explain.depesz.com

PostgreSQL's explain analyze made readable

Result: sa9f

Settings
# exclusive inclusive rows x rows loops node
1. 0.034 9,377.003 ↑ 1.0 24 1

Limit (cost=79,210.55..79,218.47 rows=24 width=2,611) (actual time=9,376.905..9,377.003 rows=24 loops=1)

2. 0.116 9,376.969 ↑ 56.3 24 1

Result (cost=79,210.55..79,656.38 rows=1,351 width=2,611) (actual time=9,376.905..9,376.969 rows=24 loops=1)

3. 112.971 9,376.853 ↑ 56.3 24 1

Sort (cost=79,210.55..79,213.93 rows=1,351 width=2,579) (actual time=9,376.852..9,376.853 rows=24 loops=1)

  • Sort Key: pc.associated_date DESC NULLS LAST
  • Sort Method: top-N heapsort Memory: 69kB
4. 119.766 9,263.882 ↓ 51.3 69,241 1

Nested Loop Left Join (cost=53,198.20..79,172.83 rows=1,351 width=2,579) (actual time=7,204.400..9,263.882 rows=69,241 loops=1)

5. 61.450 8,867.152 ↓ 256.4 69,241 1

Nested Loop Left Join (cost=53,198.20..73,229.39 rows=270 width=2,589) (actual time=7,204.383..8,867.152 rows=69,241 loops=1)

6. 64.873 8,736.461 ↓ 256.4 69,241 1

Nested Loop Left Join (cost=53,197.92..73,147.94 rows=270 width=2,595) (actual time=7,204.350..8,736.461 rows=69,241 loops=1)

7. 118.702 8,256.142 ↓ 256.4 69,241 1

Nested Loop Left Join (cost=53,175.93..56,581.84 rows=270 width=2,587) (actual time=7,201.097..8,256.142 rows=69,241 loops=1)

  • Join Filter: (offer.id = offer_approval.offer_id)
  • Rows Removed by Join Filter: 1315568
8. 446.125 8,137.440 ↓ 256.4 69,241 1

Hash Left Join (cost=53,174.50..56,419.40 rows=270 width=2,562) (actual time=7,200.610..8,137.440 rows=69,241 loops=1)

  • Hash Cond: (pc.candidate_id = tgc.candidate_id)
  • Filter: ((tgc.team_group_id IS NULL) OR (tgc.team_group_id = 1121))
  • Rows Removed by Filter: 141404
9. 129.609 7,597.103 ↓ 199.5 135,095 1

Nested Loop Left Join (cost=40,341.60..41,304.60 rows=677 width=2,558) (actual time=7,105.186..7,597.103 rows=135,095 loops=1)

10. 140.319 7,467.494 ↓ 199.5 135,094 1

Nested Loop Left Join (cost=40,341.45..41,185.89 rows=677 width=2,288) (actual time=7,105.171..7,467.494 rows=135,094 loops=1)

11. 130.327 7,327.175 ↓ 199.5 135,094 1

Merge Left Join (cost=40,341.31..41,068.46 rows=677 width=2,280) (actual time=7,105.145..7,327.175 rows=135,094 loops=1)

  • Merge Cond: (pc.candidate_id = cd.candidate_id)
12. 556.820 7,046.917 ↓ 199.5 135,094 1

Sort (cost=13,779.88..13,781.57 rows=677 width=2,239) (actual time=6,967.890..7,046.917 rows=135,094 loops=1)

  • Sort Key: pc.candidate_id
  • Sort Method: external merge Disk: 78408kB
13. 77.844 6,490.097 ↓ 199.5 135,094 1

Hash Left Join (cost=3,638.98..13,748.05 rows=677 width=2,239) (actual time=29.144..6,490.097 rows=135,094 loops=1)

  • Hash Cond: ((interview_1.id = ih.interview_id) AND (interview_1.interview_no = ih.interview_no))
14. 33.043 6,408.598 ↓ 199.5 135,084 1

Nested Loop Left Join (cost=3,154.13..13,238.53 rows=677 width=2,231) (actual time=25.432..6,408.598 rows=135,084 loops=1)

15. 85.006 6,105.389 ↓ 199.5 135,083 1

Hash Left Join (cost=3,153.56..12,763.30 rows=677 width=2,185) (actual time=25.424..6,105.389 rows=135,083 loops=1)

  • Hash Cond: (c.user_account_id = user_temp.id)
16. 47.571 6,020.247 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=3,066.66..12,674.60 rows=677 width=2,172) (actual time=25.284..6,020.247 rows=135,083 loops=1)

17. 68.141 5,702.510 ↓ 199.5 135,083 1

Hash Left Join (cost=3,066.37..12,453.99 rows=677 width=2,140) (actual time=25.264..5,702.510 rows=135,083 loops=1)

  • Hash Cond: (offer.id = offer_fee_model.offer_id)
18. 114.178 5,634.253 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=3,051.52..12,435.99 rows=677 width=2,128) (actual time=25.143..5,634.253 rows=135,083 loops=1)

19. 69.560 5,520.075 ↓ 199.5 135,083 1

Hash Left Join (cost=3,051.23..12,125.82 rows=677 width=2,072) (actual time=25.140..5,520.075 rows=135,083 loops=1)

  • Hash Cond: (offer.id = invoice.offer_id)
20. 98.720 5,449.673 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=2,958.22..12,031.03 rows=677 width=2,058) (actual time=24.281..5,449.673 rows=135,083 loops=1)

21. 63.918 5,350.953 ↓ 199.5 135,083 1

Hash Left Join (cost=2,957.95..11,832.71 rows=677 width=2,041) (actual time=24.274..5,350.953 rows=135,083 loops=1)

  • Hash Cond: (pd.vertical_id = vertical.id)
22. 140.209 5,287.007 ↓ 199.5 135,083 1

Hash Left Join (cost=2,955.78..11,828.73 rows=677 width=2,023) (actual time=24.236..5,287.007 rows=135,083 loops=1)

  • Hash Cond: (pd.company_location_id = company_location.id)
23. 74.520 5,125.655 ↓ 199.5 135,083 1

Hash Left Join (cost=366.49..8,410.67 rows=677 width=1,955) (actual time=2.868..5,125.655 rows=135,083 loops=1)

  • Hash Cond: (c.candidate_source_id = candidate_source.id)
24. 63.685 5,051.114 ↓ 199.5 135,083 1

Hash Left Join (cost=364.66..8,406.86 rows=677 width=1,443) (actual time=2.843..5,051.114 rows=135,083 loops=1)

  • Hash Cond: (c.deleted_by_user_id = ua_deleted_by.id)
25. 73.042 4,987.347 ↓ 199.5 135,083 1

Hash Left Join (cost=277.76..8,318.19 rows=677 width=1,430) (actual time=2.752..4,987.347 rows=135,083 loops=1)

  • Hash Cond: (pc.created_by = ua.id)
26. 106.903 4,914.225 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=190.87..8,229.50 rows=677 width=1,413) (actual time=2.663..4,914.225 rows=135,083 loops=1)

27. 75.364 4,672.239 ↓ 199.5 135,083 1

Hash Left Join (cost=190.58..8,022.80 rows=677 width=1,305) (actual time=2.658..4,672.239 rows=135,083 loops=1)

  • Hash Cond: ((cl.country_code)::text = (co.code)::text)
28. 161.202 4,596.804 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=181.89..8,012.32 rows=677 width=1,297) (actual time=2.583..4,596.804 rows=135,083 loops=1)

29. 59.900 3,760.187 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=181.47..7,649.10 rows=677 width=1,263) (actual time=2.565..3,760.187 rows=135,083 loops=1)

30. 56.107 3,430.121 ↓ 199.5 135,083 1

Hash Left Join (cost=181.18..7,433.70 rows=677 width=1,218) (actual time=2.559..3,430.121 rows=135,083 loops=1)

  • Hash Cond: (pc.sent_user_id = sent_user_account.id)
31. 62.741 3,373.899 ↓ 199.5 135,083 1

Hash Left Join (cost=94.28..7,345.03 rows=677 width=1,201) (actual time=2.439..3,373.899 rows=135,083 loops=1)

  • Hash Cond: (pc.shortlisted_user_id = shortlisted_user_account.id)
32. 115.630 3,310.713 ↓ 199.5 135,083 1

Nested Loop (cost=7.39..7,256.35 rows=677 width=1,184) (actual time=1.988..3,310.713 rows=135,083 loops=1)

  • Join Filter: (pc.candidate_id = c.id)
33. 101.316 1,697.268 ↓ 199.9 136,165 1

Nested Loop (cost=6.96..6,027.29 rows=681 width=994) (actual time=1.960..1,697.268 rows=136,165 loops=1)

34. 73.122 915.127 ↓ 199.9 136,165 1

Nested Loop (cost=6.54..5,621.87 rows=681 width=544) (actual time=1.922..915.127 rows=136,165 loops=1)

35. 21.185 403.643 ↓ 199.9 25,786 1

Nested Loop Left Join (cost=6.12..2,447.33 rows=129 width=147) (actual time=1.831..403.643 rows=25,786 loops=1)

36. 36.963 227.742 ↓ 199.9 25,786 1

Nested Loop Left Join (cost=5.70..1,451.22 rows=129 width=119) (actual time=1.813..227.742 rows=25,786 loops=1)

37. 34.647 36.063 ↓ 199.9 25,786 1

Bitmap Heap Scan on position_description pd (cost=5.29..435.10 rows=129 width=102) (actual time=1.793..36.063 rows=25,786 loops=1)

  • Recheck Cond: (position_category = 1)
  • Heap Blocks: exact=2895
38. 1.416 1.416 ↓ 199.9 25,786 1

Bitmap Index Scan on position_description_position_category (cost=0.00..5.25 rows=129 width=0) (actual time=1.416..1.416 rows=25,786 loops=1)

  • Index Cond: (position_category = 1)
39. 154.716 154.716 ↑ 1.0 1 25,786

Index Scan using contact__pkey on contact (cost=0.42..7.88 rows=1 width=21) (actual time=0.006..0.006 rows=1 loops=25,786)

  • Index Cond: (id = pd.contact_id)
40. 154.716 154.716 ↑ 1.0 1 25,786

Index Scan using company__pkey on company (cost=0.42..7.72 rows=1 width=32) (actual time=0.006..0.006 rows=1 loops=25,786)

  • Index Cond: (id = pd.company_id)
41. 438.362 438.362 ↑ 1.8 5 25,786

Index Scan using index_pc_pd on position_candidate pc (cost=0.42..24.52 rows=9 width=405) (actual time=0.005..0.017 rows=5 loops=25,786)

  • Index Cond: (position_description_id = pd.id)
  • Filter: ((status >= 102) AND (associated_date <= now()) AND (associated_date >= (date_trunc('year'::text, now()) - '5 years'::interval)))
42. 680.825 680.825 ↑ 1.0 1 136,165

Index Scan using candidate_extension_candidate_id__pkey on candidate_extension ce (cost=0.42..0.60 rows=1 width=450) (actual time=0.005..0.005 rows=1 loops=136,165)

  • Index Cond: (candidate_id = pc.candidate_id)
43. 1,497.815 1,497.815 ↑ 1.0 1 136,165

Index Scan using candidate_pkey on candidate c (cost=0.42..1.79 rows=1 width=198) (actual time=0.011..0.011 rows=1 loops=136,165)

  • Index Cond: (id = ce.candidate_id)
  • Filter: (deleted_timestamp IS NULL)
  • Rows Removed by Filter: 0
44. 0.039 0.445 ↓ 1.0 352 1

Hash (cost=82.51..82.51 rows=351 width=21) (actual time=0.445..0.445 rows=352 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 28kB
45. 0.406 0.406 ↓ 1.0 352 1

Seq Scan on user_account shortlisted_user_account (cost=0.00..82.51 rows=351 width=21) (actual time=0.011..0.406 rows=352 loops=1)

46. 0.038 0.115 ↓ 1.0 352 1

Hash (cost=82.51..82.51 rows=351 width=21) (actual time=0.115..0.115 rows=352 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 28kB
47. 0.077 0.077 ↓ 1.0 352 1

Seq Scan on user_account sent_user_account (cost=0.00..82.51 rows=351 width=21) (actual time=0.006..0.077 rows=352 loops=1)

48. 270.166 270.166 ↑ 1.0 1 135,083

Index Scan using position_extension__pkey on position_extension pe (cost=0.29..0.32 rows=1 width=53) (actual time=0.002..0.002 rows=1 loops=135,083)

  • Index Cond: (pc.position_description_id = position_id)
49. 675.415 675.415 ↑ 1.0 1 135,083

Index Scan using common_location_pkey on common_location cl (cost=0.42..0.54 rows=1 width=46) (actual time=0.005..0.005 rows=1 loops=135,083)

  • Index Cond: (c.current_location_id = id)
50. 0.034 0.071 ↑ 1.0 253 1

Hash (cost=5.53..5.53 rows=253 width=13) (actual time=0.071..0.071 rows=253 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 20kB
51. 0.037 0.037 ↑ 1.0 253 1

Seq Scan on country co (cost=0.00..5.53 rows=253 width=13) (actual time=0.015..0.037 rows=253 loops=1)

52. 135.083 135.083 ↓ 0.0 0 135,083

Index Scan using offer_valid_position_candidate_id__unq on offer (cost=0.28..0.31 rows=1 width=112) (actual time=0.001..0.001 rows=0 loops=135,083)

  • Index Cond: (pc.id = position_candidate_id)
53. 0.032 0.080 ↓ 1.0 352 1

Hash (cost=82.51..82.51 rows=351 width=21) (actual time=0.080..0.080 rows=352 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 28kB
54. 0.048 0.048 ↓ 1.0 352 1

Seq Scan on user_account ua (cost=0.00..82.51 rows=351 width=21) (actual time=0.006..0.048 rows=352 loops=1)

55. 0.034 0.082 ↓ 1.0 352 1

Hash (cost=82.51..82.51 rows=351 width=21) (actual time=0.082..0.082 rows=352 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 28kB
56. 0.048 0.048 ↓ 1.0 352 1

Seq Scan on user_account ua_deleted_by (cost=0.00..82.51 rows=351 width=21) (actual time=0.008..0.048 rows=352 loops=1)

57. 0.004 0.021 ↓ 1.0 38 1

Hash (cost=1.37..1.37 rows=37 width=520) (actual time=0.021..0.021 rows=38 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 11kB
58. 0.017 0.017 ↓ 1.0 38 1

Seq Scan on candidate_source (cost=0.00..1.37 rows=37 width=520) (actual time=0.014..0.017 rows=38 loops=1)

59. 7.918 21.143 ↑ 1.0 42,546 1

Hash (cost=1,558.46..1,558.46 rows=42,546 width=72) (actual time=21.143..21.143 rows=42,546 loops=1)

  • Buckets: 65536 Batches: 2 Memory Usage: 2552kB
60. 13.225 13.225 ↑ 1.0 42,546 1

Seq Scan on company_location (cost=0.00..1,558.46 rows=42,546 width=72) (actual time=0.017..13.225 rows=42,546 loops=1)

61. 0.011 0.028 ↑ 1.0 52 1

Hash (cost=1.52..1.52 rows=52 width=22) (actual time=0.028..0.028 rows=52 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 11kB
62. 0.017 0.017 ↑ 1.0 52 1

Seq Scan on vertical (cost=0.00..1.52 rows=52 width=22) (actual time=0.013..0.017 rows=52 loops=1)

63. 0.000 0.000 ↓ 0.0 0 135,083

Index Scan using client_account_pkey on user_account (cost=0.27..0.29 rows=1 width=21) (actual time=0.000..0.000 rows=0 loops=135,083)

  • Index Cond: (company.company_owner_id = id)
64. 0.311 0.842 ↑ 1.0 2,845 1

Hash (cost=57.45..57.45 rows=2,845 width=18) (actual time=0.842..0.842 rows=2,845 loops=1)

  • Buckets: 4096 Batches: 1 Memory Usage: 155kB
65. 0.531 0.531 ↑ 1.0 2,845 1

Seq Scan on invoice (cost=0.00..57.45 rows=2,845 width=18) (actual time=0.016..0.531 rows=2,845 loops=1)

66. 0.000 0.000 ↓ 0.0 0 135,083

Index Scan using offer_personal_info__offer__fkey on offer_personal_info (cost=0.28..0.46 rows=1 width=60) (actual time=0.000..0.000 rows=0 loops=135,083)

  • Index Cond: (offer_id = offer.id)
67. 0.044 0.116 ↑ 1.0 438 1

Hash (cost=9.38..9.38 rows=438 width=16) (actual time=0.116..0.116 rows=438 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 26kB
68. 0.072 0.072 ↑ 1.0 438 1

Seq Scan on offer_fee_model (cost=0.00..9.38 rows=438 width=16) (actual time=0.011..0.072 rows=438 loops=1)

69. 270.166 270.166 ↑ 1.0 1 135,083

Index Scan using compensation_position_id__uidx on compensation (cost=0.29..0.33 rows=1 width=36) (actual time=0.002..0.002 rows=1 loops=135,083)

  • Index Cond: (pc.position_description_id = position_id)
70. 0.041 0.136 ↓ 1.0 352 1

Hash (cost=82.51..82.51 rows=351 width=21) (actual time=0.136..0.136 rows=352 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 28kB
71. 0.095 0.095 ↓ 1.0 352 1

Seq Scan on user_account user_temp (cost=0.00..82.51 rows=351 width=21) (actual time=0.008..0.095 rows=352 loops=1)

72. 108.344 270.166 ↓ 0.0 0 135,083

Nested Loop Left Join (cost=0.57..0.69 rows=1 width=50) (actual time=0.001..0.002 rows=0 loops=135,083)

73. 135.083 135.083 ↓ 0.0 0 135,083

Index Scan using interview_position_candidate_id on interview interview_1 (cost=0.29..0.31 rows=1 width=41) (actual time=0.001..0.001 rows=0 loops=135,083)

  • Index Cond: (position_candidate_id = pc.id)
  • Filter: ((pc.status - interview_no) = 103)
  • Rows Removed by Filter: 0
74. 26.739 26.739 ↑ 1.0 1 8,913

Index Scan using interview_time__interview_id_fkey on interview_time (cost=0.29..0.36 rows=1 width=20) (actual time=0.003..0.003 rows=1 loops=8,913)

  • Index Cond: (interview_1.id = interview_id)
  • Filter: ((selected = 1) OR (index_num = 1))
  • Rows Removed by Filter: 0
75. 1.550 3.655 ↑ 1.0 12,594 1

Hash (cost=295.94..295.94 rows=12,594 width=24) (actual time=3.655..3.655 rows=12,594 loops=1)

  • Buckets: 16384 Batches: 1 Memory Usage: 857kB
76. 2.105 2.105 ↑ 1.0 12,594 1

Seq Scan on interview_history ih (cost=0.00..295.94 rows=12,594 width=24) (actual time=0.028..2.105 rows=12,594 loops=1)

77. 5.954 149.931 ↓ 1.5 52,536 1

Unique (cost=26,561.42..26,837.78 rows=35,488 width=53) (actual time=137.043..149.931 rows=52,536 loops=1)

78. 43.576 143.977 ↑ 1.0 54,059 1

Sort (cost=26,561.42..26,699.60 rows=55,271 width=53) (actual time=137.042..143.977 rows=54,059 loops=1)

  • Sort Key: cd.candidate_id, cd.created DESC
  • Sort Method: external merge Disk: 3496kB
79. 95.742 100.401 ↑ 1.0 54,062 1

Bitmap Heap Scan on candidate_document cd (cost=1,072.78..20,317.66 rows=55,271 width=53) (actual time=6.053..100.401 rows=54,062 loops=1)

  • Recheck Cond: ((document_type)::text = 'candidate_photo'::text)
  • Heap Blocks: exact=12845
80. 4.659 4.659 ↑ 1.0 54,062 1

Bitmap Index Scan on candidate_document_document_type_idx (cost=0.00..1,058.96 rows=55,271 width=0) (actual time=4.659..4.659 rows=54,062 loops=1)

  • Index Cond: ((document_type)::text = 'candidate_photo'::text)
81. 0.000 0.000 ↓ 0.0 0 135,094

Index Scan using compensation_fee_model_compensation_id__fkey on compensation_fee_model (cost=0.14..0.16 rows=1 width=12) (actual time=0.000..0.000 rows=0 loops=135,094)

  • Index Cond: (compensation_id = compensation.id)
82. 0.000 0.000 ↓ 0.0 0 135,094

Index Scan using company_response__position_candidate_id__fkey on position_candidate_company_response (cost=0.15..0.17 rows=1 width=274) (actual time=0.000..0.000 rows=0 loops=135,094)

  • Index Cond: (position_candidate_id = pc.id)
83. 47.090 94.212 ↑ 1.0 369,418 1

Hash (cost=6,411.18..6,411.18 rows=369,418 width=12) (actual time=94.212..94.212 rows=369,418 loops=1)

  • Buckets: 131072 Batches: 8 Memory Usage: 3207kB
84. 47.122 47.122 ↑ 1.0 369,418 1

Seq Scan on team_group_candidate tgc (cost=0.00..6,411.18 rows=369,418 width=12) (actual time=0.026..47.122 rows=369,418 loops=1)

85. 0.000 0.000 ↑ 1.0 19 69,241

Materialize (cost=1.43..85.54 rows=19 width=29) (actual time=0.000..0.000 rows=19 loops=69,241)

86. 0.047 0.451 ↑ 1.0 19 1

Hash Right Join (cost=1.43..85.44 rows=19 width=29) (actual time=0.274..0.451 rows=19 loops=1)

  • Hash Cond: (approver.id = offer_approval.user_account_id)
87. 0.377 0.377 ↓ 1.0 352 1

Seq Scan on user_account approver (cost=0.00..82.51 rows=351 width=21) (actual time=0.014..0.377 rows=352 loops=1)

88. 0.005 0.027 ↑ 1.0 19 1

Hash (cost=1.19..1.19 rows=19 width=12) (actual time=0.027..0.027 rows=19 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
89. 0.022 0.022 ↑ 1.0 19 1

Seq Scan on offer_approval (cost=0.00..1.19 rows=19 width=12) (actual time=0.020..0.022 rows=19 loops=1)

90. 0.000 415.446 ↓ 0.0 0 69,241

GroupAggregate (cost=21.99..61.34 rows=1 width=12) (actual time=0.006..0.006 rows=0 loops=69,241)

  • Group Key: cd_1.candidate_id
91. 0.000 415.446 ↓ 0.0 0 69,241

Result (cost=21.99..61.32 rows=1 width=8) (actual time=0.006..0.006 rows=0 loops=69,241)

  • One-Time Filter: (pc.status >= 102)
92. 135.263 415.446 ↓ 0.0 0 69,241

Hash Join (cost=21.99..61.32 rows=1 width=8) (actual time=0.006..0.006 rows=0 loops=69,241)

  • Hash Cond: (cd_1.document_types_id = odt.document_type_id)
93. 3.219 3.219 ↑ 14.0 1 1

Index Scan using candidate_document_candidate_id_idx on candidate_document cd_1 (cost=0.42..39.69 rows=14 width=8) (actual time=3.218..3.219 rows=1 loops=1)

  • Index Cond: (pc.candidate_id = candidate_id)
94. 276.964 276.964 ↓ 0.0 0 69,241

Hash (cost=21.50..21.50 rows=5 width=4) (actual time=0.004..0.004 rows=0 loops=69,241)

  • Buckets: 1024 Batches: 1 Memory Usage: 8kB
95. 0.000 0.000 ↓ 0.0 0 69,241

Seq Scan on onboarding_document_type odt (cost=0.00..21.50 rows=5 width=4) (actual time=0.000..0.000 rows=0 loops=69,241)

  • Filter: (pc.position_description_id = job_id)
96. 69.241 69.241 ↓ 0.0 0 69,241

Index Scan using gdpr_compliance_pkey on candidate_gdpr_compliance cgc (cost=0.28..0.30 rows=1 width=6) (actual time=0.001..0.001 rows=0 loops=69,241)

  • Index Cond: (c.id = candidate_id)
  • Filter: (portal_status IS NOT NULL)
  • Rows Removed by Filter: 0
97. 276.964 276.964 ↓ 0.0 0 69,241

GroupAggregate (cost=0.00..21.57 rows=5 width=16) (actual time=0.004..0.004 rows=0 loops=69,241)

  • Group Key: onboarding_document_type.job_id
98. 0.000 0.000 ↓ 0.0 0 69,241

Seq Scan on onboarding_document_type (cost=0.00..21.50 rows=5 width=8) (actual time=0.000..0.000 rows=0 loops=69,241)

  • Filter: (job_id = pc.position_description_id)