explain.depesz.com

PostgreSQL's explain analyze made readable

Result: cdtI

Settings
# exclusive inclusive rows x rows loops node
1. 0.003 10,467.188 ↓ 3.3 20 1

Limit (cost=1,903,402.37..1,903,408.88 rows=6 width=602) (actual time=10,467.017..10,467.188 rows=20 loops=1)

2. 0.208 10,467.185 ↓ 3.0 21 1

GroupAggregate (cost=1,903,401.29..1,903,408.88 rows=7 width=602) (actual time=10,467.007..10,467.185 rows=21 loops=1)

3. 0.134 10,466.977 ↓ 3.4 24 1

Sort (cost=1,903,401.29..1,903,401.30 rows=7 width=602) (actual time=10,466.976..10,466.977 rows=24 loops=1)

  • Sort Key: foo.sample_date_time, foo.sample_sno, foo.sample_assertion_batch, foo.sample_type, foo.sample_date, foo.collection_center, foo.mr_no, foo.patient_id, foo.sample_qty, foo.ih_name, foo.sample_status, foo.assertion_time, foo.rejected_time, foo.conducted, foo.sample_type_id, foo.collection_center_id, foo.visit_type, foo.center_id, foo.sample_collection_id, foo.patient_name, foo.outsource_dest_id, foo.outsource_name, foo.orig_sample_no, foo.transfer_time, foo.transfer_other_details, foo.receipt_time, foo.receipt_other_details, foo.bill_status, foo.charge_head
  • Sort Method: quicksort Memory: 45kB
4. 0.007 10,466.843 ↓ 8.7 61 1

Subquery Scan on foo (cost=1,903,397.51..1,903,401.19 rows=7 width=602) (actual time=10,466.812..10,466.843 rows=61 loops=1)

5. 0.261 10,466.836 ↓ 8.7 61 1

HashAggregate (cost=1,903,397.51..1,903,401.12 rows=7 width=366) (actual time=10,466.811..10,466.836 rows=61 loops=1)

6. 4.732 10,466.575 ↓ 9.6 67 1

Nested Loop (cost=1,034,508.20..1,903,396.87 rows=7 width=366) (actual time=9,158.374..10,466.575 rows=67 loops=1)

7. 0.060 10,461.642 ↓ 9.6 67 1

Nested Loop (cost=1,034,507.93..1,903,384.66 rows=7 width=351) (actual time=9,158.204..10,461.642 rows=67 loops=1)

8. 0.030 10,460.979 ↓ 9.6 67 1

Nested Loop (cost=1,034,507.37..1,903,373.44 rows=7 width=363) (actual time=9,158.187..10,460.979 rows=67 loops=1)

9. 0.080 10,460.346 ↓ 9.6 67 1

Nested Loop (cost=1,034,506.81..1,903,358.14 rows=7 width=353) (actual time=9,158.172..10,460.346 rows=67 loops=1)

10. 0.077 10,459.730 ↓ 9.6 67 1

Nested Loop Left Join (cost=1,034,506.36..1,903,340.58 rows=7 width=351) (actual time=9,158.155..10,459.730 rows=67 loops=1)

11. 0.085 10,459.653 ↓ 9.6 67 1

Nested Loop Left Join (cost=1,034,505.93..1,903,331.22 rows=7 width=346) (actual time=9,158.152..10,459.653 rows=67 loops=1)

12. 0.092 10,459.568 ↓ 9.6 67 1

Nested Loop Left Join (cost=1,034,505.50..1,903,315.62 rows=7 width=346) (actual time=9,158.149..10,459.568 rows=67 loops=1)

  • Join Filter: (scc.collection_center_id = pr.collection_center_id)
13. 0.068 10,459.476 ↓ 9.6 67 1

Nested Loop Left Join (cost=1,034,505.50..1,903,314.50 rows=7 width=337) (actual time=9,158.142..10,459.476 rows=67 loops=1)

14. 0.054 10,459.408 ↓ 9.6 67 1

Nested Loop Left Join (cost=1,034,505.36..1,903,313.34 rows=7 width=334) (actual time=9,158.139..10,459.408 rows=67 loops=1)

  • Join Filter: ((isr.incoming_visit_id)::text = (isrd.incoming_visit_id)::text)
15. 0.085 10,459.153 ↓ 9.6 67 1

Nested Loop Left Join (cost=1,034,504.94..1,903,304.35 rows=7 width=317) (actual time=9,158.130..10,459.153 rows=67 loops=1)

16. 0.062 10,458.934 ↓ 9.6 67 1

Nested Loop Left Join (cost=1,034,504.80..1,903,303.20 rows=7 width=321) (actual time=9,158.122..10,458.934 rows=67 loops=1)

17. 0.100 10,458.202 ↓ 9.6 67 1

Nested Loop (cost=1,034,504.37..1,903,293.54 rows=7 width=288) (actual time=9,158.104..10,458.202 rows=67 loops=1)

18. 0.264 10,457.968 ↓ 9.6 67 1

Nested Loop Left Join (cost=1,034,504.24..1,903,292.34 rows=7 width=275) (actual time=9,158.097..10,457.968 rows=67 loops=1)

  • Filter: (COALESCE(pr.center_id, isr.center_id) = 13)
  • Rows Removed by Filter: 327
19. 0.478 10,456.916 ↑ 3.4 394 1

Nested Loop Left Join (cost=1,034,503.82..1,901,475.38 rows=1,325 width=228) (actual time=9,158.084..10,456.916 rows=394 loops=1)

20. 0.098 10,453.680 ↑ 3.4 394 1

Hash Left Join (cost=1,034,503.38..1,895,252.96 rows=1,325 width=187) (actual time=9,158.057..10,453.680 rows=394 loops=1)

  • Hash Cond: ((dom.outsource_dest)::text = (hcm.center_id)::text)
21. 0.150 10,453.564 ↑ 3.4 394 1

Hash Left Join (cost=1,034,498.87..1,895,235.61 rows=1,325 width=184) (actual time=9,158.032..10,453.564 rows=394 loops=1)

  • Hash Cond: ((dom.outsource_dest)::text = (om.oh_id)::text)
22. 0.374 10,453.394 ↑ 3.4 394 1

Hash Join (cost=1,034,496.54..1,895,216.64 rows=1,325 width=171) (actual time=9,158.001..10,453.394 rows=394 loops=1)

  • Hash Cond: ((COALESCE(tp.test_id, tpr.test_id))::text = (d.test_id)::text)
23. 707.683 10,451.657 ↑ 3.4 394 1

Hash Left Join (cost=1,033,946.08..1,894,646.31 rows=1,325 width=138) (actual time=9,156.623..10,451.657 rows=394 loops=1)

  • Hash Cond: ((CASE WHEN (sc.sample_status = 'R'::bpchar) THEN sr.test_prescribed_id ELSE sc.sample_collection_id END = tpr.prescribed_id) AND ("substring"((sc.patient_id)::text, 5, 2) = "substring"((tpr.pat_id)::text, 5, 2)))
  • Filter: ((CASE WHEN (sc.sample_status = 'R'::bpchar) THEN tpr.conducted ELSE tp.conducted END)::text = ANY ('{N,NRN}'::text[]))
  • Rows Removed by Filter: 72
24. 587.787 5,793.105 ↑ 284.3 466 1

Hash Left Join (cost=592,547.28..1,389,150.85 rows=132,504 width=129) (actual time=5,205.506..5,793.105 rows=466 loops=1)

  • Hash Cond: ((CASE WHEN (sc.sample_status = 'R'::bpchar) THEN sr.test_prescribed_id ELSE sc.sample_collection_id END = tp.sample_collection_id) AND ("substring"((sc.patient_id)::text, 5, 2) = "substring"((tp.pat_id)::text, 5, 2)))
25. 2.201 596.202 ↑ 515.6 257 1

Hash Right Join (cost=143,773.48..144,500.92 rows=132,504 width=114) (actual time=596.090..596.202 rows=257 loops=1)

  • Hash Cond: (sr.sample_collection_id = sc.sample_collection_id)
26. 1.308 1.308 ↑ 1.0 25,665 1

Seq Scan on sample_rejections sr (cost=0.00..395.65 rows=25,665 width=8) (actual time=0.003..1.308 rows=25,665 loops=1)

27. 0.149 592.693 ↑ 515.6 257 1

Hash (cost=142,117.18..142,117.18 rows=132,504 width=110) (actual time=592.693..592.693 rows=257 loops=1)

  • Buckets: 16384 Batches: 1 Memory Usage: 27kB
28. 0.913 592.544 ↑ 515.6 257 1

Hash Left Join (cost=2.51..142,117.18 rows=132,504 width=110) (actual time=525.112..592.544 rows=257 loops=1)

  • Hash Cond: (sc.outsource_dest_id = dom.outsource_dest_id)
  • Filter: ((dom.outsource_dest_type IS NULL) OR (dom.outsource_dest_type <> 'C'::bpchar))
  • Rows Removed by Filter: 3891
29. 591.609 591.609 ↑ 36.3 4,148 1

Seq Scan on sample_collection sc (cost=0.00..141,225.46 rows=150,471 width=101) (actual time=364.654..591.609 rows=4,148 loops=1)

  • Filter: ((sample_status = 'C'::bpchar) AND (sample_receive_status = 'R'::bpchar) AND (sample_status = ANY ('{C,A,R}'::bpchar[])) AND ((sample_date)::date >= '2018-12-29'::date))
  • Rows Removed by Filter: 3095660
30. 0.010 0.022 ↑ 1.0 67 1

Hash (cost=1.67..1.67 rows=67 width=15) (actual time=0.022..0.022 rows=67 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 4kB
31. 0.012 0.012 ↑ 1.0 67 1

Seq Scan on diag_outsource_master dom (cost=0.00..1.67 rows=67 width=15) (actual time=0.004..0.012 rows=67 loops=1)

32. 2,401.997 4,609.116 ↑ 1.2 6,466,842 1

Hash (cost=276,500.72..276,500.72 rows=7,551,672 width=34) (actual time=4,609.116..4,609.116 rows=6,466,842 loops=1)

  • Buckets: 131072 Batches: 16 Memory Usage: 26821kB
33. 2,207.119 2,207.119 ↓ 1.0 7,554,345 1

Seq Scan on tests_prescribed tp (cost=0.00..276,500.72 rows=7,551,672 width=34) (actual time=0.004..2,207.119 rows=7,554,345 loops=1)

34. 2,499.722 3,950.869 ↓ 1.0 7,554,345 1

Hash (cost=276,500.72..276,500.72 rows=7,551,672 width=30) (actual time=3,950.869..3,950.869 rows=7,554,345 loops=1)

  • Buckets: 131072 Batches: 16 Memory Usage: 30135kB
35. 1,451.147 1,451.147 ↓ 1.0 7,554,345 1

Seq Scan on tests_prescribed tpr (cost=0.00..276,500.72 rows=7,551,672 width=30) (actual time=0.004..1,451.147 rows=7,554,345 loops=1)

36. 0.527 1.363 ↑ 1.0 1,798 1

Hash (cost=527.98..527.98 rows=1,798 width=49) (actual time=1.363..1.363 rows=1,798 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 143kB
37. 0.836 0.836 ↑ 1.0 1,798 1

Seq Scan on diagnostics d (cost=0.00..527.98 rows=1,798 width=49) (actual time=0.005..0.836 rows=1,798 loops=1)

38. 0.008 0.020 ↑ 1.0 59 1

Hash (cost=1.59..1.59 rows=59 width=24) (actual time=0.020..0.020 rows=59 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 4kB
39. 0.012 0.012 ↑ 1.0 59 1

Seq Scan on outhouse_master om (cost=0.00..1.59 rows=59 width=24) (actual time=0.003..0.012 rows=59 loops=1)

40. 0.005 0.018 ↑ 1.0 23 1

Hash (cost=4.23..4.23 rows=23 width=16) (actual time=0.018..0.018 rows=23 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 2kB
41. 0.013 0.013 ↑ 1.0 23 1

Seq Scan on hospital_center_master hcm (cost=0.00..4.23 rows=23 width=16) (actual time=0.003..0.013 rows=23 loops=1)

42. 2.758 2.758 ↑ 1.0 1 394

Index Scan using patient_registration_pkey on patient_registration pr (cost=0.43..4.69 rows=1 width=41) (actual time=0.007..0.007 rows=1 loops=394)

  • Index Cond: ((patient_id)::text = (sc.patient_id)::text)
43. 0.788 0.788 ↓ 0.0 0 394

Index Scan using incoming_sample_registration_pkey on incoming_sample_registration isr (cost=0.42..1.36 rows=1 width=62) (actual time=0.002..0.002 rows=0 loops=394)

  • Index Cond: ((sc.patient_id)::text = (incoming_visit_id)::text)
44. 0.134 0.134 ↑ 1.0 1 67

Index Scan using diagnostics_departments_pkey on diagnostics_departments (cost=0.14..0.16 rows=1 width=23) (actual time=0.002..0.002 rows=1 loops=67)

  • Index Cond: ((ddept_id)::text = (d.ddept_id)::text)
45. 0.670 0.670 ↑ 1.0 1 67

Index Scan using patient_details_pkey on patient_details pd (cost=0.43..1.37 rows=1 width=48) (actual time=0.010..0.010 rows=1 loops=67)

  • Index Cond: ((mr_no)::text = (pr.mr_no)::text)
46. 0.134 0.134 ↑ 1.0 1 67

Index Scan using salutation_master_pkey on salutation_master sm (cost=0.14..0.16 rows=1 width=14) (actual time=0.002..0.002 rows=1 loops=67)

  • Index Cond: ((salutation_id)::text = (pd.salutation)::text)
47. 0.201 0.201 ↓ 0.0 0 67

Index Scan using incoming_sample_registration_details_pkey on incoming_sample_registration_details isrd (cost=0.42..1.27 rows=1 width=30) (actual time=0.003..0.003 rows=0 loops=67)

  • Index Cond: (tp.prescribed_id = prescribed_id)
48. 0.000 0.000 ↓ 0.0 0 67

Index Scan using incoming_hospitals_pkey on incoming_hospitals ih (cost=0.14..0.16 rows=1 width=17) (actual time=0.000..0.000 rows=0 loops=67)

  • Index Cond: ((hospital_id)::text = (isr.orig_lab_name)::text)
49. 0.000 0.000 ↑ 1.0 1 67

Materialize (cost=0.00..1.01 rows=1 width=13) (actual time=0.000..0.000 rows=1 loops=67)

50. 0.002 0.002 ↑ 1.0 1 1

Seq Scan on sample_collection_centers scc (cost=0.00..1.01 rows=1 width=13) (actual time=0.002..0.002 rows=1 loops=1)

51. 0.000 0.000 ↓ 0.0 0 67

Index Scan using tests_prescribed_pkey on tests_prescribed tp1 (cost=0.43..2.22 rows=1 width=8) (actual time=0.000..0.000 rows=0 loops=67)

  • Index Cond: (prescribed_id = isrd.source_test_prescribed)
52. 0.000 0.000 ↓ 0.0 0 67

Index Scan using sample_collection_id_pkey on sample_collection sc1 (cost=0.43..1.33 rows=1 width=13) (actual time=0.000..0.000 rows=0 loops=67)

  • Index Cond: (sample_collection_id = tp1.sample_collection_id)
53. 0.536 0.536 ↑ 1.0 1 67

Index Scan using bac_activity_id_index on bill_activity_charge bac (cost=0.45..2.50 rows=1 width=17) (actual time=0.008..0.008 rows=1 loops=67)

  • Index Cond: (COALESCE((tp.prescribed_id)::text, (tpr.prescribed_id)::text) = (activity_id)::text)
  • Filter: ((activity_code)::text = 'DIA'::text)
54. 0.603 0.603 ↑ 1.0 1 67

Index Scan using bill_charge_pkey on bill_charge bc (cost=0.56..2.18 rows=1 width=30) (actual time=0.008..0.009 rows=1 loops=67)

  • Index Cond: ((charge_id)::text = (bac.charge_id)::text)
55. 0.603 0.603 ↑ 1.0 1 67

Index Scan using bill_pkey on bill b (cost=0.56..1.59 rows=1 width=16) (actual time=0.009..0.009 rows=1 loops=67)

  • Index Cond: ((bill_no)::text = (bc.bill_no)::text)
56. 0.201 0.201 ↑ 1.0 1 67

Index Scan using sample_type_pkey on sample_type st (cost=0.27..1.23 rows=1 width=19) (actual time=0.002..0.003 rows=1 loops=67)

  • Index Cond: (sample_type_id = sc.sample_type_id)