explain.depesz.com

PostgreSQL's explain analyze made readable

Result: uqeQ

Settings
# exclusive inclusive rows x rows loops node
1. 0.028 44.384 ↑ 1.0 1 1

Aggregate (cost=5,632.87..5,632.88 rows=1 width=8) (actual time=44.384..44.384 rows=1 loops=1)

2. 0.186 44.356 ↓ 2.4 446 1

Unique (cost=5,618.30..5,630.52 rows=188 width=1,204) (actual time=44.147..44.356 rows=446 loops=1)

3. 0.311 44.170 ↓ 2.4 446 1

Sort (cost=5,618.30..5,618.77 rows=188 width=1,204) (actual time=44.146..44.170 rows=446 loops=1)

  • Sort Key: scoring_item_submission.sis_id, l_1.enterprise_enrollment_id, (COALESCE(u.artifact_path, 'No artifact identifier specified'::character varying)), u.s3_version, u.file_name, scoring_item_submission.submission_status_id, (CASE WHEN scoring_item_submission.artifact_plagiarized_ind THEN 'Y'::text ELSE 'U'::text END), (CASE WHEN (NOT scoring_item_submission.sent_plagiarism_checker_ind) THEN 'N'::text WHEN scoring_item_submission.sent_plagiarism_checker_ind THEN 'Y'::text ELSE 'U'::text END), (CASE WHEN (scoring_item_submission.plagiarism_found_by_checker_ind AND scoring_item_submission.sent_plagiarism_checker_ind) THEN 'Y'::text WHEN (((NOT scoring_item_submission.plagiarism_found_by_checker_ind) OR (scoring_item_submission.plagiarism_found_by_checker_ind IS NULL)) AND scoring_item_submission.sent_plagiarism_checker_ind) THEN 'N'::text WHEN ((scoring_item_submission.sent_plagiarism_checker_ind IS NULL) OR (NOT scoring_item_submission.sent_plagiarism_checker_ind)) THEN 'N'::text ELSE 'U'::text END), (CASE WHEN scoring_item_submission.override_plagiarism_flags_ind THEN 'Y'::text ELSE 'U'::text END), (CASE WHEN scoring_item_submission.override_plagiarism_flags_ind THEN 'Y'::text WHEN (((NOT scoring_item_submission.override_plagiarism_flags_ind) OR (scoring_item_submission.override_plagiarism_flags_ind IS NULL)) AND (scoring_item_submission.plagiarism_found_by_checker_ind OR scoring_item_submission.artifact_plagiarized_ind)) THEN 'N'::text ELSE 'Y'::text END), scoring_item_submission.comments, m_1.metadata_name, (CASE WHEN ((mvr.value_name)::text = 'Other'::text) THEN ((((mvr.value_name)::text || '|'::text) || (mv.metadata_value)::text))::character varying ELSE mvr.value_name END), (CASE WHEN l_1.permission_to_reuse THEN 'N'::text ELSE 'Y'::text END), c.course_cd, (CASE WHEN ((u.create_dt IS NOT NULL) AND (u.create_dt > scoring_item_submission.create_dt)) THEN u.create_dt ELSE scoring_item_submission.create_dt END), (CASE WHEN ((u.update_dt IS NOT NULL) AND (u.update_dt > scoring_item_submission.update_dt)) THEN u.update_dt ELSE scoring_item_submission.update_dt END), (CASE WHEN l_1.exam_intent_ind THEN 'Y'::text ELSE CASE WHEN (NOT l_1.exam_intent_ind) THEN 'N'::text ELSE 'U'::text END END), scoring_item_submission.assignment_id, y.lesson_id, z.dp_module_id, scoring_item_submission.enrollment_id, p.dp_person_id, s.enterprise_org_id
  • Sort Method: quicksort Memory: 177kB
4. 0.249 43.859 ↓ 2.4 446 1

Hash Left Join (cost=4,649.50..5,611.20 rows=188 width=1,204) (actual time=40.868..43.859 rows=446 loops=1)

  • Hash Cond: (y.dp_module_id = z.dp_module_id)
5. 0.138 43.586 ↓ 2.4 446 1

Hash Left Join (cost=4,642.68..5,601.51 rows=188 width=1,072) (actual time=40.831..43.586 rows=446 loops=1)

  • Hash Cond: (x.lesson_id = y.lesson_id)
6. 0.129 43.404 ↓ 2.4 446 1

Hash Left Join (cost=4,631.82..5,590.15 rows=188 width=1,064) (actual time=40.780..43.404 rows=446 loops=1)

  • Hash Cond: (scoring_item_submission.assignment_id = x.assignment_id)
7. 0.142 43.240 ↓ 2.4 446 1

Hash Left Join (cost=4,627.32..5,585.14 rows=188 width=1,056) (actual time=40.740..43.240 rows=446 loops=1)

  • Hash Cond: (scoring_item_submission.sis_id = mv.sis_id)
  • Filter: (m_1.ap31_ind OR (m_1.ap31_ind IS NULL))
  • Rows Removed by Filter: 13
8. 0.356 42.628 ↓ 1.2 446 1

Nested Loop Left Join (cost=4,584.24..5,539.12 rows=376 width=1,024) (actual time=40.261..42.628 rows=446 loops=1)

9. 0.157 42.272 ↓ 1.2 446 1

Nested Loop (cost=4,583.96..5,422.65 rows=376 width=365) (actual time=40.256..42.272 rows=446 loops=1)

10. 0.258 41.669 ↓ 1.2 446 1

Nested Loop (cost=4,583.67..4,820.16 rows=376 width=365) (actual time=40.252..41.669 rows=446 loops=1)

11. 0.383 40.965 ↓ 1.1 446 1

Hash Join (cost=4,583.39..4,640.27 rows=389 width=365) (actual time=40.240..40.965 rows=446 loops=1)

  • Hash Cond: (l_1.enrollment_id = scoring_item_submission.enrollment_id)
12. 1.086 32.949 ↑ 1.9 1,155 1

HashAggregate (cost=4,342.16..4,364.47 rows=2,231 width=312) (actual time=32.591..32.949 rows=1,155 loops=1)

  • Group Key: l_1.enterprise_enrollment_id, l_1.apro_enrollment_id, l_1.dp_person_id, l_1.enrollment_id, l_1.exam_intent_ind, l_1.permission_to_reuse, l_1.enrollment_role_id, l_1.status_id, l_1.section_id
13. 0.161 31.863 ↑ 1.3 1,727 1

Append (cost=1,404.77..4,291.96 rows=2,231 width=312) (actual time=4.758..31.863 rows=1,727 loops=1)

14. 0.507 9.711 ↓ 431.0 431 1

Nested Loop (cost=1,404.77..1,814.21 rows=1 width=71) (actual time=4.757..9.711 rows=431 loops=1)

  • Join Filter: (b.course_instance_id = m_2.course_instance_id)
  • Rows Removed by Join Filter: 742
15. 0.163 8.031 ↓ 146.6 1,173 1

Nested Loop (cost=1,404.48..1,790.67 rows=8 width=79) (actual time=4.745..8.031 rows=1,173 loops=1)

16. 0.290 4.851 ↓ 61.6 431 1

HashAggregate (cost=1,404.19..1,421.92 rows=7 width=24) (actual time=4.733..4.851 rows=431 loops=1)

  • Group Key: a_1.dp_person_id, b.course_instance_id
  • Filter: (count(*) = 1)
  • Rows Removed by Filter: 103
17. 0.152 4.561 ↑ 2.2 649 1

Hash Join (cost=1,004.01..1,393.56 rows=1,418 width=16) (actual time=3.298..4.561 rows=649 loops=1)

  • Hash Cond: (a_1.section_id = b.section_id)
18. 1.162 1.418 ↑ 2.2 649 1

Bitmap Heap Scan on enrollment a_1 (cost=139.56..525.39 rows=1,418 width=16) (actual time=0.285..1.418 rows=649 loops=1)

  • Recheck Cond: (apro_enrollment_id IS NOT NULL)
  • Filter: ((status_id = ANY ('{4,5}'::integer[])) AND (enrollment_role_id = 2))
  • Rows Removed by Filter: 5105
  • Heap Blocks: exact=237
19. 0.256 0.256 ↓ 1.2 6,636 1

Bitmap Index Scan on uk_apro_enrollment_id (cost=0.00..139.20 rows=5,722 width=0) (actual time=0.256..0.256 rows=6,636 loops=1)

  • Index Cond: (apro_enrollment_id IS NOT NULL)
20. 1.225 2.991 ↓ 1.0 11,352 1

Hash (cost=729.20..729.20 rows=10,820 width=16) (actual time=2.990..2.991 rows=11,352 loops=1)

  • Buckets: 16384 Batches: 1 Memory Usage: 661kB
21. 1.766 1.766 ↓ 1.0 11,352 1

Seq Scan on section b (cost=0.00..729.20 rows=10,820 width=16) (actual time=0.009..1.766 rows=11,352 loops=1)

22. 3.017 3.017 ↓ 3.0 3 431

Index Scan using ix_enrollment_person_id on enrollment l_1 (cost=0.29..52.66 rows=1 width=71) (actual time=0.002..0.007 rows=3 loops=431)

  • Index Cond: (dp_person_id = a_1.dp_person_id)
  • Filter: ((apro_enrollment_id IS NOT NULL) AND (status_id = ANY ('{4,5}'::integer[])) AND (status_id = ANY ('{4,5}'::integer[])) AND (enrollment_role_id = 2))
  • Rows Removed by Filter: 14
23. 1.173 1.173 ↑ 1.0 1 1,173

Index Scan using pk_section on section m_2 (cost=0.29..2.93 rows=1 width=16) (actual time=0.001..0.001 rows=1 loops=1,173)

  • Index Cond: (section_id = l_1.section_id)
24. 2.909 2.909 ↑ 3.6 612 1

Seq Scan on enrollment (cost=0.00..622.30 rows=2,229 width=71) (actual time=0.124..2.909 rows=612 loops=1)

  • Filter: ((apro_enrollment_id IS NULL) AND (status_id = ANY ('{4,5}'::integer[])) AND (status_id = ANY ('{4,5}'::integer[])) AND (enrollment_role_id = 2))
  • Rows Removed by Filter: 17908
25. 2.390 19.082 ↓ 684.0 684 1

Nested Loop (cost=1,405.34..1,821.99 rows=1 width=71) (actual time=4.994..19.082 rows=684 loops=1)

  • Join Filter: (b_1.course_instance_id = s_1.course_instance_id)
  • Rows Removed by Join Filter: 5255
26. 0.774 10.753 ↓ 989.8 5,939 1

Nested Loop (cost=1,405.05..1,816.82 rows=6 width=96) (actual time=4.986..10.753 rows=5,939 loops=1)

  • Join Filter: (a_2.dp_person_id = r.dp_person_id)
27. 0.118 7.675 ↓ 96.0 96 1

Nested Loop (cost=1,404.77..1,797.96 rows=1 width=95) (actual time=4.979..7.675 rows=96 loops=1)

  • Join Filter: (b_1.course_instance_id = m_3.course_instance_id)
  • Rows Removed by Join Filter: 168
28. 0.053 7.293 ↓ 264.0 264 1

Nested Loop (cost=1,404.48..1,790.67 rows=1 width=87) (actual time=4.973..7.293 rows=264 loops=1)

29. 0.261 5.055 ↓ 13.6 95 1

HashAggregate (cost=1,404.19..1,421.92 rows=7 width=24) (actual time=4.960..5.055 rows=95 loops=1)

  • Group Key: a_2.dp_person_id, b_1.course_instance_id
  • Filter: (count(*) = 2)
  • Rows Removed by Filter: 439
30. 0.156 4.794 ↑ 2.2 649 1

Hash Join (cost=1,004.01..1,393.56 rows=1,418 width=16) (actual time=3.708..4.794 rows=649 loops=1)

  • Hash Cond: (a_2.section_id = b_1.section_id)
31. 0.983 1.264 ↑ 2.2 649 1

Bitmap Heap Scan on enrollment a_2 (cost=139.56..525.39 rows=1,418 width=16) (actual time=0.309..1.264 rows=649 loops=1)

  • Recheck Cond: (apro_enrollment_id IS NOT NULL)
  • Filter: ((status_id = ANY ('{4,5}'::integer[])) AND (enrollment_role_id = 2))
  • Rows Removed by Filter: 5105
  • Heap Blocks: exact=237
32. 0.281 0.281 ↓ 1.2 6,636 1

Bitmap Index Scan on uk_apro_enrollment_id (cost=0.00..139.20 rows=5,722 width=0) (actual time=0.281..0.281 rows=6,636 loops=1)

  • Index Cond: (apro_enrollment_id IS NOT NULL)
33. 1.495 3.374 ↓ 1.0 11,352 1

Hash (cost=729.20..729.20 rows=10,820 width=16) (actual time=3.374..3.374 rows=11,352 loops=1)

  • Buckets: 16384 Batches: 1 Memory Usage: 661kB
34. 1.879 1.879 ↓ 1.0 11,352 1

Seq Scan on section b_1 (cost=0.00..729.20 rows=10,820 width=16) (actual time=0.006..1.879 rows=11,352 loops=1)

35. 2.185 2.185 ↓ 3.0 3 95

Index Scan using ix_enrollment_person_id on enrollment l_2 (cost=0.29..52.66 rows=1 width=71) (actual time=0.003..0.023 rows=3 loops=95)

  • Index Cond: (dp_person_id = a_2.dp_person_id)
  • Filter: ((apro_enrollment_id IS NOT NULL) AND (is_primary_ind IS TRUE) AND (status_id = ANY ('{4,5}'::integer[])) AND (status_id = ANY ('{4,5}'::integer[])) AND (enrollment_role_id = 2))
  • Rows Removed by Filter: 63
36. 0.264 0.264 ↑ 1.0 1 264

Index Scan using pk_section on section m_3 (cost=0.29..7.27 rows=1 width=16) (actual time=0.001..0.001 rows=1 loops=264)

  • Index Cond: (section_id = l_2.section_id)
37. 2.304 2.304 ↓ 10.3 62 96

Index Scan using ix_enrollment_person_id on enrollment r (cost=0.29..18.79 rows=6 width=17) (actual time=0.002..0.024 rows=62 loops=96)

  • Index Cond: (dp_person_id = l_2.dp_person_id)
  • Filter: (is_primary_ind IS FALSE)
  • Rows Removed by Filter: 3
38. 5.939 5.939 ↑ 1.0 1 5,939

Index Scan using pk_section on section s_1 (cost=0.29..0.85 rows=1 width=16) (actual time=0.001..0.001 rows=1 loops=5,939)

  • Index Cond: (section_id = r.section_id)
39. 1.975 7.633 ↓ 8.4 9,529 1

Hash (cost=227.09..227.09 rows=1,132 width=73) (actual time=7.633..7.633 rows=9,529 loops=1)

  • Buckets: 16384 (originally 2048) Batches: 1 (originally 1) Memory Usage: 1023kB
40. 1.672 5.658 ↓ 8.4 9,529 1

Nested Loop (cost=6.77..227.09 rows=1,132 width=73) (actual time=0.130..5.658 rows=9,529 loops=1)

41. 0.004 0.178 ↓ 3.4 17 1

Nested Loop (cost=6.48..16.32 rows=5 width=23) (actual time=0.079..0.178 rows=17 loops=1)

42. 0.002 0.157 ↓ 3.4 17 1

Nested Loop (cost=6.34..15.16 rows=5 width=15) (actual time=0.076..0.157 rows=17 loops=1)

43. 0.008 0.138 ↓ 3.4 17 1

Nested Loop (cost=6.20..14.11 rows=5 width=19) (actual time=0.072..0.138 rows=17 loops=1)

44. 0.004 0.113 ↓ 2.8 17 1

Nested Loop (cost=6.06..12.28 rows=6 width=15) (actual time=0.069..0.113 rows=17 loops=1)

45. 0.003 0.089 ↓ 2.5 10 1

Nested Loop (cost=5.92..9.49 rows=4 width=15) (actual time=0.065..0.089 rows=10 loops=1)

46. 0.027 0.071 ↓ 2.5 5 1

Hash Join (cost=5.78..7.54 rows=2 width=15) (actual time=0.058..0.071 rows=5 loops=1)

  • Hash Cond: (lower((c.course_cd)::text) = lower((ci.course_cd)::text))
47. 0.009 0.009 ↑ 1.0 46 1

Seq Scan on course c (cost=0.00..1.46 rows=46 width=2) (actual time=0.005..0.009 rows=46 loops=1)

48. 0.007 0.035 ↓ 2.5 5 1

Hash (cost=5.75..5.75 rows=2 width=15) (actual time=0.035..0.035 rows=5 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
49. 0.010 0.028 ↓ 2.5 5 1

Hash Join (cost=1.27..5.75 rows=2 width=15) (actual time=0.019..0.028 rows=5 loops=1)

  • Hash Cond: (ci.education_period_cd = ep.education_period_cd)
50. 0.009 0.009 ↓ 1.0 37 1

Seq Scan on course_instance ci (cost=0.00..4.36 rows=36 width=14) (actual time=0.004..0.009 rows=37 loops=1)

51. 0.001 0.009 ↑ 1.0 1 1

Hash (cost=1.26..1.26 rows=1 width=9) (actual time=0.009..0.009 rows=1 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
52. 0.008 0.008 ↑ 1.0 1 1

Seq Scan on education_period ep (cost=0.00..1.26 rows=1 width=9) (actual time=0.007..0.008 rows=1 loops=1)

  • Filter: ((ap_admin_yr)::text = '2020'::text)
  • Rows Removed by Filter: 20
53. 0.015 0.015 ↑ 1.0 2 5

Index Scan using ix_dp_module_course_instance_id on dp_module m (cost=0.14..0.96 rows=2 width=16) (actual time=0.002..0.003 rows=2 loops=5)

  • Index Cond: (course_instance_id = ci.course_instance_id)
54. 0.020 0.020 ↑ 1.0 2 10

Index Scan using ix_lesson_dp_module_id on lesson l (cost=0.14..0.68 rows=2 width=16) (actual time=0.001..0.002 rows=2 loops=10)

  • Index Cond: (dp_module_id = m.dp_module_id)
  • Filter: ((submission_type)::text = 'Individual'::text)
  • Rows Removed by Filter: 0
55. 0.017 0.017 ↑ 1.0 1 17

Index Scan using ix_assignment_lesson_id on assignment aa (cost=0.14..0.29 rows=1 width=20) (actual time=0.001..0.001 rows=1 loops=17)

  • Index Cond: (lesson_id = l.lesson_id)
56. 0.017 0.017 ↑ 1.0 1 17

Index Only Scan using pk_assignment_type on assignment_type at (cost=0.14..0.22 rows=1 width=4) (actual time=0.001..0.001 rows=1 loops=17)

  • Index Cond: (assignment_type_id = aa.assignment_type_id)
  • Heap Fetches: 0
57. 0.017 0.017 ↑ 1.0 1 17

Index Only Scan using pk_assignment on assignment a (cost=0.14..0.23 rows=1 width=8) (actual time=0.001..0.001 rows=1 loops=17)

  • Index Cond: (assignment_id = aa.assignment_id)
  • Heap Fetches: 17
58. 3.808 3.808 ↑ 1.3 561 17

Index Scan using ix_sis_assignment_enrollment on scoring_item_submission (cost=0.29..34.76 rows=739 width=66) (actual time=0.002..0.224 rows=561 loops=17)

  • Index Cond: (assignment_id = a.assignment_id)
  • Filter: (submission_status_id <> 6)
  • Rows Removed by Filter: 13
59. 0.446 0.446 ↑ 1.0 1 446

Index Scan using pk_dp_person on dp_person p (cost=0.28..0.46 rows=1 width=8) (actual time=0.001..0.001 rows=1 loops=446)

  • Index Cond: (dp_person_id = l_1.dp_person_id)
  • Filter: (NOT test_ind)
60. 0.446 0.446 ↑ 1.0 1 446

Index Scan using pk_section on section s (cost=0.29..1.60 rows=1 width=16) (actual time=0.001..0.001 rows=1 loops=446)

  • Index Cond: (section_id = l_1.section_id)
61. 0.000 0.000 ↓ 0.0 0 446

Index Scan using pk_upload on upload u (cost=0.28..0.31 rows=1 width=675) (actual time=0.000..0.000 rows=0 loops=446)

  • Index Cond: (upload_id = scoring_item_submission.upload_id)
62. 0.083 0.470 ↑ 1.4 536 1

Hash (cost=33.82..33.82 rows=741 width=41) (actual time=0.470..0.470 rows=536 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 47kB
63. 0.129 0.387 ↑ 1.4 536 1

Hash Join (cost=4.97..33.82 rows=741 width=41) (actual time=0.063..0.387 rows=536 loops=1)

  • Hash Cond: ((mv.metadata_id = atm.metadata_id) AND (mv.assignment_type_id = atm.assignment_type_id))
64. 0.160 0.231 ↑ 1.4 536 1

Hash Join (cost=1.65..20.12 rows=741 width=36) (actual time=0.031..0.231 rows=536 loops=1)

  • Hash Cond: ((mv.metadata_id = mvr.metadata_id) AND (mv.value_range_id = mvr.value_range_id))
65. 0.056 0.056 ↑ 1.0 733 1

Seq Scan on metadata_value mv (cost=0.00..14.41 rows=741 width=25) (actual time=0.009..0.056 rows=733 loops=1)

66. 0.007 0.015 ↑ 1.0 26 1

Hash (cost=1.26..1.26 rows=26 width=19) (actual time=0.015..0.015 rows=26 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 10kB
67. 0.008 0.008 ↑ 1.0 26 1

Seq Scan on metadata_value_range mvr (cost=0.00..1.26 rows=26 width=19) (actual time=0.004..0.008 rows=26 loops=1)

68. 0.002 0.027 ↑ 1.0 4 1

Hash (cost=3.26..3.26 rows=4 width=29) (actual time=0.027..0.027 rows=4 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
69. 0.005 0.025 ↑ 1.0 4 1

Hash Join (cost=2.18..3.26 rows=4 width=29) (actual time=0.022..0.025 rows=4 loops=1)

  • Hash Cond: (m_1.metadata_type_id = mt.metadata_type_id)
70. 0.006 0.015 ↑ 1.0 4 1

Hash Join (cost=1.09..2.15 rows=4 width=33) (actual time=0.013..0.015 rows=4 loops=1)

  • Hash Cond: (atm.metadata_id = m_1.metadata_id)
71. 0.003 0.003 ↑ 1.0 4 1

Seq Scan on assignment_type_metadata atm (cost=0.00..1.04 rows=4 width=8) (actual time=0.002..0.003 rows=4 loops=1)

72. 0.001 0.006 ↑ 1.0 4 1

Hash (cost=1.04..1.04 rows=4 width=25) (actual time=0.006..0.006 rows=4 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
73. 0.005 0.005 ↑ 1.0 4 1

Seq Scan on metadata m_1 (cost=0.00..1.04 rows=4 width=25) (actual time=0.003..0.005 rows=4 loops=1)

74. 0.002 0.005 ↑ 1.0 4 1

Hash (cost=1.04..1.04 rows=4 width=4) (actual time=0.005..0.005 rows=4 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
75. 0.003 0.003 ↑ 1.0 4 1

Seq Scan on metadata_type mt (cost=0.00..1.04 rows=4 width=4) (actual time=0.003..0.003 rows=4 loops=1)

76. 0.015 0.035 ↓ 1.2 129 1

Hash (cost=3.11..3.11 rows=111 width=16) (actual time=0.035..0.035 rows=129 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 15kB
77. 0.020 0.020 ↓ 1.2 129 1

Seq Scan on assignment x (cost=0.00..3.11 rows=111 width=16) (actual time=0.003..0.020 rows=129 loops=1)

78. 0.020 0.044 ↓ 1.0 129 1

Hash (cost=9.27..9.27 rows=127 width=16) (actual time=0.044..0.044 rows=129 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 15kB
79. 0.024 0.024 ↓ 1.0 129 1

Seq Scan on lesson y (cost=0.00..9.27 rows=127 width=16) (actual time=0.003..0.024 rows=129 loops=1)

80. 0.008 0.024 ↑ 1.1 75 1

Hash (cost=5.81..5.81 rows=81 width=8) (actual time=0.024..0.024 rows=75 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 11kB
81. 0.016 0.016 ↑ 1.1 75 1

Seq Scan on dp_module z (cost=0.00..5.81 rows=81 width=8) (actual time=0.004..0.016 rows=75 loops=1)