explain.depesz.com

PostgreSQL's explain analyze made readable

Result: 6jXF

Settings
# exclusive inclusive rows x rows loops node
1. 53,015.567 93,939.439 ↓ 3.9 850,568 1

Hash Left Join (cost=1,091,416.22..24,764,621.75 rows=216,456 width=188) (actual time=2,770.301..93,939.439 rows=850,568 loops=1)

  • Hash Cond: ((projects.id = ""*SELECT* 1"".project_id) AND ((COALESCE(""*SELECT* 1_1"".activity_id, sa.activity_id)) = ""*SELECT* 1"".activity_id))
  • Join Filter: (("*SELECT* 1_1".date >= "*SELECT* 1".start_date) AND (("*SELECT* 1_1".date <= "*SELECT* 1".end_date) OR ("*SELECT* 1".end_date IS NULL)))
  • Rows Removed by Join Filter: 238662
2. 401.651 40,517.178 ↓ 3.9 850,568 1

Hash Join (cost=1,064,036.01..9,831,730.05 rows=216,456 width=136) (actual time=2,360.070..40,517.178 rows=850,568 loops=1)

  • Hash Cond: (projects.account_id = accounts.id)
3. 192.958 40,115.382 ↓ 1.7 1,116,748 1

Append (cost=1,064,017.34..9,823,492.72 rows=649,367 width=136) (actual time=2,359.919..40,115.382 rows=1,116,748 loops=1)

4. 893.375 39,474.006 ↓ 2.7 1,087,842 1

Hash Join (cost=1,064,017.34..9,302,607.62 rows=404,209 width=108) (actual time=2,359.919..39,474.006 rows=1,087,842 loops=1)

  • Hash Cond: (projects.account_id = accounts_1.id)
  • Join Filter: ((((""*SELECT* 1_1"".vacation_user_id)::double precision) IS NULL) OR (((""*SELECT* 1_1"".vacation_hours)::double precision) < (COALESCE(sa.capacity, accounts_1.default_capacity))::double precision))
  • Rows Removed by Join Filter: 13596
5. 720.094 38,580.474 ↑ 1.1 1,101,438 1

Hash Left Join (cost=1,063,998.38..9,284,260.78 rows=1,200,621 width=144) (actual time=2,343.650..38,580.474 rows=1,101,438 loops=1)

  • Hash Cond: ((projects.account_id = sa.account_id) AND ("*SELECT* 1_1".user_id = sa.user_id))
  • Join Filter: (("*SELECT* 1_1".date >= sa.start_date) AND ("*SELECT* 1_1".date <= sa.end_date))
  • Rows Removed by Join Filter: 259092
6. 521.764 37,841.775 ↑ 1.1 1,101,438 1

Hash Join (cost=1,063,002.52..8,000,001.13 rows=1,200,621 width=120) (actual time=2,324.988..37,841.775 rows=1,101,438 loops=1)

  • Hash Cond: ("*SELECT* 1_1".project_id = projects.id)
7. 189.230 37,317.757 ↑ 1.1 1,101,438 1

Append (cost=1,062,773.75..7,984,612.22 rows=1,200,621 width=116) (actual time=2,322.722..37,317.757 rows=1,101,438 loops=1)

8. 212.265 23,378.628 ↑ 1.3 396,845 1

Result (cost=1,062,773.75..7,787,123.57 rows=496,660 width=116) (actual time=2,322.721..23,378.628 rows=396,845 loops=1)

9. 60.071 23,166.363 ↑ 1.3 396,845 1

Append (cost=1,062,773.75..7,780,915.32 rows=496,660 width=140) (actual time=2,322.718..23,166.363 rows=396,845 loops=1)

10. 97.785 4,691.396 ↑ 1.4 338,629 1

Subquery Scan on *SELECT* 1_1 (cost=1,062,773.75..7,714,854.75 rows=457,222 width=114) (actual time=2,322.717..4,691.396 rows=338,629 loops=1)

11. 2,245.888 4,593.611 ↑ 1.4 338,629 1

Hash Right Join (cost=1,062,773.75..7,707,996.42 rows=457,222 width=134) (actual time=2,322.716..4,593.611 rows=338,629 loops=1)

  • Hash Cond: ((staff_memberships.account_id = projects_1.account_id) AND (staff_memberships.user_id = plan_rows.user_id))
  • Join Filter: (generate_series.generate_series = ((generate_series_1.generate_series)::date))
  • Rows Removed by Join Filter: 14110732
12. 45.069 100.361 ↑ 17.8 32,266 1

HashAggregate (cost=537,214.32..545,839.32 rows=575,000 width=52) (actual time=73.246..100.361 rows=32,266 loops=1)

  • Group Key: generate_series_1.generate_series, staff_memberships.user_id, staff_memberships.account_id
13. 13.062 55.292 ↑ 134.2 32,422 1

Hash Join (cost=138.05..493,700.50 rows=4,351,382 width=21) (actual time=1.738..55.292 rows=32,422 loops=1)

  • Hash Cond: (vacations.staff_membership_id = staff_memberships.id)
  • Join Filter: ((generate_series_1.generate_series >= staff_memberships.joined_at) AND ((staff_memberships.archived_at IS NULL) OR (generate_series_1.generate_series <= staff_memberships.archived_at)))
  • Rows Removed by Join Filter: 1908
14. 16.191 40.570 ↑ 634.8 34,330 1

Nested Loop (cost=0.01..436,340.93 rows=21,792,000 width=17) (actual time=0.034..40.570 rows=34,330 loops=1)

15. 2.587 2.587 ↑ 1.0 21,792 1

Seq Scan on vacations (cost=0.00..500.92 rows=21,792 width=17) (actual time=0.017..2.587 rows=21,792 loops=1)

16. 21.792 21.792 ↑ 500.0 2 21,792

Function Scan on generate_series generate_series_1 (cost=0.01..10.01 rows=1,000 width=8) (actual time=0.001..0.001 rows=2 loops=21,792)

17. 0.861 1.660 ↑ 1.0 4,002 1

Hash (cost=88.02..88.02 rows=4,002 width=20) (actual time=1.660..1.660 rows=4,002 loops=1)

  • Buckets: 4096 Batches: 1 Memory Usage: 229kB
18. 0.799 0.799 ↑ 1.0 4,002 1

Seq Scan on staff_memberships (cost=0.00..88.02 rows=4,002 width=20) (actual time=0.008..0.799 rows=4,002 loops=1)

19. 141.117 2,247.362 ↑ 1.4 338,629 1

Hash (cost=518,701.10..518,701.10 rows=457,222 width=66) (actual time=2,247.362..2,247.362 rows=338,629 loops=1)

  • Buckets: 524288 Batches: 1 Memory Usage: 38679kB
20. 1,106.416 2,106.245 ↑ 1.4 338,629 1

Hash Anti Join (cost=463,568.36..518,701.10 rows=457,222 width=66) (actual time=782.545..2,106.245 rows=338,629 loops=1)

  • Hash Cond: ((projects_1.account_id = non_working_intervals_by_dates.account_id) AND (plan_rows.user_id = non_working_intervals_by_dates.user_id))
  • Join Filter: (generate_series.generate_series = non_working_intervals_by_dates.date)
  • Rows Removed by Join Filter: 11449923
21. 172.978 973.670 ↑ 1.7 346,275 1

Hash Right Join (cost=461,391.56..465,319.85 rows=577,750 width=66) (actual time=756.353..973.670 rows=346,275 loops=1)

  • Hash Cond: ((plan_rows_1.project_plan_id = project_plans.id) AND (((min(((plan_rows_1.uuid)::character varying)::text))::uuid) = plan_items.plan_row_uuid) AND (plan_rows_1.user_id = plan_rows.user_id))
  • Join Filter: (((plan_rows_1.epic_id = plan_rows.epic_id) OR (plan_rows.epic_id IS NULL)) AND ((generate_series.generate_series)::date >= (COALESCE(plan_roles.start_date, '1980-01-01'::date))) AND ((generate_series.generate_series)::date <= (COALESCE(lag((plan_roles.start_date - 1), 1) OVER (?), '3000-01-01'::date))))
  • Rows Removed by Join Filter: 3247
22. 85.698 198.996 ↓ 9.0 44,428 1

HashAggregate (cost=8,529.07..8,603.30 rows=4,949 width=48) (actual time=150.438..198.996 rows=44,428 loops=1)

  • Group Key: plan_rows_1.project_plan_id, plan_rows_1.epic_id, plan_rows_1.user_id, plan_roles.activity_id, COALESCE(plan_roles.start_date, '1980-01-01'::date), COALESCE(lag((plan_roles.start_date - 1), 1) OVER (?), '3000-01-01'::date)
23. 37.865 113.298 ↑ 1.0 44,581 1

WindowAgg (cost=6,077.00..7,080.12 rows=44,583 width=68) (actual time=68.485..113.298 rows=44,581 loops=1)

24. 29.796 75.433 ↑ 1.0 44,581 1

Sort (cost=6,077.00..6,188.46 rows=44,583 width=52) (actual time=68.473..75.433 rows=44,581 loops=1)

  • Sort Key: plan_roles.plan_row_uuid, plan_roles.start_date DESC NULLS LAST
  • Sort Method: quicksort Memory: 5023kB
25. 18.416 45.637 ↑ 1.0 44,581 1

Hash Join (cost=1,631.38..2,634.26 rows=44,583 width=52) (actual time=22.251..45.637 rows=44,581 loops=1)

  • Hash Cond: (plan_roles.plan_row_uuid = plan_rows_1.uuid)
26. 5.217 5.217 ↑ 1.0 44,581 1

Seq Scan on plan_roles (cost=0.00..885.83 rows=44,583 width=24) (actual time=0.010..5.217 rows=44,581 loops=1)

27. 12.377 22.004 ↑ 1.0 48,106 1

Hash (cost=1,030.06..1,030.06 rows=48,106 width=28) (actual time=22.004..22.004 rows=48,106 loops=1)

  • Buckets: 65536 Batches: 1 Memory Usage: 3180kB
28. 9.627 9.627 ↑ 1.0 48,106 1

Seq Scan on plan_rows plan_rows_1 (cost=0.00..1,030.06 rows=48,106 width=28) (actual time=0.006..9.627 rows=48,106 loops=1)

29. 156.032 601.696 ↑ 1.7 346,275 1

Hash (cost=442,751.87..442,751.87 rows=577,750 width=70) (actual time=601.696..601.696 rows=346,275 loops=1)

  • Buckets: 1048576 Batches: 1 Memory Usage: 45544kB
30. 94.599 445.664 ↑ 1.7 346,275 1

Nested Loop (cost=1,989.96..442,751.87 rows=577,750 width=70) (actual time=25.133..445.664 rows=346,275 loops=1)

31. 10.168 78.445 ↓ 1.2 27,262 1

Hash Join (cost=1,989.96..3,661.86 rows=23,110 width=70) (actual time=25.100..78.445 rows=27,262 loops=1)

  • Hash Cond: (project_plans.project_id = projects_1.id)
32. 13.665 65.995 ↓ 1.2 27,262 1

Hash Join (cost=1,761.19..3,372.38 rows=23,110 width=66) (actual time=22.801..65.995 rows=27,262 loops=1)

  • Hash Cond: (plan_items.plan_row_uuid = plan_rows.uuid)
33. 15.977 31.735 ↓ 1.1 29,797 1

Hash Join (cost=202.03..1,744.27 rows=26,265 width=54) (actual time=1.841..31.735 rows=29,797 loops=1)

  • Hash Cond: (plan_items.project_plan_id = project_plans.id)
34. 13.958 13.958 ↓ 1.0 55,664 1

Seq Scan on plan_items (cost=0.00..1,396.10 rows=55,634 width=46) (actual time=0.012..13.958 rows=55,664 loops=1)

  • Filter: (utilization > '0'::numeric)
  • Rows Removed by Filter: 264
35. 0.494 1.800 ↑ 1.0 2,851 1

Hash (cost=166.39..166.39 rows=2,851 width=8) (actual time=1.800..1.800 rows=2,851 loops=1)

  • Buckets: 4096 Batches: 1 Memory Usage: 144kB
36. 1.306 1.306 ↑ 1.0 2,851 1

Seq Scan on project_plans (cost=0.00..166.39 rows=2,851 width=8) (actual time=0.006..1.306 rows=2,851 loops=1)

  • Filter: active
  • Rows Removed by Filter: 3188
37. 11.217 20.595 ↓ 1.0 42,344 1

Hash (cost=1,030.06..1,030.06 rows=42,328 width=28) (actual time=20.595..20.595 rows=42,344 loops=1)

  • Buckets: 65536 Batches: 1 Memory Usage: 2816kB
38. 9.378 9.378 ↓ 1.0 42,344 1

Seq Scan on plan_rows (cost=0.00..1,030.06 rows=42,328 width=28) (actual time=0.017..9.378 rows=42,344 loops=1)

  • Filter: (user_id IS NOT NULL)
  • Rows Removed by Filter: 5762
39. 1.193 2.282 ↑ 1.0 5,812 1

Hash (cost=156.12..156.12 rows=5,812 width=8) (actual time=2.282..2.282 rows=5,812 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 292kB
40. 1.089 1.089 ↑ 1.0 5,812 1

Seq Scan on projects projects_1 (cost=0.00..156.12 rows=5,812 width=8) (actual time=0.016..1.089 rows=5,812 loops=1)

41. 272.620 272.620 ↑ 1.9 13 27,262

Function Scan on generate_series (cost=0.01..18.76 rows=25 width=8) (actual time=0.005..0.010 rows=13 loops=27,262)

  • Filter: (date_part('dow'::text, generate_series) = ANY ('{1,2,3,4,5}'::double precision[]))
  • Rows Removed by Filter: 5
42. 13.449 26.159 ↑ 1.0 58,975 1

Hash (cost=1,281.12..1,281.12 rows=59,712 width=12) (actual time=26.159..26.159 rows=58,975 loops=1)

  • Buckets: 65536 Batches: 1 Memory Usage: 3047kB
43. 12.710 12.710 ↑ 1.0 59,712 1

Seq Scan on non_working_intervals_by_dates (cost=0.00..1,281.12 rows=59,712 width=12) (actual time=0.014..12.710 rows=59,712 loops=1)

44. 53.817 18,414.896 ↓ 1.5 58,216 1

Hash Join (cost=1,059.11..63,182.89 rows=39,438 width=114) (actual time=6.822..18,414.896 rows=58,216 loops=1)

  • Hash Cond: (project_plans_1.project_id = project.id)
  • Join Filter: (NOT (SubPlan 1))
  • Rows Removed by Join Filter: 770
45. 21.916 132.141 ↑ 1.3 58,986 1

Nested Loop (cost=830.34..62,335.05 rows=78,875 width=58) (actual time=4.463..132.141 rows=58,986 loops=1)

46. 2.720 36.710 ↑ 1.2 2,535 1

Hash Join (cost=830.34..2,390.04 rows=3,155 width=58) (actual time=4.447..36.710 rows=2,535 loops=1)

  • Hash Cond: (plan_items_1.project_plan_id = project_plans_1.id)
47. 16.534 32.402 ↓ 1.2 7,876 1

Hash Join (cost=628.31..2,170.46 rows=6,682 width=54) (actual time=2.824..32.402 rows=7,876 loops=1)

  • Hash Cond: (plan_items_1.plan_row_uuid = plan_rows_2.uuid)
48. 13.093 13.093 ↓ 1.0 55,664 1

Seq Scan on plan_items plan_items_1 (cost=0.00..1,396.10 rows=55,634 width=46) (actual time=0.006..13.093 rows=55,664 loops=1)

  • Filter: (utilization > '0'::numeric)
  • Rows Removed by Filter: 264
49. 1.086 2.775 ↑ 1.0 5,762 1

Hash (cost=556.08..556.08 rows=5,778 width=24) (actual time=2.775..2.775 rows=5,762 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 366kB
50. 1.689 1.689 ↑ 1.0 5,762 1

Index Scan using index_plan_rows_on_user_id on plan_rows plan_rows_2 (cost=0.29..556.08 rows=5,778 width=24) (actual time=0.007..1.689 rows=5,762 loops=1)

  • Index Cond: (user_id IS NULL)
51. 0.455 1.588 ↑ 1.0 2,851 1

Hash (cost=166.39..166.39 rows=2,851 width=8) (actual time=1.588..1.588 rows=2,851 loops=1)

  • Buckets: 4096 Batches: 1 Memory Usage: 144kB
52. 1.133 1.133 ↑ 1.0 2,851 1

Seq Scan on project_plans project_plans_1 (cost=0.00..166.39 rows=2,851 width=8) (actual time=0.006..1.133 rows=2,851 loops=1)

  • Filter: active
  • Rows Removed by Filter: 3188
53. 73.515 73.515 ↑ 1.1 23 2,535

Function Scan on generate_series generate_series_2 (cost=0.01..18.76 rows=25 width=8) (actual time=0.008..0.029 rows=23 loops=2,535)

  • Filter: (date_part('dow'::text, generate_series) = ANY ('{1,2,3,4,5}'::double precision[]))
  • Rows Removed by Filter: 9
54. 1.027 2.264 ↑ 1.0 5,812 1

Hash (cost=156.12..156.12 rows=5,812 width=12) (actual time=2.264..2.264 rows=5,812 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 314kB
55. 1.237 1.237 ↑ 1.0 5,812 1

Seq Scan on projects project (cost=0.00..156.12 rows=5,812 width=12) (actual time=0.014..1.237 rows=5,812 loops=1)

56.          

SubPlan (for Hash Join)

57. 58.986 18,226.674 ↓ 0.0 0 58,986

Nested Loop (cost=0.69..44.76 rows=1 width=0) (actual time=0.309..0.309 rows=0 loops=58,986)

  • Join Filter: (non_working_intervals_by_dates_2.office_id = clients_3.office_id)
  • Rows Removed by Join Filter: 3
58. 117.972 117.972 ↑ 1.0 1 58,986

Index Scan using clients_pkey on clients clients_3 (cost=0.28..2.50 rows=1 width=4) (actual time=0.002..0.002 rows=1 loops=58,986)

  • Index Cond: (project.client_id = id)
59. 18,049.716 18,049.716 ↑ 4.0 3 58,986

Index Scan using non_working_intervals_by_dates_idx on non_working_intervals_by_dates non_working_intervals_by_dates_2 (cost=0.41..42.12 rows=12 width=4) (actual time=0.296..0.306 rows=3 loops=58,986)

  • Index Cond: ((project.account_id = account_id) AND (generate_series_2.generate_series = date))
60. 12,894.947 13,749.899 ↓ 1.0 704,593 1

Hash Right Join (cost=45,029.23..184,445.93 rows=703,961 width=116) (actual time=782.581..13,749.899 rows=704,593 loops=1)

  • Hash Cond: (plan_rows_3.user_id = time_logs.user_id)
  • Join Filter: ((time_logs.date >= (COALESCE(plan_roles_1.start_date, '1980-01-01'::date))) AND (time_logs.date <= (COALESCE(lag((plan_roles_1.start_date - 1), 1) OVER (?), '3000-01-01'::date))) AND (((plan_rows_3.epic_id = time_logs.epic_id) AND (plan_rows_3.project_plan_id = epics.project_plan_id)) OR ((plan_rows_3.epic_id IS NULL) AND (plan_rows_3.project_plan_id = active_plan.id))))
  • Rows Removed by Join Filter: 62978265
61. 105.620 207.969 ↓ 9.0 44,428 1

HashAggregate (cost=8,529.07..8,603.30 rows=4,949 width=48) (actual time=131.685..207.969 rows=44,428 loops=1)

  • Group Key: plan_rows_3.project_plan_id, plan_rows_3.epic_id, plan_rows_3.user_id, plan_roles_1.activity_id, COALESCE(plan_roles_1.start_date, '1980-01-01'::date), COALESCE(lag((plan_roles_1.start_date - 1), 1) OVER (?), '3000-01-01'::date)
62. 30.298 102.349 ↑ 1.0 44,581 1

WindowAgg (cost=6,077.00..7,080.12 rows=44,583 width=68) (actual time=66.040..102.349 rows=44,581 loops=1)

63. 27.296 72.051 ↑ 1.0 44,581 1

Sort (cost=6,077.00..6,188.46 rows=44,583 width=52) (actual time=66.029..72.051 rows=44,581 loops=1)

  • Sort Key: plan_roles_1.plan_row_uuid, plan_roles_1.start_date DESC NULLS LAST
  • Sort Method: quicksort Memory: 5023kB
64. 17.796 44.755 ↑ 1.0 44,581 1

Hash Join (cost=1,631.38..2,634.26 rows=44,583 width=52) (actual time=22.499..44.755 rows=44,581 loops=1)

  • Hash Cond: (plan_roles_1.plan_row_uuid = plan_rows_3.uuid)
65. 4.729 4.729 ↑ 1.0 44,581 1

Seq Scan on plan_roles plan_roles_1 (cost=0.00..885.83 rows=44,583 width=24) (actual time=0.008..4.729 rows=44,581 loops=1)

66. 12.387 22.230 ↑ 1.0 48,106 1

Hash (cost=1,030.06..1,030.06 rows=48,106 width=28) (actual time=22.230..22.230 rows=48,106 loops=1)

  • Buckets: 65536 Batches: 1 Memory Usage: 3180kB
67. 9.843 9.843 ↑ 1.0 48,106 1

Seq Scan on plan_rows plan_rows_3 (cost=0.00..1,030.06 rows=48,106 width=28) (actual time=0.007..9.843 rows=48,106 loops=1)

68. 215.920 646.983 ↑ 1.0 703,961 1

Hash (cost=27,700.65..27,700.65 rows=703,961 width=40) (actual time=646.983..646.983 rows=703,961 loops=1)

  • Buckets: 1048576 Batches: 1 Memory Usage: 61640kB
69. 272.541 431.063 ↑ 1.0 703,961 1

Hash Left Join (cost=1,826.58..27,700.65 rows=703,961 width=40) (actual time=21.225..431.063 rows=703,961 loops=1)

  • Hash Cond: (time_logs.epic_id = epics.id)
70. 137.499 137.499 ↑ 1.0 703,961 1

Seq Scan on time_logs (cost=0.00..16,194.61 rows=703,961 width=28) (actual time=0.044..137.499 rows=703,961 loops=1)

71. 6.991 21.023 ↑ 1.0 26,435 1

Hash (cost=1,496.14..1,496.14 rows=26,435 width=16) (actual time=21.023..21.023 rows=26,435 loops=1)

  • Buckets: 32768 Batches: 1 Memory Usage: 1424kB
72. 8.987 14.032 ↑ 1.0 26,435 1

Hash Left Join (cost=202.03..1,496.14 rows=26,435 width=16) (actual time=1.824..14.032 rows=26,435 loops=1)

  • Hash Cond: (epics.project_id = active_plan.project_id)
73. 3.251 3.251 ↑ 1.0 26,435 1

Seq Scan on epics (cost=0.00..619.35 rows=26,435 width=12) (actual time=0.006..3.251 rows=26,435 loops=1)

74. 0.600 1.794 ↑ 1.0 2,851 1

Hash (cost=166.39..166.39 rows=2,851 width=8) (actual time=1.794..1.794 rows=2,851 loops=1)

  • Buckets: 4096 Batches: 1 Memory Usage: 144kB
75. 1.194 1.194 ↑ 1.0 2,851 1

Seq Scan on project_plans active_plan (cost=0.00..166.39 rows=2,851 width=8) (actual time=0.007..1.194 rows=2,851 loops=1)

  • Filter: active
  • Rows Removed by Filter: 3188
76. 1.204 2.254 ↑ 1.0 5,812 1

Hash (cost=156.12..156.12 rows=5,812 width=8) (actual time=2.254..2.254 rows=5,812 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 292kB
77. 1.050 1.050 ↑ 1.0 5,812 1

Seq Scan on projects (cost=0.00..156.12 rows=5,812 width=8) (actual time=0.010..1.050 rows=5,812 loops=1)

78. 1.662 18.605 ↑ 1.0 4,221 1

Hash (cost=932.12..932.12 rows=4,249 width=40) (actual time=18.605..18.605 rows=4,221 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 370kB
79. 1.184 16.943 ↑ 1.0 4,221 1

Subquery Scan on sa (cost=847.14..932.12 rows=4,249 width=40) (actual time=14.247..16.943 rows=4,221 loops=1)

80. 1.116 15.759 ↑ 1.0 4,221 1

Unique (cost=847.14..889.63 rows=4,249 width=65) (actual time=14.244..15.759 rows=4,221 loops=1)

81. 4.092 14.643 ↑ 1.0 4,249 1

Sort (cost=847.14..857.76 rows=4,249 width=65) (actual time=14.243..14.643 rows=4,249 loops=1)

  • Sort Key: staff_memberships_1.account_id, staff_memberships_1.user_id, (COALESCE(staff_membership_activity_links.start_date, staff_memberships_1.joined_at)), (COALESCE(lag((staff_membership_activity_links.start_date - 1), 1) OVER (?), staff_memberships_1.archived_at, '3000-01-01'::date)) DESC
  • Sort Method: quicksort Memory: 790kB
82. 3.697 10.551 ↑ 1.0 4,249 1

WindowAgg (cost=484.85..591.08 rows=4,249 width=65) (actual time=6.394..10.551 rows=4,249 loops=1)

83. 2.743 6.854 ↑ 1.0 4,249 1

Sort (cost=484.85..495.47 rows=4,249 width=56) (actual time=6.384..6.854 rows=4,249 loops=1)

  • Sort Key: staff_membership_activity_links.staff_membership_id, staff_membership_activity_links.start_date DESC NULLS LAST
  • Sort Method: quicksort Memory: 790kB
84. 1.567 4.111 ↑ 1.0 4,249 1

Hash Join (cost=138.05..228.79 rows=4,249 width=56) (actual time=2.083..4.111 rows=4,249 loops=1)

  • Hash Cond: (staff_membership_activity_links.staff_membership_id = staff_memberships_1.id)
85. 0.498 0.498 ↑ 1.0 4,256 1

Seq Scan on staff_membership_activity_links (cost=0.00..79.56 rows=4,256 width=28) (actual time=0.010..0.498 rows=4,256 loops=1)

86. 1.070 2.046 ↑ 1.0 4,002 1

Hash (cost=88.02..88.02 rows=4,002 width=32) (actual time=2.046..2.046 rows=4,002 loops=1)

  • Buckets: 4096 Batches: 1 Memory Usage: 276kB
87. 0.976 0.976 ↑ 1.0 4,002 1

Seq Scan on staff_memberships staff_memberships_1 (cost=0.00..88.02 rows=4,002 width=32) (actual time=0.006..0.976 rows=4,002 loops=1)

88. 0.058 0.157 ↑ 1.0 354 1

Hash (cost=14.54..14.54 rows=354 width=9) (actual time=0.157..0.157 rows=354 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 24kB
89. 0.099 0.099 ↑ 1.0 354 1

Seq Scan on accounts accounts_1 (cost=0.00..14.54 rows=354 width=9) (actual time=0.004..0.099 rows=354 loops=1)

90. 21.277 448.418 ↑ 8.5 28,906 1

Subquery Scan on *SELECT* 2_1 (cost=424,372.25..513,596.17 rows=245,158 width=136) (actual time=142.288..448.418 rows=28,906 loops=1)

91. 255.223 427.141 ↑ 8.5 28,906 1

Hash Anti Join (cost=424,372.25..510,531.69 rows=245,158 width=143) (actual time=142.284..427.141 rows=28,906 loops=1)

  • Hash Cond: ((staff_memberships_2.account_id = non_working_intervals_by_dates_1.account_id) AND (staff_memberships_2.user_id = non_working_intervals_by_dates_1.user_id))
  • Join Filter: (generate_series_3.generate_series = non_working_intervals_by_dates_1.date)
  • Rows Removed by Join Filter: 1153172
92. 31.211 136.854 ↑ 9.5 29,394 1

Hash Join (cost=422,195.45..490,256.83 rows=280,181 width=64) (actual time=107.132..136.854 rows=29,394 loops=1)

  • Hash Cond: (staff_memberships_2.id = vacations_1.staff_membership_id)
  • Join Filter: ((generate_series_3.generate_series >= (COALESCE(staff_membership_activity_links_1.start_date, staff_memberships_2.joined_at))) AND (generate_series_3.generate_series <= (COALESCE(lag((staff_membership_activity_links_1.start_date - 1), 1) OVER (?), staff_memberships_2.archived_at, '3000-01-01'::date))))
  • Rows Removed by Join Filter: 10924
93. 1.871 18.687 ↑ 1.0 4,221 1

Unique (cost=836.52..879.01 rows=4,249 width=65) (actual time=16.052..18.687 rows=4,221 loops=1)

94. 3.745 16.816 ↑ 1.0 4,249 1

Sort (cost=836.52..847.14 rows=4,249 width=65) (actual time=16.051..16.816 rows=4,249 loops=1)

  • Sort Key: staff_memberships_2.account_id, staff_memberships_2.user_id, (COALESCE(staff_membership_activity_links_1.start_date, staff_memberships_2.joined_at)), (COALESCE(lag((staff_membership_activity_links_1.start_date - 1), 1) OVER (?), staff_memberships_2.archived_at, '3000-01-01'::date)) DESC
  • Sort Method: quicksort Memory: 592kB
95. 3.807 13.071 ↑ 1.0 4,249 1

WindowAgg (cost=484.85..580.45 rows=4,249 width=65) (actual time=8.860..13.071 rows=4,249 loops=1)

96. 3.511 9.264 ↑ 1.0 4,249 1

Sort (cost=484.85..495.47 rows=4,249 width=44) (actual time=8.845..9.264 rows=4,249 loops=1)

  • Sort Key: staff_membership_activity_links_1.staff_membership_id, staff_membership_activity_links_1.start_date DESC NULLS LAST
  • Sort Method: quicksort Memory: 561kB
97. 2.282 5.753 ↑ 1.0 4,249 1

Hash Join (cost=138.05..228.79 rows=4,249 width=44) (actual time=2.832..5.753 rows=4,249 loops=1)

  • Hash Cond: (staff_membership_activity_links_1.staff_membership_id = staff_memberships_2.id)
98. 0.670 0.670 ↑ 1.0 4,256 1

Seq Scan on staff_membership_activity_links staff_membership_activity_links_1 (cost=0.00..79.56 rows=4,256 width=20) (actual time=0.015..0.670 rows=4,256 loops=1)

99. 1.453 2.801 ↑ 1.0 4,002 1

Hash (cost=88.02..88.02 rows=4,002 width=24) (actual time=2.801..2.801 rows=4,002 loops=1)

  • Buckets: 4096 Batches: 1 Memory Usage: 245kB
100. 1.348 1.348 ↑ 1.0 4,002 1

Seq Scan on staff_memberships staff_memberships_2 (cost=0.00..88.02 rows=4,002 width=24) (actual time=0.010..1.348 rows=4,002 loops=1)

101. 14.226 86.956 ↑ 17.5 31,132 1

Hash (cost=414,548.93..414,548.93 rows=544,800 width=44) (actual time=86.956..86.956 rows=31,132 loops=1)

  • Buckets: 1048576 Batches: 1 Memory Usage: 10776kB
102. 25.608 72.730 ↑ 17.5 31,132 1

Nested Loop (cost=0.01..414,548.93 rows=544,800 width=44) (actual time=0.033..72.730 rows=31,132 loops=1)

103. 3.538 3.538 ↑ 1.0 21,792 1

Seq Scan on vacations vacations_1 (cost=0.00..500.92 rows=21,792 width=44) (actual time=0.015..3.538 rows=21,792 loops=1)

104. 43.584 43.584 ↑ 25.0 1 21,792

Function Scan on generate_series generate_series_3 (cost=0.01..18.76 rows=25 width=8) (actual time=0.002..0.002 rows=1 loops=21,792)

  • Filter: (date_part('dow'::text, generate_series) = ANY ('{1,2,3,4,5}'::double precision[]))
  • Rows Removed by Filter: 0
105. 18.062 35.064 ↑ 1.0 58,975 1

Hash (cost=1,281.12..1,281.12 rows=59,712 width=12) (actual time=35.064..35.064 rows=58,975 loops=1)

  • Buckets: 65536 Batches: 1 Memory Usage: 3047kB
106. 17.002 17.002 ↑ 1.0 59,712 1

Seq Scan on non_working_intervals_by_dates non_working_intervals_by_dates_1 (cost=0.00..1,281.12 rows=59,712 width=12) (actual time=0.014..17.002 rows=59,712 loops=1)

107. 0.026 0.145 ↑ 11.8 10 1

Hash (cost=17.20..17.20 rows=118 width=4) (actual time=0.145..0.145 rows=10 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
108. 0.119 0.119 ↑ 11.8 10 1

Seq Scan on accounts (cost=0.00..17.20 rows=118 width=4) (actual time=0.019..0.119 rows=10 loops=1)

  • Filter: ((suspended_at)::date >= CURRENT_DATE)
  • Rows Removed by Filter: 344
109. 98.962 406.694 ↑ 1.0 263,033 1

Hash (cost=23,315.28..23,315.28 rows=270,995 width=44) (actual time=406.694..406.694 rows=263,033 loops=1)

  • Buckets: 524288 Batches: 1 Memory Usage: 24593kB
110. 32.008 307.732 ↑ 1.0 263,033 1

Append (cost=109.73..23,315.28 rows=270,995 width=44) (actual time=2.373..307.732 rows=263,033 loops=1)

111. 0.111 18.725 ↓ 9.7 474 1

Subquery Scan on *SELECT* 1 (cost=109.73..1,614.47 rows=49 width=44) (actual time=2.372..18.725 rows=474 loops=1)

112. 0.266 18.614 ↓ 9.7 474 1

Nested Loop (cost=109.73..1,613.98 rows=49 width=612) (actual time=2.371..18.614 rows=474 loops=1)

113. 0.148 17.874 ↓ 9.7 474 1

Nested Loop (cost=109.59..1,606.06 rows=49 width=52) (actual time=2.360..17.874 rows=474 loops=1)

114. 0.067 1.766 ↓ 5.0 5 1

Nested Loop (cost=109.17..277.90 rows=1 width=32) (actual time=1.414..1.766 rows=5 loops=1)

  • Join Filter: (clients.brand_id = rate_cards.rateable_id)
  • Rows Removed by Join Filter: 570
115. 0.141 0.664 ↑ 1.0 115 1

WindowAgg (cost=108.61..111.49 rows=115 width=45) (actual time=0.517..0.664 rows=115 loops=1)

116. 0.056 0.523 ↑ 1.0 115 1

Sort (cost=108.61..108.90 rows=115 width=29) (actual time=0.509..0.523 rows=115 loops=1)

  • Sort Key: rate_cards.rateable_id, rate_cards.start_date DESC NULLS LAST
  • Sort Method: quicksort Memory: 33kB
117. 0.467 0.467 ↑ 1.0 115 1

Seq Scan on rate_cards (cost=0.00..104.68 rows=115 width=29) (actual time=0.114..0.467 rows=115 loops=1)

  • Filter: ((rateable_type)::text = 'Brand'::text)
  • Rows Removed by Filter: 4739
118. 0.153 1.035 ↑ 1.0 5 115

Materialize (cost=0.56..156.65 rows=5 width=8) (actual time=0.004..0.009 rows=5 loops=115)

119. 0.007 0.882 ↑ 1.0 5 1

Nested Loop (cost=0.56..156.63 rows=5 width=8) (actual time=0.410..0.882 rows=5 loops=1)

120. 0.010 0.855 ↑ 1.0 5 1

Nested Loop (cost=0.28..155.13 rows=5 width=8) (actual time=0.398..0.855 rows=5 loops=1)

121. 0.815 0.815 ↑ 1.0 5 1

Seq Scan on pricing_models (cost=0.00..142.62 rows=5 width=4) (actual time=0.374..0.815 rows=5 loops=1)

  • Filter: ((rates_type)::text = 'brand'::text)
  • Rows Removed by Filter: 5805
122. 0.030 0.030 ↑ 1.0 1 5

Index Scan using projects_pkey on projects projects_2 (cost=0.28..2.50 rows=1 width=8) (actual time=0.006..0.006 rows=1 loops=5)

  • Index Cond: (id = pricing_models.project_id)
123. 0.020 0.020 ↑ 1.0 1 5

Index Scan using clients_pkey on clients (cost=0.28..0.30 rows=1 width=8) (actual time=0.004..0.004 rows=1 loops=5)

  • Index Cond: (id = projects_2.client_id)
124. 15.960 15.960 ↓ 1.9 95 5

Index Scan using index_rates_on_activity_id_and_rate_card_id on rates (cost=0.42..1,327.66 rows=49 width=28) (actual time=0.794..3.192 rows=95 loops=5)

  • Index Cond: (rate_card_id = rate_cards.id)
125. 0.474 0.474 ↑ 1.0 1 474

Index Only Scan using brands_pkey on brands (cost=0.14..0.16 rows=1 width=4) (actual time=0.001..0.001 rows=1 loops=474)

  • Index Cond: (id = clients.brand_id)
  • Heap Fetches: 474
126. 14.740 81.401 ↓ 2.6 91,600 1

Subquery Scan on *SELECT* 2 (cost=583.00..5,479.99 rows=35,024 width=44) (actual time=12.821..81.401 rows=91,600 loops=1)

127. 41.192 66.661 ↓ 2.6 91,600 1

Hash Join (cost=583.00..5,129.75 rows=35,024 width=612) (actual time=12.820..66.661 rows=91,600 loops=1)

  • Hash Cond: (rates_1.rate_card_id = rate_cards_1.id)
128. 19.562 19.562 ↑ 1.0 174,437 1

Seq Scan on rates rates_1 (cost=0.00..3,542.37 rows=174,437 width=28) (actual time=0.015..19.562 rows=174,437 loops=1)

129. 0.208 5.907 ↑ 1.1 657 1

Hash (cost=574.00..574.00 rows=720 width=24) (actual time=5.907..5.907 rows=657 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 47kB
130. 0.231 5.699 ↑ 1.1 657 1

Hash Join (cost=378.98..574.00 rows=720 width=24) (actual time=3.558..5.699 rows=657 loops=1)

  • Hash Cond: (clients_1.office_id = offices.id)
131. 0.210 3.403 ↑ 1.0 623 1

Hash Join (cost=214.02..399.80 rows=623 width=8) (actual time=1.474..3.403 rows=623 loops=1)

  • Hash Cond: (projects_3.client_id = clients_1.id)
132. 1.006 2.587 ↑ 1.0 623 1

Hash Join (cost=150.41..334.56 rows=623 width=8) (actual time=0.857..2.587 rows=623 loops=1)

  • Hash Cond: (projects_3.id = pricing_models_1.project_id)
133. 0.788 0.788 ↑ 1.0 5,812 1

Seq Scan on projects projects_3 (cost=0.00..156.12 rows=5,812 width=8) (actual time=0.046..0.788 rows=5,812 loops=1)

134. 0.098 0.793 ↑ 1.0 623 1

Hash (cost=142.62..142.62 rows=623 width=4) (actual time=0.793..0.793 rows=623 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 30kB
135. 0.695 0.695 ↑ 1.0 623 1

Seq Scan on pricing_models pricing_models_1 (cost=0.00..142.62 rows=623 width=4) (actual time=0.016..0.695 rows=623 loops=1)

  • Filter: ((rates_type)::text = 'office'::text)
  • Rows Removed by Filter: 5187
136. 0.292 0.606 ↑ 1.0 1,849 1

Hash (cost=40.49..40.49 rows=1,849 width=8) (actual time=0.606..0.606 rows=1,849 loops=1)

  • Buckets: 2048 Batches: 1 Memory Usage: 89kB
137. 0.314 0.314 ↑ 1.0 1,849 1

Seq Scan on clients clients_1 (cost=0.00..40.49 rows=1,849 width=8) (actual time=0.006..0.314 rows=1,849 loops=1)

138. 0.132 2.065 ↑ 1.1 450 1

Hash (cost=158.85..158.85 rows=489 width=28) (actual time=2.065..2.065 rows=450 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 35kB
139. 0.138 1.933 ↑ 1.1 450 1

Hash Join (cost=140.44..158.85 rows=489 width=28) (actual time=1.389..1.933 rows=450 loops=1)

  • Hash Cond: (rate_cards_1.rateable_id = offices.id)
140. 0.394 1.592 ↑ 1.0 489 1

WindowAgg (cost=126.52..138.74 rows=489 width=45) (actual time=1.165..1.592 rows=489 loops=1)

141. 0.284 1.198 ↑ 1.0 489 1

Sort (cost=126.52..127.74 rows=489 width=29) (actual time=1.157..1.198 rows=489 loops=1)

  • Sort Key: rate_cards_1.rateable_id, rate_cards_1.start_date DESC NULLS LAST
  • Sort Method: quicksort Memory: 63kB
142. 0.914 0.914 ↑ 1.0 489 1

Seq Scan on rate_cards rate_cards_1 (cost=0.00..104.68 rows=489 width=29) (actual time=0.175..0.914 rows=489 loops=1)

  • Filter: ((rateable_type)::text = 'Office'::text)
  • Rows Removed by Filter: 4365
143. 0.110 0.203 ↑ 1.0 441 1

Hash (cost=8.41..8.41 rows=441 width=4) (actual time=0.203..0.203 rows=441 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 24kB
144. 0.093 0.093 ↑ 1.0 441 1

Seq Scan on offices (cost=0.00..8.41 rows=441 width=4) (actual time=0.008..0.093 rows=441 loops=1)

145. 14.868 87.607 ↑ 2.2 94,593 1

Subquery Scan on *SELECT* 3 (cost=840.78..9,338.49 rows=204,158 width=44) (actual time=13.270..87.607 rows=94,593 loops=1)

146. 40.990 72.739 ↑ 2.2 94,593 1

Hash Join (cost=840.78..7,296.91 rows=204,158 width=612) (actual time=13.268..72.739 rows=94,593 loops=1)

  • Hash Cond: (rates_2.rate_card_id = rate_cards_2.id)
147. 18.528 18.528 ↑ 1.0 174,437 1

Seq Scan on rates rates_2 (cost=0.00..3,542.37 rows=174,437 width=28) (actual time=0.010..18.528 rows=174,437 loops=1)

148. 1.268 13.221 ↑ 1.0 4,004 1

Hash (cost=788.31..788.31 rows=4,197 width=24) (actual time=13.221..13.221 rows=4,004 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 299kB
149. 1.419 11.953 ↑ 1.0 4,004 1

Hash Join (cost=586.95..788.31 rows=4,197 width=24) (actual time=7.827..11.953 rows=4,004 loops=1)

  • Hash Cond: (projects_4.client_id = clients_2.id)
150. 1.441 5.578 ↑ 1.0 3,620 1

Hash Join (cost=228.77..380.91 rows=3,620 width=8) (actual time=2.864..5.578 rows=3,620 loops=1)

  • Hash Cond: (pricing_models_2.project_id = projects_4.id)
151. 1.333 1.333 ↑ 1.0 3,621 1

Seq Scan on pricing_models pricing_models_2 (cost=0.00..142.62 rows=3,621 width=4) (actual time=0.008..1.333 rows=3,621 loops=1)

  • Filter: ((rates_type)::text = 'client'::text)
  • Rows Removed by Filter: 2189
152. 1.234 2.804 ↑ 1.0 5,812 1

Hash (cost=156.12..156.12 rows=5,812 width=8) (actual time=2.803..2.804 rows=5,812 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 292kB
153. 1.570 1.570 ↑ 1.0 5,812 1

Seq Scan on projects projects_4 (cost=0.00..156.12 rows=5,812 width=8) (actual time=0.006..1.570 rows=5,812 loops=1)

154. 0.416 4.956 ↑ 1.0 1,820 1

Hash (cost=335.42..335.42 rows=1,821 width=28) (actual time=4.956..4.956 rows=1,820 loops=1)

  • Buckets: 2048 Batches: 1 Memory Usage: 123kB
155. 0.446 4.540 ↑ 1.0 1,820 1

Hash Join (cost=266.89..335.42 rows=1,821 width=28) (actual time=2.813..4.540 rows=1,820 loops=1)

  • Hash Cond: (rate_cards_2.rateable_id = clients_2.id)
156. 1.173 3.275 ↑ 1.0 1,821 1

WindowAgg (cost=203.29..248.81 rows=1,821 width=45) (actual time=1.985..3.275 rows=1,821 loops=1)

157. 0.993 2.102 ↑ 1.0 1,821 1

Sort (cost=203.29..207.84 rows=1,821 width=29) (actual time=1.978..2.102 rows=1,821 loops=1)

  • Sort Key: rate_cards_2.rateable_id, rate_cards_2.start_date DESC NULLS LAST
  • Sort Method: quicksort Memory: 191kB
158. 1.109 1.109 ↑ 1.0 1,821 1

Seq Scan on rate_cards rate_cards_2 (cost=0.00..104.68 rows=1,821 width=29) (actual time=0.009..1.109 rows=1,821 loops=1)

  • Filter: ((rateable_type)::text = 'Client'::text)
  • Rows Removed by Filter: 3033
159. 0.437 0.819 ↑ 1.0 1,849 1

Hash (cost=40.49..40.49 rows=1,849 width=4) (actual time=0.819..0.819 rows=1,849 loops=1)

  • Buckets: 2048 Batches: 1 Memory Usage: 82kB
160. 0.382 0.382 ↑ 1.0 1,849 1

Seq Scan on clients clients_2 (cost=0.00..40.49 rows=1,849 width=4) (actual time=0.007..0.382 rows=1,849 loops=1)

161. 13.454 87.991 ↓ 2.4 76,366 1

Subquery Scan on *SELECT* 4 (cost=695.56..5,527.35 rows=31,764 width=44) (actual time=9.526..87.991 rows=76,366 loops=1)

162. 45.625 74.537 ↓ 2.4 76,366 1

Hash Join (cost=695.56..5,209.71 rows=31,764 width=612) (actual time=9.525..74.537 rows=76,366 loops=1)

  • Hash Cond: (rates_3.rate_card_id = rate_cards_3.id)
163. 19.411 19.411 ↑ 1.0 174,437 1

Seq Scan on rates rates_3 (cost=0.00..3,542.37 rows=174,437 width=28) (actual time=0.010..19.411 rows=174,437 loops=1)

164. 0.507 9.501 ↓ 2.4 1,591 1

Hash (cost=687.40..687.40 rows=653 width=24) (actual time=9.501..9.501 rows=1,591 loops=1)

  • Buckets: 2048 (originally 1024) Batches: 1 (originally 1) Memory Usage: 110kB
165. 1.117 8.994 ↓ 2.4 1,591 1

Hash Join (cost=502.95..687.40 rows=653 width=24) (actual time=7.179..8.994 rows=1,591 loops=1)

  • Hash Cond: (projects_5.id = pricing_models_3.project_id)
166. 0.712 0.712 ↑ 1.0 5,812 1

Seq Scan on projects projects_5 (cost=0.00..156.12 rows=5,812 width=4) (actual time=0.006..0.712 rows=5,812 loops=1)

167. 0.494 7.165 ↓ 2.4 1,591 1

Hash (cost=494.79..494.79 rows=653 width=24) (actual time=7.165..7.165 rows=1,591 loops=1)

  • Buckets: 2048 (originally 1024) Batches: 1 (originally 1) Memory Usage: 110kB
168. 0.671 6.671 ↓ 2.4 1,591 1

Hash Join (cost=403.40..494.79 rows=653 width=24) (actual time=3.501..6.671 rows=1,591 loops=1)

  • Hash Cond: (rate_cards_3.rateable_id = pricing_models_3.id)
169. 2.272 4.584 ↑ 1.0 2,429 1

WindowAgg (cost=241.26..301.98 rows=2,429 width=45) (actual time=2.081..4.584 rows=2,429 loops=1)

170. 1.168 2.312 ↑ 1.0 2,429 1

Sort (cost=241.26..247.33 rows=2,429 width=29) (actual time=2.073..2.312 rows=2,429 loops=1)

  • Sort Key: rate_cards_3.rateable_id, rate_cards_3.start_date DESC NULLS LAST
  • Sort Method: quicksort Memory: 286kB
171. 1.144 1.144 ↑ 1.0 2,429 1

Seq Scan on rate_cards rate_cards_3 (cost=0.00..104.68 rows=2,429 width=29) (actual time=0.009..1.144 rows=2,429 loops=1)

  • Filter: ((rateable_type)::text = 'PricingModel'::text)
  • Rows Removed by Filter: 2425
172. 0.313 1.416 ↑ 1.0 1,561 1

Hash (cost=142.62..142.62 rows=1,561 width=8) (actual time=1.416..1.416 rows=1,561 loops=1)

  • Buckets: 2048 Batches: 1 Memory Usage: 77kB
173. 1.103 1.103 ↑ 1.0 1,561 1

Seq Scan on pricing_models pricing_models_3 (cost=0.00..142.62 rows=1,561 width=8) (actual time=0.010..1.103 rows=1,561 loops=1)

  • Filter: ((rates_type)::text = 'custom'::text)
  • Rows Removed by Filter: 4249
Planning time : 7.223 ms
Execution time : 94,088.256 ms