explain.depesz.com

PostgreSQL's explain analyze made readable

Result: zDNV

Settings
# exclusive inclusive rows x rows loops node
1. 0.000 0.000 ↓ 0.0

Merge Left Join (cost=2,698,442.96..2,726,341.83 rows=22,581 width=188) (actual rows= loops=)

  • Merge 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)))
2. 0.000 0.000 ↓ 0.0

Sort (cost=2,643,222.55..2,643,279.00 rows=22,581 width=136) (actual rows= loops=)

  • Sort Key: projects.id, (COALESCE(""*SELECT* 1_1"".activity_id, sa.activity_id))
3. 0.000 0.000 ↓ 0.0

Hash Join (cost=1,842,729.28..2,641,589.62 rows=22,581 width=136) (actual rows= loops=)

  • Hash Cond: (projects.account_id = accounts.id)
4. 0.000 0.000 ↓ 0.0

Append (cost=1,842,710.61..2,640,713.57 rows=67,743 width=136) (actual rows= loops=)

5. 0.000 0.000 ↓ 0.0

Hash Join (cost=1,842,710.61..2,203,655.11 rows=186 width=108) (actual rows= loops=)

  • Hash Cond: ((projects.account_id = accounts_1.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) AND ((((""*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)))
6. 0.000 0.000 ↓ 0.0

Hash Join (cost=1,842,525.91..2,161,365.64 rows=1,199,950 width=120) (actual rows= loops=)

  • Hash Cond: ("*SELECT* 1_1".project_id = projects.id)
7. 0.000 0.000 ↓ 0.0

Append (cost=1,842,297.14..2,145,985.21 rows=1,199,950 width=116) (actual rows= loops=)

8. 0.000 0.000 ↓ 0.0

Result (cost=1,842,297.14..1,938,703.25 rows=495,989 width=116) (actual rows= loops=)

9. 0.000 0.000 ↓ 0.0

Append (cost=1,842,297.14..1,932,503.38 rows=495,989 width=140) (actual rows= loops=)

10. 0.000 0.000 ↓ 0.0

Subquery Scan on *SELECT* 1_1 (cost=1,842,297.14..1,867,543.08 rows=457,239 width=114) (actual rows= loops=)

11. 0.000 0.000 ↓ 0.0

Merge Left Join (cost=1,842,297.14..1,860,684.50 rows=457,239 width=134) (actual rows= loops=)

  • Merge Cond: ((projects_1.account_id = summary_vacations_by_dates.account_id) AND (generate_series.generate_series = summary_vacations_by_dates.date) AND (plan_rows.user_id = summary_vacations_by_dates.user_id))
12. 0.000 0.000 ↓ 0.0

Merge Anti Join (cost=548,847.35..555,445.96 rows=457,239 width=66) (actual rows= loops=)

  • Merge Cond: ((projects_1.account_id = non_working_intervals_by_dates.account_id) AND (generate_series.generate_series = non_working_intervals_by_dates.date) AND (plan_rows.user_id = non_working_intervals_by_dates.user_id))
13. 0.000 0.000 ↓ 0.0

Sort (cost=542,829.36..544,277.29 rows=579,175 width=66) (actual rows= loops=)

  • Sort Key: projects_1.account_id, generate_series.generate_series, plan_rows.user_id
14. 0.000 0.000 ↓ 0.0

Merge Left Join (cost=12,929.64..463,633.77 rows=579,175 width=66) (actual rows= loops=)

  • Merge Cond: (plan_items.plan_row_uuid = pa.plan_row_uuid)
  • Join Filter: (((pa.epic_id = plan_rows.epic_id) OR (plan_rows.epic_id IS NULL)) AND (pa.project_plan_id = project_plans.id) AND (pa.user_id = plan_rows.user_id) AND ((generate_series.generate_series)::date >= pa.start_date) AND ((generate_series.generate_series)::date <= pa.end_date))
15. 0.000 0.000 ↓ 0.0

Nested Loop (cost=3,971.09..448,257.03 rows=579,175 width=70) (actual rows= loops=)

16. 0.000 0.000 ↓ 0.0

Merge Join (cost=3,971.09..8,084.02 rows=23,167 width=70) (actual rows= loops=)

  • Merge Cond: (plan_rows.uuid = plan_items.plan_row_uuid)
17. 0.000 0.000 ↓ 0.0

Index Scan using plan_rows_uuid_key on plan_rows (cost=0.29..3,663.60 rows=42,428 width=28) (actual rows= loops=)

  • Filter: (user_id IS NOT NULL)
18. 0.000 0.000 ↓ 0.0

Sort (cost=3,970.18..4,035.85 rows=26,267 width=58) (actual rows= loops=)

  • Sort Key: plan_items.plan_row_uuid
19. 0.000 0.000 ↓ 0.0

Hash Join (cost=430.80..2,042.06 rows=26,267 width=58) (actual rows= loops=)

  • Hash Cond: (project_plans.project_id = projects_1.id)
20. 0.000 0.000 ↓ 0.0

Hash Join (cost=202.03..1,744.28 rows=26,267 width=54) (actual rows= loops=)

  • Hash Cond: (plan_items.project_plan_id = project_plans.id)
21. 0.000 0.000 ↓ 0.0

Seq Scan on plan_items (cost=0.00..1,396.10 rows=55,639 width=46) (actual rows= loops=)

  • Filter: (utilization > '0'::numeric)
22. 0.000 0.000 ↓ 0.0

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

23. 0.000 0.000 ↓ 0.0

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

  • Filter: active
24. 0.000 0.000 ↓ 0.0

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

25. 0.000 0.000 ↓ 0.0

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

26. 0.000 0.000 ↓ 0.0

Function Scan on generate_series (cost=0.01..18.76 rows=25 width=8) (actual rows= loops=)

  • Filter: (date_part('dow'::text, generate_series) = ANY ('{1,2,3,4,5}'::double precision[]))
27. 0.000 0.000 ↓ 0.0

Sort (cost=8,958.54..8,970.97 rows=4,971 width=36) (actual rows= loops=)

  • Sort Key: pa.plan_row_uuid
28. 0.000 0.000 ↓ 0.0

Subquery Scan on pa (cost=8,529.07..8,653.34 rows=4,971 width=36) (actual rows= loops=)

29. 0.000 0.000 ↓ 0.0

HashAggregate (cost=8,529.07..8,603.63 rows=4,971 width=48) (actual rows= loops=)

  • 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)
30. 0.000 0.000 ↓ 0.0

WindowAgg (cost=6,077.00..7,080.12 rows=44,583 width=68) (actual rows= loops=)

31. 0.000 0.000 ↓ 0.0

Sort (cost=6,077.00..6,188.46 rows=44,583 width=52) (actual rows= loops=)

  • Sort Key: plan_roles.plan_row_uuid, plan_roles.start_date DESC NULLS LAST
32. 0.000 0.000 ↓ 0.0

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

  • Hash Cond: (plan_roles.plan_row_uuid = plan_rows_1.uuid)
33. 0.000 0.000 ↓ 0.0

Seq Scan on plan_roles (cost=0.00..885.83 rows=44,583 width=24) (actual rows= loops=)

34. 0.000 0.000 ↓ 0.0

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

35. 0.000 0.000 ↓ 0.0

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

36. 0.000 0.000 ↓ 0.0

Sort (cost=6,017.99..6,167.27 rows=59,712 width=12) (actual rows= loops=)

  • Sort Key: non_working_intervals_by_dates.account_id, non_working_intervals_by_dates.date, non_working_intervals_by_dates.user_id
37. 0.000 0.000 ↓ 0.0

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

38. 0.000 0.000 ↓ 0.0

Materialize (cost=1,293,449.79..1,296,324.79 rows=575,000 width=44) (actual rows= loops=)

39. 0.000 0.000 ↓ 0.0

Sort (cost=1,293,449.79..1,294,887.29 rows=575,000 width=44) (actual rows= loops=)

  • Sort Key: summary_vacations_by_dates.account_id, summary_vacations_by_dates.date, summary_vacations_by_dates.user_id
40. 0.000 0.000 ↓ 0.0

Subquery Scan on summary_vacations_by_dates (cost=1,151,985.56..1,220,752.83 rows=575,000 width=44) (actual rows= loops=)

41. 0.000 0.000 ↓ 0.0

GroupAggregate (cost=1,151,985.56..1,215,002.83 rows=575,000 width=52) (actual rows= loops=)

  • Group Key: generate_series_1.generate_series, staff_memberships.user_id, staff_memberships.account_id
42. 0.000 0.000 ↓ 0.0

Sort (cost=1,151,985.56..1,162,864.01 rows=4,351,382 width=21) (actual rows= loops=)

  • Sort Key: generate_series_1.generate_series, staff_memberships.user_id, staff_memberships.account_id
43. 0.000 0.000 ↓ 0.0

Hash Join (cost=138.05..493,700.50 rows=4,351,382 width=21) (actual rows= loops=)

  • 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)))
44. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.01..436,340.93 rows=21,792,000 width=17) (actual rows= loops=)

45. 0.000 0.000 ↓ 0.0

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

46. 0.000 0.000 ↓ 0.0

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

47. 0.000 0.000 ↓ 0.0

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

48. 0.000 0.000 ↓ 0.0

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

49. 0.000 0.000 ↓ 0.0

Hash Join (cost=1,215.85..62,092.86 rows=38,750 width=114) (actual rows= loops=)

  • Hash Cond: (project_plans_1.project_id = project.id)
  • Join Filter: (NOT (SubPlan 1))
50. 0.000 0.000 ↓ 0.0

Nested Loop (cost=987.08..61,446.50 rows=77,500 width=58) (actual rows= loops=)

51. 0.000 0.000 ↓ 0.0

Hash Join (cost=987.08..2,546.49 rows=3,100 width=58) (actual rows= loops=)

  • Hash Cond: (plan_items_1.project_plan_id = project_plans_1.id)
52. 0.000 0.000 ↓ 0.0

Hash Join (cost=785.05..2,327.21 rows=6,567 width=54) (actual rows= loops=)

  • Hash Cond: (plan_items_1.plan_row_uuid = plan_rows_2.uuid)
53. 0.000 0.000 ↓ 0.0

Seq Scan on plan_items plan_items_1 (cost=0.00..1,396.10 rows=55,639 width=46) (actual rows= loops=)

  • Filter: (utilization > '0'::numeric)
54. 0.000 0.000 ↓ 0.0

Hash (cost=714.07..714.07 rows=5,678 width=24) (actual rows= loops=)

55. 0.000 0.000 ↓ 0.0

Bitmap Heap Scan on plan_rows plan_rows_2 (cost=108.29..714.07 rows=5,678 width=24) (actual rows= loops=)

  • Recheck Cond: (user_id IS NULL)
56. 0.000 0.000 ↓ 0.0

Bitmap Index Scan on index_plan_rows_on_user_id (cost=0.00..106.88 rows=5,678 width=0) (actual rows= loops=)

  • Index Cond: (user_id IS NULL)
57. 0.000 0.000 ↓ 0.0

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

58. 0.000 0.000 ↓ 0.0

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

  • Filter: active
59. 0.000 0.000 ↓ 0.0

Function Scan on generate_series generate_series_2 (cost=0.01..18.76 rows=25 width=8) (actual rows= loops=)

  • Filter: (date_part('dow'::text, generate_series) = ANY ('{1,2,3,4,5}'::double precision[]))
60. 0.000 0.000 ↓ 0.0

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

61. 0.000 0.000 ↓ 0.0

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

62.          

SubPlan (for Hash Join)

63. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.69..16.74 rows=1 width=0) (actual rows= loops=)

64. 0.000 0.000 ↓ 0.0

Index Scan using clients_pkey on clients clients_3 (cost=0.28..8.29 rows=1 width=4) (actual rows= loops=)

  • Index Cond: (project.client_id = id)
65. 0.000 0.000 ↓ 0.0

Index Only Scan using non_working_intervals_by_office_id_idx on non_working_intervals_by_dates non_working_intervals_by_dates_2 (cost=0.41..8.44 rows=1 width=4) (actual rows= loops=)

  • Index Cond: ((account_id = project.account_id) AND (office_id = clients_3.office_id) AND (date = generate_series_2.generate_series))
66. 0.000 0.000 ↓ 0.0

Hash Right Join (cost=50,529.23..194,242.61 rows=703,961 width=116) (actual rows= loops=)

  • Hash Cond: (pa_1.user_id = time_logs.user_id)
  • Join Filter: ((time_logs.date >= pa_1.start_date) AND (time_logs.date <= pa_1.end_date) AND (((pa_1.epic_id = time_logs.epic_id) AND (pa_1.project_plan_id = epics.project_plan_id)) OR ((pa_1.epic_id IS NULL) AND (pa_1.project_plan_id = active_plan.id))))
67. 0.000 0.000 ↓ 0.0

Subquery Scan on pa_1 (cost=8,529.07..8,653.34 rows=4,971 width=40) (actual rows= loops=)

68. 0.000 0.000 ↓ 0.0

HashAggregate (cost=8,529.07..8,603.63 rows=4,971 width=48) (actual rows= loops=)

  • 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)
69. 0.000 0.000 ↓ 0.0

WindowAgg (cost=6,077.00..7,080.12 rows=44,583 width=68) (actual rows= loops=)

70. 0.000 0.000 ↓ 0.0

Sort (cost=6,077.00..6,188.46 rows=44,583 width=52) (actual rows= loops=)

  • Sort Key: plan_roles_1.plan_row_uuid, plan_roles_1.start_date DESC NULLS LAST
71. 0.000 0.000 ↓ 0.0

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

  • Hash Cond: (plan_roles_1.plan_row_uuid = plan_rows_3.uuid)
72. 0.000 0.000 ↓ 0.0

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

73. 0.000 0.000 ↓ 0.0

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

74. 0.000 0.000 ↓ 0.0

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

75. 0.000 0.000 ↓ 0.0

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

76. 0.000 0.000 ↓ 0.0

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

  • Hash Cond: (time_logs.epic_id = epics.id)
77. 0.000 0.000 ↓ 0.0

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

78. 0.000 0.000 ↓ 0.0

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

79. 0.000 0.000 ↓ 0.0

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

  • Hash Cond: (epics.project_id = active_plan.project_id)
80. 0.000 0.000 ↓ 0.0

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

81. 0.000 0.000 ↓ 0.0

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

82. 0.000 0.000 ↓ 0.0

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

  • Filter: active
83. 0.000 0.000 ↓ 0.0

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

84. 0.000 0.000 ↓ 0.0

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

85. 0.000 0.000 ↓ 0.0

Hash (cost=121.39..121.39 rows=4,221 width=49) (actual rows= loops=)

86. 0.000 0.000 ↓ 0.0

Hash Join (cost=18.96..121.39 rows=4,221 width=49) (actual rows= loops=)

  • Hash Cond: (sa.account_id = accounts_1.id)
87. 0.000 0.000 ↓ 0.0

Seq Scan on staff_activities_with_dates sa (cost=0.00..91.21 rows=4,221 width=40) (actual rows= loops=)

88. 0.000 0.000 ↓ 0.0

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

89. 0.000 0.000 ↓ 0.0

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

90. 0.000 0.000 ↓ 0.0

Subquery Scan on *SELECT* 2_1 (cost=2,320.78..436,717.88 rows=67,557 width=136) (actual rows= loops=)

91. 0.000 0.000 ↓ 0.0

Hash Anti Join (cost=2,320.78..435,873.42 rows=67,557 width=143) (actual rows= loops=)

  • Hash Cond: ((sa_1.account_id = non_working_intervals_by_dates_1.account_id) AND (sa_1.user_id = non_working_intervals_by_dates_1.user_id))
  • Join Filter: (generate_series_3.generate_series = non_working_intervals_by_dates_1.date)
92. 0.000 0.000 ↓ 0.0

Hash Join (cost=143.98..429,184.39 rows=77,078 width=64) (actual rows= loops=)

  • Hash Cond: (vacations_1.staff_membership_id = sa_1.staff_membership_id)
  • Join Filter: ((generate_series_3.generate_series >= sa_1.start_date) AND (generate_series_3.generate_series <= sa_1.end_date))
93. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.01..414,548.93 rows=544,800 width=44) (actual rows= loops=)

94. 0.000 0.000 ↓ 0.0

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

95. 0.000 0.000 ↓ 0.0

Function Scan on generate_series generate_series_3 (cost=0.01..18.76 rows=25 width=8) (actual rows= loops=)

  • Filter: (date_part('dow'::text, generate_series) = ANY ('{1,2,3,4,5}'::double precision[]))
96. 0.000 0.000 ↓ 0.0

Hash (cost=91.21..91.21 rows=4,221 width=36) (actual rows= loops=)

97. 0.000 0.000 ↓ 0.0

Seq Scan on staff_activities_with_dates sa_1 (cost=0.00..91.21 rows=4,221 width=36) (actual rows= loops=)

98. 0.000 0.000 ↓ 0.0

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

99. 0.000 0.000 ↓ 0.0

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 rows= loops=)

100. 0.000 0.000 ↓ 0.0

Hash (cost=17.20..17.20 rows=118 width=4) (actual rows= loops=)

101. 0.000 0.000 ↓ 0.0

Seq Scan on accounts (cost=0.00..17.20 rows=118 width=4) (actual rows= loops=)

  • Filter: ((suspended_at)::date >= CURRENT_DATE)
102. 0.000 0.000 ↓ 0.0

Materialize (cost=55,220.42..56,583.76 rows=272,669 width=44) (actual rows= loops=)

103. 0.000 0.000 ↓ 0.0

Sort (cost=55,220.42..55,902.09 rows=272,669 width=44) (actual rows= loops=)

  • Sort Key: ""*SELECT* 1"".project_id, ""*SELECT* 1"".activity_id
104. 0.000 0.000 ↓ 0.0

Append (cost=300.88..22,213.28 rows=272,669 width=44) (actual rows= loops=)

105. 0.000 0.000 ↓ 0.0

Subquery Scan on *SELECT* 1 (cost=300.88..470.62 rows=49 width=44) (actual rows= loops=)

106. 0.000 0.000 ↓ 0.0

Merge Join (cost=300.88..470.13 rows=49 width=612) (actual rows= loops=)

  • Merge Cond: (clients.brand_id = brands.id)
107. 0.000 0.000 ↓ 0.0

Nested Loop (cost=294.80..1,671.71 rows=49 width=52) (actual rows= loops=)

108. 0.000 0.000 ↓ 0.0

Merge Join (cost=294.38..294.67 rows=1 width=32) (actual rows= loops=)

  • Merge Cond: (rate_cards.rateable_id = clients.brand_id)
109. 0.000 0.000 ↓ 0.0

WindowAgg (cost=108.61..111.49 rows=115 width=45) (actual rows= loops=)

110. 0.000 0.000 ↓ 0.0

Sort (cost=108.61..108.90 rows=115 width=29) (actual rows= loops=)

  • Sort Key: rate_cards.rateable_id, rate_cards.start_date DESC NULLS LAST
111. 0.000 0.000 ↓ 0.0

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

  • Filter: ((rateable_type)::text = 'Brand'::text)
112. 0.000 0.000 ↓ 0.0

Sort (cost=185.76..185.78 rows=5 width=8) (actual rows= loops=)

  • Sort Key: clients.brand_id
113. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.56..185.71 rows=5 width=8) (actual rows= loops=)

114. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.28..184.13 rows=5 width=8) (actual rows= loops=)

115. 0.000 0.000 ↓ 0.0

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

  • Filter: ((rates_type)::text = 'brand'::text)
116. 0.000 0.000 ↓ 0.0

Index Scan using projects_pkey on projects projects_2 (cost=0.28..8.30 rows=1 width=8) (actual rows= loops=)

  • Index Cond: (id = pricing_models.project_id)
117. 0.000 0.000 ↓ 0.0

Index Scan using clients_pkey on clients (cost=0.28..0.32 rows=1 width=8) (actual rows= loops=)

  • Index Cond: (id = projects_2.client_id)
118. 0.000 0.000 ↓ 0.0

Index Scan using index_rates_on_activity_id_and_rate_card_id on rates (cost=0.42..1,376.55 rows=49 width=28) (actual rows= loops=)

  • Index Cond: (rate_card_id = rate_cards.id)
119. 0.000 0.000 ↓ 0.0

Sort (cost=6.09..6.37 rows=115 width=4) (actual rows= loops=)

  • Sort Key: brands.id
120. 0.000 0.000 ↓ 0.0

Seq Scan on brands (cost=0.00..2.15 rows=115 width=4) (actual rows= loops=)

121. 0.000 0.000 ↓ 0.0

Subquery Scan on *SELECT* 2 (cost=583.00..5,484.31 rows=35,240 width=44) (actual rows= loops=)

122. 0.000 0.000 ↓ 0.0

Hash Join (cost=583.00..5,131.91 rows=35,240 width=612) (actual rows= loops=)

  • Hash Cond: (rates_1.rate_card_id = rate_cards_1.id)
123. 0.000 0.000 ↓ 0.0

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

124. 0.000 0.000 ↓ 0.0

Hash (cost=574.00..574.00 rows=720 width=24) (actual rows= loops=)

125. 0.000 0.000 ↓ 0.0

Hash Join (cost=378.98..574.00 rows=720 width=24) (actual rows= loops=)

  • Hash Cond: (clients_1.office_id = offices.id)
126. 0.000 0.000 ↓ 0.0

Hash Join (cost=214.02..399.80 rows=623 width=8) (actual rows= loops=)

  • Hash Cond: (projects_3.client_id = clients_1.id)
127. 0.000 0.000 ↓ 0.0

Hash Join (cost=150.41..334.56 rows=623 width=8) (actual rows= loops=)

  • Hash Cond: (projects_3.id = pricing_models_1.project_id)
128. 0.000 0.000 ↓ 0.0

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

129. 0.000 0.000 ↓ 0.0

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

130. 0.000 0.000 ↓ 0.0

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

  • Filter: ((rates_type)::text = 'office'::text)
131. 0.000 0.000 ↓ 0.0

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

132. 0.000 0.000 ↓ 0.0

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

133. 0.000 0.000 ↓ 0.0

Hash (cost=158.85..158.85 rows=489 width=28) (actual rows= loops=)

134. 0.000 0.000 ↓ 0.0

Hash Join (cost=140.44..158.85 rows=489 width=28) (actual rows= loops=)

  • Hash Cond: (rate_cards_1.rateable_id = offices.id)
135. 0.000 0.000 ↓ 0.0

WindowAgg (cost=126.52..138.74 rows=489 width=45) (actual rows= loops=)

136. 0.000 0.000 ↓ 0.0

Sort (cost=126.52..127.74 rows=489 width=29) (actual rows= loops=)

  • Sort Key: rate_cards_1.rateable_id, rate_cards_1.start_date DESC NULLS LAST
137. 0.000 0.000 ↓ 0.0

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

  • Filter: ((rateable_type)::text = 'Office'::text)
138. 0.000 0.000 ↓ 0.0

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

139. 0.000 0.000 ↓ 0.0

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

140. 0.000 0.000 ↓ 0.0

Subquery Scan on *SELECT* 3 (cost=840.78..9,363.71 rows=205,419 width=44) (actual rows= loops=)

141. 0.000 0.000 ↓ 0.0

Hash Join (cost=840.78..7,309.52 rows=205,419 width=612) (actual rows= loops=)

  • Hash Cond: (rates_2.rate_card_id = rate_cards_2.id)
142. 0.000 0.000 ↓ 0.0

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

143. 0.000 0.000 ↓ 0.0

Hash (cost=788.31..788.31 rows=4,197 width=24) (actual rows= loops=)

144. 0.000 0.000 ↓ 0.0

Hash Join (cost=586.95..788.31 rows=4,197 width=24) (actual rows= loops=)

  • Hash Cond: (projects_4.client_id = clients_2.id)
145. 0.000 0.000 ↓ 0.0

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

  • Hash Cond: (pricing_models_2.project_id = projects_4.id)
146. 0.000 0.000 ↓ 0.0

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

  • Filter: ((rates_type)::text = 'client'::text)
147. 0.000 0.000 ↓ 0.0

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

148. 0.000 0.000 ↓ 0.0

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

149. 0.000 0.000 ↓ 0.0

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

150. 0.000 0.000 ↓ 0.0

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

  • Hash Cond: (rate_cards_2.rateable_id = clients_2.id)
151. 0.000 0.000 ↓ 0.0

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

152. 0.000 0.000 ↓ 0.0

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

  • Sort Key: rate_cards_2.rateable_id, rate_cards_2.start_date DESC NULLS LAST
153. 0.000 0.000 ↓ 0.0

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

  • Filter: ((rateable_type)::text = 'Client'::text)
154. 0.000 0.000 ↓ 0.0

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

155. 0.000 0.000 ↓ 0.0

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

156. 0.000 0.000 ↓ 0.0

Subquery Scan on *SELECT* 4 (cost=695.56..5,531.29 rows=31,961 width=44) (actual rows= loops=)

157. 0.000 0.000 ↓ 0.0

Hash Join (cost=695.56..5,211.68 rows=31,961 width=612) (actual rows= loops=)

  • Hash Cond: (rates_3.rate_card_id = rate_cards_3.id)
158. 0.000 0.000 ↓ 0.0

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

159. 0.000 0.000 ↓ 0.0

Hash (cost=687.40..687.40 rows=653 width=24) (actual rows= loops=)

160. 0.000 0.000 ↓ 0.0

Hash Join (cost=502.95..687.40 rows=653 width=24) (actual rows= loops=)

  • Hash Cond: (projects_5.id = pricing_models_3.project_id)
161. 0.000 0.000 ↓ 0.0

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

162. 0.000 0.000 ↓ 0.0

Hash (cost=494.79..494.79 rows=653 width=24) (actual rows= loops=)

163. 0.000 0.000 ↓ 0.0

Hash Join (cost=403.40..494.79 rows=653 width=24) (actual rows= loops=)

  • Hash Cond: (rate_cards_3.rateable_id = pricing_models_3.id)
164. 0.000 0.000 ↓ 0.0

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

165. 0.000 0.000 ↓ 0.0

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

  • Sort Key: rate_cards_3.rateable_id, rate_cards_3.start_date DESC NULLS LAST
166. 0.000 0.000 ↓ 0.0

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

  • Filter: ((rateable_type)::text = 'PricingModel'::text)
167. 0.000 0.000 ↓ 0.0

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

168. 0.000 0.000 ↓ 0.0

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

  • Filter: ((rates_type)::text = 'custom'::text)