explain.depesz.com

PostgreSQL's explain analyze made readable

Result: MOER

Settings
# exclusive inclusive rows x rows loops node
1. 31,746.602 82,802.526 ↑ 312,392,459,224.6 1,402,849 1

Nested Loop Left Join (cost=1,195,902,451.43..251,388,762,808,151,488.00 rows=438,239,449,030,806,528 width=760) (actual time=15,123.574..82,802.526 rows=1,402,849 loops=1)

2. 957.563 31,416.038 ↑ 97,000,777.6 1,402,849 1

Hash Left Join (cost=1,195,902,451.43..5,348,136,445,660.45 rows=136,077,443,834,544 width=760) (actual time=15,122.019..31,416.038 rows=1,402,849 loops=1)

  • Hash Cond: (v.box_id = b.id)
3. 761.574 30,457.380 ↑ 6,083,460.5 1,402,849 1

Hash Left Join (cost=1,195,902,291.68..563,023,698,054.57 rows=8,534,176,471,279 width=764) (actual time=15,120.914..30,457.380 rows=1,402,849 loops=1)

  • Hash Cond: (p.geographical_site_id = gs.id)
4. 836.173 29,695.711 ↑ 1,813,252.0 1,402,849 1

Hash Left Join (cost=1,195,902,260.60..258,286,189,451.40 rows=2,543,718,769,383 width=681) (actual time=15,120.807..29,695.711 rows=1,402,849 loops=1)

  • Hash Cond: (r.reservation_agreement_id = ra.id)
5. 921.748 28,859.227 ↑ 723,853.1 1,402,849 1

Hash Left Join (cost=1,195,902,210.33..166,844,323,060.65 rows=1,015,456,594,564 width=514) (actual time=15,120.488..28,859.227 rows=1,402,849 loops=1)

  • Hash Cond: (r.account_id = a.id)
6. 10,593.910 27,936.007 ↑ 723,853.1 1,402,849 1

Hash Left Join (cost=1,195,901,929.02..149,073,832,374.47 rows=1,015,456,594,564 width=506) (actual time=15,119.001..27,936.007 rows=1,402,849 loops=1)

  • Hash Cond: (r.user_id = bu.id)
7. 785.775 16,035.181 ↑ 723,853.1 1,402,849 1

Merge Join (cost=1,195,819,296.84..16,429,725,809.80 rows=1,015,456,594,564 width=422) (actual time=13,811.534..16,035.181 rows=1,402,849 loops=1)

  • Merge Cond: (v.id = r.vehicle_id)
8. 2.614 15.139 ↑ 51.8 4,700 1

Sort (cost=40,411.59..41,019.94 rows=243,339 width=40) (actual time=14.152..15.139 rows=4,700 loops=1)

  • Sort Key: v.id
  • Sort Method: quicksort Memory: 655kB
9. 2.270 12.525 ↑ 44.4 5,485 1

Merge Join (cost=1,650.73..5,327.74 rows=243,339 width=40) (actual time=9.180..12.525 rows=5,485 loops=1)

  • Merge Cond: (v.vehicle_model_id = vm.id)
10. 2.097 4.199 ↓ 1.0 5,485 1

Sort (cost=648.65..662.11 rows=5,386 width=22) (actual time=3.736..4.199 rows=5,485 loops=1)

  • Sort Key: v.vehicle_model_id
  • Sort Method: quicksort Memory: 618kB
11. 0.324 2.102 ↓ 1.0 5,485 1

Append (cost=0.00..314.85 rows=5,386 width=22) (actual time=0.005..2.102 rows=5,485 loops=1)

12. 0.001 0.001 ↓ 0.0 0 1

Seq Scan on vehicle v (cost=0.00..0.00 rows=1 width=130) (actual time=0.001..0.001 rows=0 loops=1)

13. 0.075 0.075 ↑ 1.0 198 1

Seq Scan on vehicle v_1 (cost=0.00..11.98 rows=198 width=20) (actual time=0.004..0.075 rows=198 loops=1)

14. 0.318 0.318 ↑ 1.0 947 1

Seq Scan on vehicle v_2 (cost=0.00..55.47 rows=947 width=22) (actual time=0.003..0.318 rows=947 loops=1)

15. 1.215 1.215 ↓ 1.0 3,872 1

Seq Scan on vehicle v_3 (cost=0.00..219.72 rows=3,772 width=22) (actual time=0.001..1.215 rows=3,872 loops=1)

16. 0.077 0.077 ↑ 1.0 200 1

Seq Scan on vehicle v_4 (cost=0.00..12.00 rows=200 width=20) (actual time=0.002..0.077 rows=200 loops=1)

17. 0.005 0.005 ↑ 1.0 11 1

Seq Scan on vehicle v_5 (cost=0.00..1.11 rows=11 width=130) (actual time=0.002..0.005 rows=11 loops=1)

18. 0.087 0.087 ↑ 1.0 257 1

Seq Scan on vehicle v_6 (cost=0.00..14.57 rows=257 width=20) (actual time=0.002..0.087 rows=257 loops=1)

19. 3.639 6.056 ↓ 1.1 9,813 1

Sort (cost=1,002.08..1,024.67 rows=9,036 width=26) (actual time=5.439..6.056 rows=9,813 loops=1)

  • Sort Key: vm.id
  • Sort Method: quicksort Memory: 963kB
20. 0.535 2.417 ↓ 1.0 9,039 1

Append (cost=0.00..408.35 rows=9,036 width=26) (actual time=0.004..2.417 rows=9,039 loops=1)

21. 0.000 0.000 ↓ 0.0 0 1

Seq Scan on vehicle_model vm (cost=0.00..0.00 rows=1 width=244) (actual time=0.000..0.000 rows=0 loops=1)

22. 0.091 0.091 ↑ 1.0 411 1

Seq Scan on vehicle_model vm_1 (cost=0.00..17.11 rows=411 width=21) (actual time=0.003..0.091 rows=411 loops=1)

23. 0.377 0.377 ↑ 1.0 1,889 1

Seq Scan on vehicle_model vm_2 (cost=0.00..84.89 rows=1,889 width=21) (actual time=0.002..0.377 rows=1,889 loops=1)

24. 1.217 1.217 ↓ 1.0 5,758 1

Seq Scan on vehicle_model vm_3 (cost=0.00..267.54 rows=5,754 width=27) (actual time=0.004..1.217 rows=5,758 loops=1)

25. 0.086 0.086 ↑ 1.0 412 1

Seq Scan on vehicle_model vm_4 (cost=0.00..17.12 rows=412 width=22) (actual time=0.002..0.086 rows=412 loops=1)

26. 0.005 0.005 ↑ 1.0 12 1

Seq Scan on vehicle_model vm_5 (cost=0.00..1.12 rows=12 width=244) (actual time=0.002..0.005 rows=12 loops=1)

27. 0.106 0.106 ↑ 1.0 557 1

Seq Scan on vehicle_model vm_6 (cost=0.00..20.57 rows=557 width=28) (actual time=0.002..0.106 rows=557 loops=1)

28. 646.795 15,234.267 ↑ 594.9 1,402,849 1

Materialize (cost=1,195,778,885.25..1,199,951,889.11 rows=834,600,772 width=386) (actual time=13,797.376..15,234.267 rows=1,402,849 loops=1)

29. 4,925.950 14,587.472 ↑ 594.9 1,402,849 1

Sort (cost=1,195,778,885.25..1,197,865,387.18 rows=834,600,772 width=386) (actual time=13,797.373..14,587.472 rows=1,402,849 loops=1)

  • Sort Key: r.vehicle_id
  • Sort Method: external merge Disk: 363,568kB
30. 357.807 9,661.522 ↑ 594.9 1,402,849 1

Hash Left Join (cost=34,033.01..33,744,870.89 rows=834,600,772 width=386) (actual time=1,302.274..9,661.522 rows=1,402,849 loops=1)

  • Hash Cond: (r.waypoint = w_p.id)
31. 588.980 9,302.550 ↑ 70.7 1,402,849 1

Hash Left Join (cost=33,861.17..4,310,384.07 rows=99,239,093 width=365) (actual time=1,301.090..9,302.550 rows=1,402,849 loops=1)

  • Hash Cond: (r.arrival_parking_id = a_p.id)
32. 607.052 8,712.589 ↑ 8.4 1,402,849 1

Hash Join (cost=33,689.34..810,293.68 rows=11,800,130 width=369) (actual time=1,300.084..8,712.589 rows=1,402,849 loops=1)

  • Hash Cond: (r.departure_parking_id = p.id)
33. 575.735 8,104.670 ↑ 1.0 1,402,849 1

Hash Join (cost=33,517.50..393,960.31 rows=1,403,107 width=340) (actual time=1,299.161..8,104.670 rows=1,402,849 loops=1)

  • Hash Cond: (r.company_id = c.id)
34. 4,532.667 7,527.114 ↑ 1.0 1,402,849 1

Hash Left Join (cost=33,216.65..369,105.08 rows=1,403,107 width=326) (actual time=1,297.319..7,527.114 rows=1,402,849 loops=1)

  • Hash Cond: (r.trip_id = ubn.trip_id)
35. 120.475 1,697.231 ↑ 1.0 1,402,849 1

Append (cost=0.00..188,547.06 rows=1,403,107 width=318) (actual time=0.014..1,697.231 rows=1,402,849 loops=1)

36. 0.000 0.000 ↓ 0.0 0 1

Seq Scan on reservation r (cost=0.00..0.00 rows=1 width=1,060) (actual time=0.000..0.000 rows=0 loops=1)

37. 74.177 74.177 ↑ 1.0 64,988 1

Seq Scan on reservation r_1 (cost=0.00..11,621.88 rows=64,988 width=304) (actual time=0.014..74.177 rows=64,988 loops=1)

38. 379.741 379.741 ↑ 1.0 278,628 1

Seq Scan on reservation r_2 (cost=0.00..50,048.28 rows=278,628 width=345) (actual time=0.015..379.741 rows=278,628 loops=1)

39. 924.086 924.086 ↑ 1.0 912,319 1

Seq Scan on reservation r_3 (cost=0.00..93,457.76 rows=912,576 width=310) (actual time=0.025..924.086 rows=912,319 loops=1)

40. 151.896 151.896 ↑ 1.0 111,195 1

Seq Scan on reservation r_4 (cost=0.00..26,797.95 rows=111,195 width=323) (actual time=0.021..151.896 rows=111,195 loops=1)

41. 2.627 2.627 ↑ 1.0 2,352 1

Seq Scan on reservation r_5 (cost=0.00..166.52 rows=2,352 width=283) (actual time=0.040..2.627 rows=2,352 loops=1)

42. 44.229 44.229 ↑ 1.0 33,367 1

Seq Scan on reservation r_6 (cost=0.00..6,454.67 rows=33,367 width=309) (actual time=0.013..44.229 rows=33,367 loops=1)

43. 1,120.394 1,297.216 ↑ 1.0 1,013,051 1

Hash (cost=15,606.51..15,606.51 rows=1,013,051 width=12) (actual time=1,297.216..1,297.216 rows=1,013,051 loops=1)

  • Buckets: 4,096 Batches: 64 Memory Usage: 695kB
44. 176.822 176.822 ↑ 1.0 1,013,051 1

Seq Scan on mv_user_booking_number ubn (cost=0.00..15,606.51 rows=1,013,051 width=12) (actual time=0.376..176.822 rows=1,013,051 loops=1)

45. 0.718 1.821 ↑ 1.0 3,638 1

Hash (cost=255.38..255.38 rows=3,638 width=22) (actual time=1.821..1.821 rows=3,638 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 197kB
46. 1.103 1.103 ↑ 1.0 3,638 1

Seq Scan on company c (cost=0.00..255.38 rows=3,638 width=22) (actual time=0.002..1.103 rows=3,638 loops=1)

47. 0.362 0.867 ↑ 1.0 1,673 1

Hash (cost=150.81..150.81 rows=1,682 width=33) (actual time=0.867..0.867 rows=1,673 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 108kB
48. 0.110 0.505 ↑ 1.0 1,673 1

Append (cost=0.00..150.81 rows=1,682 width=33) (actual time=0.004..0.505 rows=1,673 loops=1)

49. 0.000 0.000 ↓ 0.0 0 1

Seq Scan on parking p (cost=0.00..0.00 rows=1 width=126) (actual time=0.000..0.000 rows=0 loops=1)

50. 0.035 0.035 ↑ 1.0 121 1

Seq Scan on parking p_1 (cost=0.00..10.21 rows=121 width=32) (actual time=0.003..0.035 rows=121 loops=1)

51. 0.102 0.102 ↑ 1.0 496 1

Seq Scan on parking p_2 (cost=0.00..43.96 rows=496 width=35) (actual time=0.002..0.102 rows=496 loops=1)

52. 0.173 0.173 ↑ 1.0 754 1

Seq Scan on parking p_3 (cost=0.00..72.62 rows=762 width=30) (actual time=0.004..0.173 rows=754 loops=1)

53. 0.020 0.020 ↑ 1.0 115 1

Seq Scan on parking p_4 (cost=0.00..7.15 rows=115 width=27) (actual time=0.002..0.020 rows=115 loops=1)

54. 0.002 0.002 ↑ 1.0 6 1

Seq Scan on parking p_5 (cost=0.00..1.06 rows=6 width=126) (actual time=0.002..0.002 rows=6 loops=1)

55. 0.063 0.063 ↑ 1.0 181 1

Seq Scan on parking p_6 (cost=0.00..15.81 rows=181 width=37) (actual time=0.003..0.063 rows=181 loops=1)

56. 0.409 0.981 ↑ 1.0 1,673 1

Hash (cost=150.81..150.81 rows=1,682 width=4) (actual time=0.981..0.981 rows=1,673 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 59kB
57. 0.139 0.572 ↑ 1.0 1,673 1

Append (cost=0.00..150.81 rows=1,682 width=4) (actual time=0.006..0.572 rows=1,673 loops=1)

58. 0.000 0.000 ↓ 0.0 0 1

Seq Scan on parking a_p (cost=0.00..0.00 rows=1 width=4) (actual time=0.000..0.000 rows=0 loops=1)

59. 0.046 0.046 ↑ 1.0 121 1

Seq Scan on parking a_p_1 (cost=0.00..10.21 rows=121 width=4) (actual time=0.005..0.046 rows=121 loops=1)

60. 0.122 0.122 ↑ 1.0 496 1

Seq Scan on parking a_p_2 (cost=0.00..43.96 rows=496 width=4) (actual time=0.001..0.122 rows=496 loops=1)

61. 0.179 0.179 ↑ 1.0 754 1

Seq Scan on parking a_p_3 (cost=0.00..72.62 rows=762 width=4) (actual time=0.002..0.179 rows=754 loops=1)

62. 0.032 0.032 ↑ 1.0 115 1

Seq Scan on parking a_p_4 (cost=0.00..7.15 rows=115 width=4) (actual time=0.002..0.032 rows=115 loops=1)

63. 0.003 0.003 ↑ 1.0 6 1

Seq Scan on parking a_p_5 (cost=0.00..1.06 rows=6 width=4) (actual time=0.001..0.003 rows=6 loops=1)

64. 0.051 0.051 ↑ 1.0 181 1

Seq Scan on parking a_p_6 (cost=0.00..15.81 rows=181 width=4) (actual time=0.001..0.051 rows=181 loops=1)

65. 0.568 1.165 ↑ 1.0 1,673 1

Hash (cost=150.81..150.81 rows=1,682 width=29) (actual time=1.165..1.165 rows=1,673 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 102kB
66. 0.149 0.597 ↑ 1.0 1,673 1

Append (cost=0.00..150.81 rows=1,682 width=29) (actual time=0.005..0.597 rows=1,673 loops=1)

67. 0.001 0.001 ↓ 0.0 0 1

Seq Scan on parking w_p (cost=0.00..0.00 rows=1 width=122) (actual time=0.001..0.001 rows=0 loops=1)

68. 0.044 0.044 ↑ 1.0 121 1

Seq Scan on parking w_p_1 (cost=0.00..10.21 rows=121 width=28) (actual time=0.003..0.044 rows=121 loops=1)

69. 0.132 0.132 ↑ 1.0 496 1

Seq Scan on parking w_p_2 (cost=0.00..43.96 rows=496 width=31) (actual time=0.001..0.132 rows=496 loops=1)

70. 0.195 0.195 ↑ 1.0 754 1

Seq Scan on parking w_p_3 (cost=0.00..72.62 rows=762 width=26) (actual time=0.001..0.195 rows=754 loops=1)

71. 0.024 0.024 ↑ 1.0 115 1

Seq Scan on parking w_p_4 (cost=0.00..7.15 rows=115 width=23) (actual time=0.002..0.024 rows=115 loops=1)

72. 0.003 0.003 ↑ 1.0 6 1

Seq Scan on parking w_p_5 (cost=0.00..1.06 rows=6 width=122) (actual time=0.001..0.003 rows=6 loops=1)

73. 0.049 0.049 ↑ 1.0 181 1

Seq Scan on parking w_p_6 (cost=0.00..15.81 rows=181 width=33) (actual time=0.002..0.049 rows=181 loops=1)

74. 144.928 1,306.916 ↓ 1.0 427,711 1

Hash (cost=71,019.90..71,019.90 rows=427,703 width=92) (actual time=1,306.916..1,306.916 rows=427,711 loops=1)

  • Buckets: 1,024 Batches: 64 Memory Usage: 731kB
75. 369.763 1,161.988 ↓ 1.0 427,711 1

Hash Left Join (cost=35,002.82..71,019.90 rows=427,703 width=92) (actual time=697.790..1,161.988 rows=427,711 loops=1)

  • Hash Cond: (bu.id = u.user_id)
76. 94.491 94.491 ↓ 1.0 427,711 1

Seq Scan on basic_user bu (cost=0.00..16,546.03 rows=427,703 width=68) (actual time=0.044..94.491 rows=427,711 loops=1)

77. 106.554 697.734 ↓ 1.0 426,998 1

Hash (cost=27,163.45..27,163.45 rows=426,990 width=24) (actual time=697.734..697.734 rows=426,998 loops=1)

  • Buckets: 2,048 Batches: 32 Memory Usage: 501kB
78. 110.467 591.180 ↓ 1.0 426,998 1

Hash Left Join (cost=846.49..27,163.45 rows=426,990 width=24) (actual time=11.582..591.180 rows=426,998 loops=1)

  • Hash Cond: (u.economic_unit_id = eu.id)
79. 471.203 471.203 ↓ 1.0 426,998 1

Seq Scan on "user" u (cost=0.00..17,314.90 rows=426,990 width=15) (actual time=2.055..471.203 rows=426,998 loops=1)

80. 4.492 9.510 ↑ 1.0 24,155 1

Hash (cost=402.55..402.55 rows=24,155 width=17) (actual time=9.510..9.510 rows=24,155 loops=1)

  • Buckets: 2,048 Batches: 2 Memory Usage: 603kB
81. 5.018 5.018 ↑ 1.0 24,155 1

Seq Scan on economic_unit eu (cost=0.00..402.55 rows=24,155 width=17) (actual time=0.524..5.018 rows=24,155 loops=1)

82. 0.741 1.472 ↑ 1.0 4,325 1

Hash (cost=227.25..227.25 rows=4,325 width=12) (actual time=1.472..1.472 rows=4,325 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 189kB
83. 0.731 0.731 ↑ 1.0 4,325 1

Seq Scan on account a (cost=0.00..227.25 rows=4,325 width=12) (actual time=0.012..0.731 rows=4,325 loops=1)

84. 0.119 0.311 ↑ 1.0 500 1

Hash (cost=44.00..44.00 rows=501 width=171) (actual time=0.311..0.311 rows=500 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 45kB
85. 0.034 0.192 ↑ 1.0 500 1

Append (cost=0.00..44.00 rows=501 width=171) (actual time=0.004..0.192 rows=500 loops=1)

86. 0.000 0.000 ↓ 0.0 0 1

Seq Scan on reservation_agreement ra (cost=0.00..0.00 rows=1 width=696) (actual time=0.000..0.000 rows=0 loops=1)

87. 0.010 0.010 ↑ 1.0 28 1

Seq Scan on reservation_agreement ra_1 (cost=0.00..2.28 rows=28 width=696) (actual time=0.003..0.010 rows=28 loops=1)

88. 0.033 0.033 ↑ 1.0 127 1

Seq Scan on reservation_agreement ra_2 (cost=0.00..9.27 rows=127 width=59) (actual time=0.002..0.033 rows=127 loops=1)

89. 0.092 0.092 ↑ 1.0 284 1

Seq Scan on reservation_agreement ra_3 (cost=0.00..25.84 rows=284 width=55) (actual time=0.002..0.092 rows=284 loops=1)

90. 0.009 0.009 ↑ 1.0 37 1

Seq Scan on reservation_agreement ra_4 (cost=0.00..3.37 rows=37 width=696) (actual time=0.002..0.009 rows=37 loops=1)

91. 0.004 0.004 ↑ 1.0 3 1

Seq Scan on reservation_agreement ra_5 (cost=0.00..1.03 rows=3 width=696) (actual time=0.004..0.004 rows=3 loops=1)

92. 0.010 0.010 ↑ 1.0 21 1

Seq Scan on reservation_agreement ra_6 (cost=0.00..2.21 rows=21 width=696) (actual time=0.002..0.010 rows=21 loops=1)

93. 0.046 0.095 ↑ 2.8 240 1

Hash (cost=22.70..22.70 rows=671 width=91) (actual time=0.095..0.095 rows=240 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 13kB
94. 0.014 0.049 ↑ 2.8 240 1

Append (cost=0.00..22.70 rows=671 width=91) (actual time=0.002..0.049 rows=240 loops=1)

95. 0.001 0.001 ↓ 0.0 0 1

Seq Scan on geographical_site gs (cost=0.00..0.00 rows=1 width=122) (actual time=0.001..0.001 rows=0 loops=1)

96. 0.001 0.001 ↑ 1.0 6 1

Seq Scan on geographical_site gs_1 (cost=0.00..1.06 rows=6 width=122) (actual time=0.001..0.001 rows=6 loops=1)

97. 0.009 0.009 ↑ 1.0 81 1

Seq Scan on geographical_site gs_2 (cost=0.00..1.81 rows=81 width=16) (actual time=0.002..0.009 rows=81 loops=1)

98. 0.014 0.014 ↑ 1.0 125 1

Seq Scan on geographical_site gs_3 (cost=0.00..3.25 rows=125 width=22) (actual time=0.003..0.014 rows=125 loops=1)

99. 0.003 0.003 ↑ 1.0 14 1

Seq Scan on geographical_site gs_4 (cost=0.00..1.14 rows=14 width=122) (actual time=0.001..0.003 rows=14 loops=1)

100. 0.001 0.001 ↓ 0.0 0 1

Seq Scan on geographical_site gs_5 (cost=0.00..14.30 rows=430 width=122) (actual time=0.001..0.001 rows=0 loops=1)

101. 0.006 0.006 ↑ 1.0 14 1

Seq Scan on geographical_site gs_6 (cost=0.00..1.14 rows=14 width=122) (actual time=0.004..0.006 rows=14 loops=1)

102. 0.428 1.095 ↑ 1.0 3,177 1

Hash (cost=119.88..119.88 rows=3,189 width=4) (actual time=1.095..1.095 rows=3,177 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 112kB
103. 0.189 0.667 ↑ 1.0 3,177 1

Append (cost=0.00..119.88 rows=3,189 width=4) (actual time=0.002..0.667 rows=3,177 loops=1)

104. 0.000 0.000 ↓ 0.0 0 1

Seq Scan on box b (cost=0.00..0.00 rows=1 width=4) (actual time=0.000..0.000 rows=0 loops=1)

105. 0.020 0.020 ↑ 1.0 145 1

Seq Scan on box b_1 (cost=0.00..5.46 rows=146 width=4) (actual time=0.002..0.020 rows=145 loops=1)

106. 0.115 0.115 ↑ 1.0 788 1

Seq Scan on box b_2 (cost=0.00..28.88 rows=788 width=4) (actual time=0.002..0.115 rows=788 loops=1)

107. 0.292 0.292 ↑ 1.0 1,858 1

Seq Scan on box b_3 (cost=0.00..69.68 rows=1,868 width=4) (actual time=0.002..0.292 rows=1,858 loops=1)

108. 0.025 0.025 ↑ 1.0 201 1

Seq Scan on box b_4 (cost=0.00..8.01 rows=201 width=4) (actual time=0.002..0.025 rows=201 loops=1)

109. 0.003 0.003 ↑ 1.0 20 1

Seq Scan on box b_5 (cost=0.00..1.20 rows=20 width=4) (actual time=0.002..0.003 rows=20 loops=1)

110. 0.023 0.023 ↑ 1.0 165 1

Seq Scan on box b_6 (cost=0.00..6.65 rows=165 width=4) (actual time=0.002..0.023 rows=165 loops=1)

111. 4,208.547 19,639.886 ↓ 0.0 0 1,402,849

Append (cost=0.00..43.80 rows=7 width=8) (actual time=0.011..0.014 rows=0 loops=1,402,849)

112. 0.000 0.000 ↓ 0.0 0 1,402,849

Seq Scan on trip_rating tr (cost=0.00..0.00 rows=1 width=8) (actual time=0.000..0.000 rows=0 loops=1,402,849)

  • Filter: (trip_id = r.trip_id)
113. 2,805.698 2,805.698 ↓ 0.0 0 1,402,849

Index Scan using trip_rating_be_pkey on trip_rating tr_1 (cost=0.29..7.66 rows=1 width=8) (actual time=0.002..0.002 rows=0 loops=1,402,849)

  • Index Cond: (trip_id = r.trip_id)
114. 2,805.698 2,805.698 ↓ 0.0 0 1,402,849

Index Scan using trip_rating_de_pkey on trip_rating tr_2 (cost=0.42..7.82 rows=1 width=8) (actual time=0.002..0.002 rows=0 loops=1,402,849)

  • Index Cond: (trip_id = r.trip_id)
115. 5,611.396 5,611.396 ↓ 0.0 0 1,402,849

Index Scan using trip_rating_fr_pkey on trip_rating tr_3 (cost=0.42..7.83 rows=1 width=8) (actual time=0.004..0.004 rows=0 loops=1,402,849)

  • Index Cond: (trip_id = r.trip_id)
116. 2,805.698 2,805.698 ↓ 0.0 0 1,402,849

Index Scan using trip_rating_it_pkey on trip_rating tr_4 (cost=0.29..7.69 rows=1 width=8) (actual time=0.002..0.002 rows=0 loops=1,402,849)

  • Index Cond: (trip_id = r.trip_id)
117. 1,402.849 1,402.849 ↓ 0.0 0 1,402,849

Index Scan using trip_rating_lu_pkey on trip_rating tr_5 (cost=0.15..5.17 rows=1 width=8) (actual time=0.001..0.001 rows=0 loops=1,402,849)

  • Index Cond: (trip_id = r.trip_id)
Planning time : 42.847 ms
Execution time : 83,037.115 ms