explain.depesz.com

PostgreSQL's explain analyze made readable

Result: Y4pW

Settings
# exclusive inclusive rows x rows loops node
1. 0.035 19,164.764 ↓ 24.0 24 1

Limit (cost=56,741.43..56,741.76 rows=1 width=2,611) (actual time=19,164.565..19,164.764 rows=24 loops=1)

2. 0.277 19,164.729 ↓ 24.0 24 1

Result (cost=56,741.43..56,741.76 rows=1 width=2,611) (actual time=19,164.564..19,164.729 rows=24 loops=1)

3. 72.215 19,164.452 ↓ 24.0 24 1

Sort (cost=56,741.43..56,741.43 rows=1 width=2,579) (actual time=19,164.450..19,164.452 rows=24 loops=1)

  • Sort Key: pc.associated_date DESC NULLS LAST
  • Sort Method: top-N heapsort Memory: 66kB
4. 676.456 19,092.237 ↓ 33,540.0 33,540 1

Nested Loop Left Join (cost=53,198.85..56,741.42 rows=1 width=2,579) (actual time=6,766.546..19,092.237 rows=33,540 loops=1)

  • Join Filter: (approver.id = offer_approval.user_account_id)
  • Rows Removed by Join Filter: 11805238
5. 220.259 17,443.121 ↓ 33,540.0 33,540 1

Nested Loop Left Join (cost=53,198.85..56,654.45 rows=1 width=2,580) (actual time=6,765.889..17,443.121 rows=33,540 loops=1)

  • Join Filter: (offer.id = offer_approval.offer_id)
  • Rows Removed by Join Filter: 637255
6. 2,867.434 17,189.322 ↓ 33,540.0 33,540 1

Nested Loop Left Join (cost=53,198.85..56,653.03 rows=1 width=2,572) (actual time=6,765.858..17,189.322 rows=33,540 loops=1)

  • Join Filter: (c.id = cgc.candidate_id)
  • Rows Removed by Join Filter: 66708231
7. 24.968 8,116.988 ↓ 33,540.0 33,540 1

Nested Loop Left Join (cost=53,198.57..56,505.51 rows=1 width=2,578) (actual time=6,764.614..8,116.988 rows=33,540 loops=1)

8. 45.081 7,957.860 ↓ 33,540.0 33,540 1

Nested Loop Left Join (cost=53,198.57..56,483.84 rows=1 width=2,570) (actual time=6,764.605..7,957.860 rows=33,540 loops=1)

9. 440.451 7,677.999 ↓ 33,540.0 33,540 1

Hash Left Join (cost=53,176.58..56,422.48 rows=1 width=2,562) (actual time=6,764.497..7,677.999 rows=33,540 loops=1)

  • Hash Cond: (pc.candidate_id = tgc.candidate_id)
  • Filter: ((tgc.team_group_id IS NULL) OR (tgc.team_group_id = 1133))
  • Rows Removed by Filter: 177105
10. 122.572 7,145.356 ↓ 199.5 135,095 1

Nested Loop Left Join (cost=40,341.60..41,304.60 rows=677 width=2,558) (actual time=6,670.395..7,145.356 rows=135,095 loops=1)

11. 132.320 7,022.784 ↓ 199.5 135,094 1

Nested Loop Left Join (cost=40,341.45..41,185.89 rows=677 width=2,288) (actual time=6,670.379..7,022.784 rows=135,094 loops=1)

12. 128.140 6,890.464 ↓ 199.5 135,094 1

Merge Left Join (cost=40,341.31..41,068.46 rows=677 width=2,280) (actual time=6,670.353..6,890.464 rows=135,094 loops=1)

  • Merge Cond: (pc.candidate_id = cd.candidate_id)
13. 546.070 6,615.432 ↓ 199.5 135,094 1

Sort (cost=13,779.88..13,781.57 rows=677 width=2,239) (actual time=6,535.264..6,615.432 rows=135,094 loops=1)

  • Sort Key: pc.candidate_id
  • Sort Method: external merge Disk: 78408kB
14. 75.309 6,069.362 ↓ 199.5 135,094 1

Hash Left Join (cost=3,638.98..13,748.05 rows=677 width=2,239) (actual time=28.053..6,069.362 rows=135,094 loops=1)

  • Hash Cond: ((interview_1.id = ih.interview_id) AND (interview_1.interview_no = ih.interview_no))
15. 149.567 5,990.311 ↓ 199.5 135,084 1

Nested Loop Left Join (cost=3,154.13..13,238.53 rows=677 width=2,231) (actual time=24.253..5,990.311 rows=135,084 loops=1)

16. 81.914 5,705.661 ↓ 199.5 135,083 1

Hash Left Join (cost=3,153.56..12,763.30 rows=677 width=2,185) (actual time=24.244..5,705.661 rows=135,083 loops=1)

  • Hash Cond: (c.user_account_id = user_temp.id)
17. 162.629 5,623.613 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=3,066.66..12,674.60 rows=677 width=2,172) (actual time=24.104..5,623.613 rows=135,083 loops=1)

18. 62.690 5,325.901 ↓ 199.5 135,083 1

Hash Left Join (cost=3,066.37..12,453.99 rows=677 width=2,140) (actual time=24.086..5,325.901 rows=135,083 loops=1)

  • Hash Cond: (offer.id = offer_fee_model.offer_id)
19. 107.014 5,263.096 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=3,051.52..12,435.99 rows=677 width=2,128) (actual time=23.966..5,263.096 rows=135,083 loops=1)

20. 62.913 5,156.082 ↓ 199.5 135,083 1

Hash Left Join (cost=3,051.23..12,125.82 rows=677 width=2,072) (actual time=23.961..5,156.082 rows=135,083 loops=1)

  • Hash Cond: (offer.id = invoice.offer_id)
21. 90.731 5,092.357 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=2,958.22..12,031.03 rows=677 width=2,058) (actual time=23.143..5,092.357 rows=135,083 loops=1)

22. 60.974 5,001.626 ↓ 199.5 135,083 1

Hash Left Join (cost=2,957.95..11,832.71 rows=677 width=2,041) (actual time=23.137..5,001.626 rows=135,083 loops=1)

  • Hash Cond: (pd.vertical_id = vertical.id)
23. 135.716 4,940.629 ↓ 199.5 135,083 1

Hash Left Join (cost=2,955.78..11,828.73 rows=677 width=2,023) (actual time=23.103..4,940.629 rows=135,083 loops=1)

  • Hash Cond: (pd.company_location_id = company_location.id)
24. 71.169 4,784.359 ↓ 199.5 135,083 1

Hash Left Join (cost=366.49..8,410.67 rows=677 width=1,955) (actual time=2.327..4,784.359 rows=135,083 loops=1)

  • Hash Cond: (c.candidate_source_id = candidate_source.id)
25. 58.319 4,713.167 ↓ 199.5 135,083 1

Hash Left Join (cost=364.66..8,406.86 rows=677 width=1,443) (actual time=2.301..4,713.167 rows=135,083 loops=1)

  • Hash Cond: (c.deleted_by_user_id = ua_deleted_by.id)
26. 65.482 4,654.770 ↓ 199.5 135,083 1

Hash Left Join (cost=277.76..8,318.19 rows=677 width=1,430) (actual time=2.219..4,654.770 rows=135,083 loops=1)

  • Hash Cond: (pc.created_by = ua.id)
27. 89.505 4,589.208 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=190.87..8,229.50 rows=677 width=1,413) (actual time=2.135..4,589.208 rows=135,083 loops=1)

28. 69.751 4,364.620 ↓ 199.5 135,083 1

Hash Left Join (cost=190.58..8,022.80 rows=677 width=1,305) (actual time=2.128..4,364.620 rows=135,083 loops=1)

  • Hash Cond: ((cl.country_code)::text = (co.code)::text)
29. 107.706 4,294.804 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=181.89..8,012.32 rows=677 width=1,297) (actual time=2.060..4,294.804 rows=135,083 loops=1)

30. 33.460 3,511.683 ↓ 199.5 135,083 1

Nested Loop Left Join (cost=181.47..7,649.10 rows=677 width=1,263) (actual time=2.035..3,511.683 rows=135,083 loops=1)

31. 53.457 3,208.057 ↓ 199.5 135,083 1

Hash Left Join (cost=181.18..7,433.70 rows=677 width=1,218) (actual time=2.016..3,208.057 rows=135,083 loops=1)

  • Hash Cond: (pc.sent_user_id = sent_user_account.id)
32. 56.821 3,154.487 ↓ 199.5 135,083 1

Hash Left Join (cost=94.28..7,345.03 rows=677 width=1,201) (actual time=1.899..3,154.487 rows=135,083 loops=1)

  • Hash Cond: (pc.shortlisted_user_id = shortlisted_user_account.id)
33. 161.314 3,097.511 ↓ 199.5 135,083 1

Nested Loop (cost=7.39..7,256.35 rows=677 width=1,184) (actual time=1.738..3,097.511 rows=135,083 loops=1)

  • Join Filter: (pc.candidate_id = c.id)
34. 51.250 1,574.547 ↓ 199.9 136,165 1

Nested Loop (cost=6.96..6,027.29 rows=681 width=994) (actual time=1.711..1,574.547 rows=136,165 loops=1)

35. 63.760 842.472 ↓ 199.9 136,165 1

Nested Loop (cost=6.54..5,621.87 rows=681 width=544) (actual time=1.686..842.472 rows=136,165 loops=1)

36. 5.732 366.136 ↓ 199.9 25,786 1

Nested Loop Left Join (cost=6.12..2,447.33 rows=129 width=147) (actual time=1.657..366.136 rows=25,786 loops=1)

37. 44.826 205.688 ↓ 199.9 25,786 1

Nested Loop Left Join (cost=5.70..1,451.22 rows=129 width=119) (actual time=1.638..205.688 rows=25,786 loops=1)

38. 30.597 31.932 ↓ 199.9 25,786 1

Bitmap Heap Scan on position_description pd (cost=5.29..435.10 rows=129 width=102) (actual time=1.602..31.932 rows=25,786 loops=1)

  • Recheck Cond: (position_category = 1)
  • Heap Blocks: exact=2895
39. 1.335 1.335 ↓ 199.9 25,786 1

Bitmap Index Scan on position_description_position_category (cost=0.00..5.25 rows=129 width=0) (actual time=1.335..1.335 rows=25,786 loops=1)

  • Index Cond: (position_category = 1)
40. 128.930 128.930 ↑ 1.0 1 25,786

Index Scan using contact__pkey on contact (cost=0.42..7.88 rows=1 width=21) (actual time=0.005..0.005 rows=1 loops=25,786)

  • Index Cond: (id = pd.contact_id)
41. 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)
42. 412.576 412.576 ↑ 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..0.016 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)))
43. 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)
44. 1,361.650 1,361.650 ↑ 1.0 1 136,165

Index Scan using candidate_pkey on candidate c (cost=0.42..1.79 rows=1 width=198) (actual time=0.010..0.010 rows=1 loops=136,165)

  • Index Cond: (id = ce.candidate_id)
  • Filter: (deleted_timestamp IS NULL)
  • Rows Removed by Filter: 0
45. 0.033 0.155 ↓ 1.0 352 1

Hash (cost=82.51..82.51 rows=351 width=21) (actual time=0.155..0.155 rows=352 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 28kB
46. 0.122 0.122 ↓ 1.0 352 1

Seq Scan on user_account shortlisted_user_account (cost=0.00..82.51 rows=351 width=21) (actual time=0.022..0.122 rows=352 loops=1)

47. 0.037 0.113 ↓ 1.0 352 1

Hash (cost=82.51..82.51 rows=351 width=21) (actual time=0.113..0.113 rows=352 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 28kB
48. 0.076 0.076 ↓ 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..0.076 rows=352 loops=1)

49. 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)
50. 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)
51. 0.027 0.065 ↑ 1.0 253 1

Hash (cost=5.53..5.53 rows=253 width=13) (actual time=0.065..0.065 rows=253 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 20kB
52. 0.038 0.038 ↑ 1.0 253 1

Seq Scan on country co (cost=0.00..5.53 rows=253 width=13) (actual time=0.016..0.038 rows=253 loops=1)

53. 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)
54. 0.031 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
55. 0.049 0.049 ↓ 1.0 352 1

Seq Scan on user_account ua (cost=0.00..82.51 rows=351 width=21) (actual time=0.005..0.049 rows=352 loops=1)

56. 0.034 0.078 ↓ 1.0 352 1

Hash (cost=82.51..82.51 rows=351 width=21) (actual time=0.078..0.078 rows=352 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 28kB
57. 0.044 0.044 ↓ 1.0 352 1

Seq Scan on user_account ua_deleted_by (cost=0.00..82.51 rows=351 width=21) (actual time=0.005..0.044 rows=352 loops=1)

58. 0.005 0.023 ↓ 1.0 38 1

Hash (cost=1.37..1.37 rows=37 width=520) (actual time=0.023..0.023 rows=38 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 11kB
59. 0.018 0.018 ↓ 1.0 38 1

Seq Scan on candidate_source (cost=0.00..1.37 rows=37 width=520) (actual time=0.015..0.018 rows=38 loops=1)

60. 7.592 20.554 ↑ 1.0 42,546 1

Hash (cost=1,558.46..1,558.46 rows=42,546 width=72) (actual time=20.554..20.554 rows=42,546 loops=1)

  • Buckets: 65536 Batches: 2 Memory Usage: 2552kB
61. 12.962 12.962 ↑ 1.0 42,546 1

Seq Scan on company_location (cost=0.00..1,558.46 rows=42,546 width=72) (actual time=0.018..12.962 rows=42,546 loops=1)

62. 0.006 0.023 ↑ 1.0 52 1

Hash (cost=1.52..1.52 rows=52 width=22) (actual time=0.023..0.023 rows=52 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 11kB
63. 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)

64. 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)
65. 0.274 0.812 ↑ 1.0 2,845 1

Hash (cost=57.45..57.45 rows=2,845 width=18) (actual time=0.812..0.812 rows=2,845 loops=1)

  • Buckets: 4096 Batches: 1 Memory Usage: 155kB
66. 0.538 0.538 ↑ 1.0 2,845 1

Seq Scan on invoice (cost=0.00..57.45 rows=2,845 width=18) (actual time=0.016..0.538 rows=2,845 loops=1)

67. 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)
68. 0.042 0.115 ↑ 1.0 438 1

Hash (cost=9.38..9.38 rows=438 width=16) (actual time=0.115..0.115 rows=438 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 26kB
69. 0.073 0.073 ↑ 1.0 438 1

Seq Scan on offer_fee_model (cost=0.00..9.38 rows=438 width=16) (actual time=0.009..0.073 rows=438 loops=1)

70. 135.083 135.083 ↑ 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=0.001..0.001 rows=1 loops=135,083)

  • Index Cond: (pc.position_description_id = position_id)
71. 0.045 0.134 ↓ 1.0 352 1

Hash (cost=82.51..82.51 rows=351 width=21) (actual time=0.134..0.134 rows=352 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 28kB
72. 0.089 0.089 ↓ 1.0 352 1

Seq Scan on user_account user_temp (cost=0.00..82.51 rows=351 width=21) (actual time=0.008..0.089 rows=352 loops=1)

73. 0.000 135.083 ↓ 0.0 0 135,083

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

74. 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
75. 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
76. 1.554 3.742 ↑ 1.0 12,594 1

Hash (cost=295.94..295.94 rows=12,594 width=24) (actual time=3.742..3.742 rows=12,594 loops=1)

  • Buckets: 16384 Batches: 1 Memory Usage: 857kB
77. 2.188 2.188 ↑ 1.0 12,594 1

Seq Scan on interview_history ih (cost=0.00..295.94 rows=12,594 width=24) (actual time=0.017..2.188 rows=12,594 loops=1)

78. 5.633 146.892 ↓ 1.5 52,536 1

Unique (cost=26,561.42..26,837.78 rows=35,488 width=53) (actual time=134.870..146.892 rows=52,536 loops=1)

79. 41.722 141.259 ↑ 1.0 54,059 1

Sort (cost=26,561.42..26,699.60 rows=55,271 width=53) (actual time=134.869..141.259 rows=54,059 loops=1)

  • Sort Key: cd.candidate_id, cd.created DESC
  • Sort Method: external merge Disk: 3496kB
80. 94.907 99.537 ↑ 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=5.988..99.537 rows=54,062 loops=1)

  • Recheck Cond: ((document_type)::text = 'candidate_photo'::text)
  • Heap Blocks: exact=12845
81. 4.630 4.630 ↑ 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=4.630..4.630 rows=54,062 loops=1)

  • Index Cond: ((document_type)::text = 'candidate_photo'::text)
82. 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)
83. 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)
84. 45.456 92.192 ↑ 1.0 369,418 1

Hash (cost=6,411.66..6,411.66 rows=369,466 width=12) (actual time=92.192..92.192 rows=369,418 loops=1)

  • Buckets: 131072 Batches: 8 Memory Usage: 3207kB
85. 46.736 46.736 ↑ 1.0 369,418 1

Seq Scan on team_group_candidate tgc (cost=0.00..6,411.66 rows=369,466 width=12) (actual time=0.026..46.736 rows=369,418 loops=1)

86. 0.000 234.780 ↓ 0.0 0 33,540

GroupAggregate (cost=21.99..61.34 rows=1 width=12) (actual time=0.007..0.007 rows=0 loops=33,540)

  • Group Key: cd_1.candidate_id
87. 0.000 234.780 ↓ 0.0 0 33,540

Result (cost=21.99..61.32 rows=1 width=8) (actual time=0.007..0.007 rows=0 loops=33,540)

  • One-Time Filter: (pc.status >= 102)
88. 67.000 234.780 ↓ 0.0 0 33,540

Hash Join (cost=21.99..61.32 rows=1 width=8) (actual time=0.007..0.007 rows=0 loops=33,540)

  • Hash Cond: (cd_1.document_types_id = odt.document_type_id)
89. 0.080 0.080 ↑ 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=0.080..0.080 rows=1 loops=1)

  • Index Cond: (pc.candidate_id = candidate_id)
90. 167.700 167.700 ↓ 0.0 0 33,540

Hash (cost=21.50..21.50 rows=5 width=4) (actual time=0.005..0.005 rows=0 loops=33,540)

  • Buckets: 1024 Batches: 1 Memory Usage: 8kB
91. 0.000 0.000 ↓ 0.0 0 33,540

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=33,540)

  • Filter: (pc.position_description_id = job_id)
92. 134.160 134.160 ↓ 0.0 0 33,540

GroupAggregate (cost=0.00..21.57 rows=5 width=16) (actual time=0.004..0.004 rows=0 loops=33,540)

  • Group Key: onboarding_document_type.job_id
93. 0.000 0.000 ↓ 0.0 0 33,540

Seq Scan on onboarding_document_type (cost=0.00..21.50 rows=5 width=8) (actual time=0.000..0.000 rows=0 loops=33,540)

  • Filter: (job_id = pc.position_description_id)
94. 6,204.900 6,204.900 ↑ 1.0 1,989 33,540

Index Scan using candidate_gdpr_compliance_portal_status_idx on candidate_gdpr_compliance cgc (cost=0.28..122.40 rows=2,009 width=6) (actual time=0.003..0.185 rows=1,989 loops=33,540)

95. 33.540 33.540 ↑ 1.0 19 33,540

Seq Scan on offer_approval (cost=0.00..1.19 rows=19 width=12) (actual time=0.001..0.001 rows=19 loops=33,540)

96. 972.660 972.660 ↓ 1.0 352 33,540

Seq Scan on user_account approver (cost=0.00..82.51 rows=351 width=21) (actual time=0.000..0.029 rows=352 loops=33,540)