807.275 14,542.371 ↓ 1.0 98,049 1

Nested Loop Left Join (cost=286,593.61..2,050,451.29 rows=95,376 width=3,712) (actual time=4,132.810..14,542.371 rows=98,049 loops=1)

3. 75.635 12,440.949 ↓ 1.0 98,049 1

Hash Left Join (cost=286,581.85..605,633.79 rows=95,376 width=3,631) (actual time=4,132.745..12,440.949 rows=98,049 loops=1)

  • Hash Cond: (t.id_last_follow_up = fu.id_follow_up)
4. 114.318 12,365.296 ↓ 1.0 98,049 1

Hash Left Join (cost=286,580.60..604,528.05 rows=95,376 width=1,567) (actual time=4,132.698..12,365.296 rows=98,049 loops=1)

  • Hash Cond: (v.id_utilisateur_creation = u3.id_utilisateur)
5. 103.488 12,248.563 ↓ 1.0 98,049 1

Hash Left Join (cost=286,352.62..602,511.77 rows=95,376 width=1,563) (actual time=4,130.247..12,248.563 rows=98,049 loops=1)

  • Hash Cond: (t.id_utilisateur_creation = u.id_utilisateur)
6. 71.295 12,142.561 ↓ 1.0 98,049 1

Hash Left Join (cost=286,124.63..600,495.48 rows=95,376 width=1,554) (actual time=4,127.706..12,142.561 rows=98,049 loops=1)

  • Hash Cond: (v.id_produit = p.id_produit)
7. 76.243 12,071.239 ↓ 1.0 98,049 1

Hash Left Join (cost=286,123.21..599,441.97 rows=95,376 width=1,042) (actual time=4,127.654..12,071.239 rows=98,049 loops=1)

  • Hash Cond: (t.id_ticket = cat.id_ticket)
8. 64.825 11,993.582 ↓ 1.0 98,049 1

Hash Left Join (cost=262,614.46..570,568.11 rows=95,376 width=1,034) (actual time=4,126.222..11,993.582 rows=98,049 loops=1)

  • Hash Cond: (t.id_ticketing_detail = td.id_ticketing_detail)
9. 111.922 11,928.731 ↓ 1.0 98,049 1

Hash Left Join (cost=262,612.69..570,125.29 rows=95,376 width=620) (actual time=4,126.190..11,928.731 rows=98,049 loops=1)

  • Hash Cond: (thi.id_utilisateur = thu.id_utilisateur)
10. 85.509 11,814.350 ↓ 1.0 98,049 1

Hash Join (cost=262,384.71..568,109.01 rows=95,376 width=615) (actual time=4,123.710..11,814.350 rows=98,049 loops=1)

  • Hash Cond: (tt.id_ticketing_queue = tq.id_ticketing_queue)
11. 5,411.403 11,728.822 ↓ 1.0 98,049 1

Hash Right Join (cost=262,383.44..566,796.32 rows=95,376 width=488) (actual time=4,123.672..11,728.822 rows=98,049 loops=1)

  • Hash Cond: (thi.id_ticketing_history = t.last_id_ticketing_history)
12. 2,196.175 2,196.175 ↑ 1.0 8,021,103 1

Seq Scan on ticketing_history thi (cost=0.00..139,250.94 rows=8,024,594 width=16) (actual time=0.066..2,196.175 rows=8,021,103 loops=1)

13. 137.860 4,121.244 ↓ 1.0 98,049 1

Hash (cost=255,323.24..255,323.24 rows=95,376 width=480) (actual time=4,121.244..4,121.244 rows=98,049 loops=1)

  • Buckets: 2048 Batches: 8 Memory Usage: 5020kB
14. 42.638 3,983.384 ↓ 1.0 98,049 1

Hash Join (cost=210,376.41..255,323.24 rows=95,376 width=480) (actual time=2,880.172..3,983.384 rows=98,049 loops=1)

  • Hash Cond: (t.id_ticketing_thematique = tt.id_ticketing_thematique)
15. 43.067 3,940.709 ↓ 1.0 98,049 1

Hash Join (cost=210,374.01..254,009.42 rows=95,376 width=458) (actual time=2,880.119..3,940.709 rows=98,049 loops=1)

  • Hash Cond: (t.id_ticketing_statut = ts.id_ticketing_statut)
16. 41.365 3,897.632 ↓ 1.0 98,049 1

Hash Join (cost=210,372.65..252,696.64 rows=95,376 width=335) (actual time=2,880.095..3,897.632 rows=98,049 loops=1)

  • Hash Cond: (v.id_statut_vente = sv.id_statut_vente)
17. 240.272 3,856.157 ↓ 1.0 98,049 1

Hash Join (cost=210,366.19..251,378.76 rows=95,376 width=296) (actual time=2,879.966..3,856.157 rows=98,049 loops=1)

  • Hash Cond: (v.id_client = c.id_client)
18. 464.038 2,782.112 ↓ 1.0 98,049 1

Hash Join (cost=148,228.27..177,587.32 rows=95,376 width=275) (actual time=2,046.079..2,782.112 rows=98,049 loops=1)

  • Hash Cond: (ams.id_adresse_manager = sa.id_address_manager)
19. 272.340 272.340 ↑ 1.0 552,101 1

Seq Scan on adresse_manager ams (cost=0.00..14,490.12 rows=554,712 width=37) (actual time=0.010..272.340 rows=552,101 loops=1)

20. 75.625 2,045.734 ↓ 1.0 98,049 1

Hash (cost=143,869.07..143,869.07 rows=95,376 width=246) (actual time=2,045.734..2,045.734 rows=98,049 loops=1)

  • Buckets: 4096 Batches: 4 Memory Usage: 4590kB
21. 304.479 1,970.109 ↓ 1.0 98,049 1

Hash Join (cost=128,273.42..143,869.07 rows=95,376 width=246) (actual time=1,552.318..1,970.109 rows=98,049 loops=1)

  • Hash Cond: (sa.id_sale = v.id_vente)
22. 113.710 113.710 ↑ 1.0 396,096 1

Seq Scan on sale_address sa (cost=0.00..6,879.28 rows=396,428 width=8) (actual time=0.012..113.710 rows=396,096 loops=1)

23. 77.028 1,551.920 ↓ 1.0 98,049 1

Hash (cost=123,899.27..123,899.27 rows=95,692 width=242) (actual time=1,551.920..1,551.920 rows=98,049 loops=1)

  • Buckets: 4096 Batches: 4 Memory Usage: 4543kB
24. 215.027 1,474.892 ↓ 1.0 98,049 1

Hash Join (cost=17,085.22..123,899.27 rows=95,692 width=242) (actual time=325.631..1,474.892 rows=98,049 loops=1)

  • Hash Cond: (t.id_vente = v.id_vente)
25. 934.816 934.816 ↓ 1.0 98,049 1

Seq Scan on ticket t (cost=0.00..97,131.88 rows=95,721 width=222) (actual time=0.068..934.816 rows=98,049 loops=1)

  • Filter: (id_ticketing_thematique = ANY ('{320,321,322}'::integer[]))
  • Rows Removed by Filter: 1851990
26. 135.203 325.049 ↑ 1.0 396,168 1

Hash (cost=9,782.43..9,782.43 rows=397,743 width=20) (actual time=325.049..325.049 rows=396,168 loops=1)

  • Buckets: 32768 Batches: 4 Memory Usage: 4948kB
27. 189.846 189.846 ↑ 1.0 396,168 1

Seq Scan on vente v (cost=0.00..9,782.43 rows=397,743 width=20) (actual time=0.026..189.846 rows=396,168 loops=1)

28. 183.756 833.773 ↓ 1.0 392,509 1

Hash (cost=54,598.63..54,598.63 rows=389,863 width=25) (actual time=833.773..833.773 rows=392,509 loops=1)

  • Buckets: 16384 Batches: 4 Memory Usage: 5570kB
29. 650.017 650.017 ↓ 1.0 392,509 1

Seq Scan on client c (cost=0.00..54,598.63 rows=389,863 width=25) (actual time=0.701..650.017 rows=392,509 loops=1)

30. 0.054 0.110 ↑ 1.0 154 1

Hash (cost=4.54..4.54 rows=154 width=43) (actual time=0.110..0.110 rows=154 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 12kB
31. 0.056 0.056 ↑ 1.0 154 1

Seq Scan on statut_vente sv (cost=0.00..4.54 rows=154 width=43) (actual time=0.004..0.056 rows=154 loops=1)

32. 0.005 0.010 ↑ 1.0 16 1

Hash (cost=1.16..1.16 rows=16 width=123) (actual time=0.010..0.010 rows=16 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
33. 0.005 0.005 ↑ 1.0 16 1

Seq Scan on ticketing_statut ts (cost=0.00..1.16 rows=16 width=123) (actual time=0.003..0.005 rows=16 loops=1)

34. 0.020 0.037 ↓ 1.0 63 1

Hash (cost=1.62..1.62 rows=62 width=30) (actual time=0.037..0.037 rows=63 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 4kB
35. 0.017 0.017 ↓ 1.0 63 1

Seq Scan on ticketing_thematique tt (cost=0.00..1.62 rows=62 width=30) (actual time=0.004..0.017 rows=63 loops=1)

36. 0.005 0.019 ↓ 1.1 13 1

Hash (cost=1.12..1.12 rows=12 width=135) (actual time=0.019..0.019 rows=13 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
37. 0.014 0.014 ↓ 1.1 13 1

Seq Scan on ticketing_queue tq (cost=0.00..1.12 rows=12 width=135) (actual time=0.010..0.014 rows=13 loops=1)

38. 1.092 2.459 ↑ 1.0 4,666 1

Hash (cost=169.66..169.66 rows=4,666 width=13) (actual time=2.459..2.459 rows=4,666 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 220kB
39. 1.367 1.367 ↑ 1.0 4,666 1

Seq Scan on utilisateur thu (cost=0.00..169.66 rows=4,666 width=13) (actual time=0.007..1.367 rows=4,666 loops=1)

40. 0.008 0.026 ↓ 1.0 35 1

Hash (cost=1.34..1.34 rows=34 width=422) (actual time=0.026..0.026 rows=35 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 2kB
41. 0.018 0.018 ↓ 1.0 35 1

Seq Scan on ticketing_detail td (cost=0.00..1.34 rows=34 width=422) (actual time=0.011..0.018 rows=35 loops=1)

42. 0.064 1.414 ↑ 2.1 209 1

Hash (cost=23,503.37..23,503.37 rows=430 width=12) (actual time=1.414..1.414 rows=209 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
43. 0.056 1.350 ↑ 2.1 209 1

Subquery Scan on cat (cost=23,494.77..23,503.37 rows=430 width=12) (actual time=1.253..1.350 rows=209 loops=1)

44. 0.216 1.294 ↑ 2.1 209 1

HashAggregate (cost=23,494.77..23,499.07 rows=430 width=4) (actual time=1.253..1.294 rows=209 loops=1)

  • Group Key: tca_1.id_ticket
45. 1.003 1.078 ↑ 34.0 220 1

Bitmap Heap Scan on ticketing_callback_action tca_1 (cost=174.43..23,457.35 rows=7,484 width=4) (actual time=0.104..1.078 rows=220 loops=1)

  • Recheck Cond: (id_callback_action = 2060)
  • Heap Blocks: exact=214
46. 0.075 0.075 ↑ 34.0 220 1

Bitmap Index Scan on ix_ticketing_callback_action_id_vw_order_error (cost=0.00..172.56 rows=7,484 width=0) (actual time=0.075..0.075 rows=220 loops=1)

  • Index Cond: (id_callback_action = 2060)
47. 0.009 0.027 ↑ 1.0 19 1

Hash (cost=1.19..1.19 rows=19 width=520) (actual time=0.027..0.027 rows=19 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 2kB
48. 0.018 0.018 ↑ 1.0 19 1

Seq Scan on produit p (cost=0.00..1.19 rows=19 width=520) (actual time=0.014..0.018 rows=19 loops=1)

49. 1.245 2.514 ↑ 1.0 4,666 1

Hash (cost=169.66..169.66 rows=4,666 width=17) (actual time=2.514..2.514 rows=4,666 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 221kB
50. 1.269 1.269 ↑ 1.0 4,666 1

Seq Scan on utilisateur u (cost=0.00..169.66 rows=4,666 width=17) (actual time=0.004..1.269 rows=4,666 loops=1)

51. 1.109 2.415 ↑ 1.0 4,666 1

Hash (cost=169.66..169.66 rows=4,666 width=8) (actual time=2.415..2.415 rows=4,666 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 166kB
52. 1.306 1.306 ↑ 1.0 4,666 1

Seq Scan on utilisateur u3 (cost=0.00..169.66 rows=4,666 width=8) (actual time=0.004..1.306 rows=4,666 loops=1)

53. 0.011 0.018 ↑ 1.0 11 1

Hash (cost=1.11..1.11 rows=11 width=2,068) (actual time=0.018..0.018 rows=11 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 2kB
54. 0.007 0.007 ↑ 1.0 11 1

Seq Scan on follow_up fu (cost=0.00..1.11 rows=11 width=2,068) (actual time=0.006..0.007 rows=11 loops=1)

55. 0.000 294.147 ↓ 0.0 0 98,049

Index Scan using id_chasing_action_pkey on ticketing_callback_action tca (cost=11.76..15.14 rows=1 width=85) (actual time=0.003..0.003 rows=0 loops=98,049)

  • Index Cond: (id_ticketing_callback_action = (SubPlan 1))
56.          

SubPlan (forIndex Scan)

57. 98.049 1,470.735 ↑ 1.0 1 98,049

Aggregate (cost=11.32..11.33 rows=1 width=4) (actual time=0.015..0.015 rows=1 loops=98,049)

58. 1,372.686 1,372.686 ↑ 12.0 1 98,049

Index Scan using ix_ticketing_callback_action_id_ticket on ticketing_callback_action (cost=0.43..11.29 rows=12 width=4) (actual time=0.012..0.014 rows=1 loops=98,049)

  • Index Cond: (id_ticket = t.id_ticket)
  • Filter: (id_callback_action <> ALL ('{60,62}'::integer[]))
  • Rows Removed by Filter: 1
59. 98.049 1,470.735 ↑ 1.0 1 98,049

Aggregate (cost=11.32..11.33 rows=1 width=4) (actual time=0.015..0.015 rows=1 loops=98,049)

60. 1,372.686 1,372.686 ↑ 12.0 1 98,049

Index Scan using ix_ticketing_callback_action_id_ticket on ticketing_callback_action (cost=0.43..11.29 rows=12 width=4) (actual time=0.012..0.014 rows=1 loops=98,049)

  • Index Cond: (id_ticket = t.id_ticket)
  • Filter: (id_callback_action <> ALL ('{60,62}'::integer[]))
  • Rows Removed by Filter: 1
61. 0.068 0.156 ↑ 1.2 178 1

Hash (cost=6.17..6.17 rows=217 width=61) (actual time=0.156..0.156 rows=178 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 17kB
62. 0.088 0.088 ↑ 1.2 178 1

Seq Scan on callback_action ca (cost=0.00..6.17 rows=217 width=61) (actual time=0.018..0.088 rows=178 loops=1)