explain.depesz.com

PostgreSQL's explain analyze made readable

Result: lIoW

Settings
# exclusive inclusive rows x rows loops node
1. 9.064 79.564 ↓ 19.6 1,372 1

Hash Left Join (cost=4,796.16..8,035.38 rows=70 width=634) (actual time=8.165..79.564 rows=1,372 loops=1)

  • Output: pep.employee_id, (SubPlan 7), sec_org.short_name, concat_ws(' '::text, CASE WHEN (prm.dep IS NULL) THEN (('<i>'::text || (COALESCE(pd.dep_name, 'Hе указано'::character varying))::text) || '</i>,'::text) ELSE NULL::text END, i.surname, i.name, i.patr_name, (', ТН: '::text || NULLIF((pe.number)::text, ''::text))), (((cat.e_code)::text = '1'::text) OR (((cat.e_code)::text = '10'::text) AND ((r.e_code)::text = ANY ('{10002,10003,10233,10235}'::text[])))), ((cat.e_code)::text = ANY ('{2,3}'::text[])), ((prm.d2 >= pep.start_date) AND (prm.d2 <= COALESCE((pep.end_date - 1), prm.d2))), ((prm.d2_last >= pep.start_date) AND (prm.d2_last <= COALESCE((pep.end_date - 1), prm.d2_last)))
  • Hash Cond: (pp.department_id = pd.id)
  • Buffers: shared hit=18120
2.          

CTE _prm

3. 0.015 0.015 ↑ 1.0 1 1

Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.014..0.015 rows=1 loops=1)

  • Output: 33693, to_date('01.01.2019'::text, 'dd.mm.yyyy'::text), to_date('10.01.2019'::text, 'dd.mm.yyyy'::text), 'false'::text, 4664, NULL::integer
4.          

CTE prm

5. 0.029 0.029 ↑ 1.0 1 1

CTE Scan on _prm (cost=0.00..0.03 rows=1 width=48) (actual time=0.028..0.029 rows=1 loops=1)

  • Output: _prm.cln, _prm.d1, _prm.d2, _prm.is_detail, _prm.dep, ((_prm.d1 - '1 year'::interval))::date, ((_prm.d2 - '1 year'::interval))::date
6.          

CTE sec_org

7. 0.000 0.002 ↓ 0.0 0 1

Nested Loop (cost=0.43..10.65 rows=2 width=95) (actual time=0.002..0.002 rows=0 loops=1)

  • Output: suo.org_id, CASE WHEN (_prm_1.is_detail = 'true'::text) THEN mc.short_name ELSE NULL::character varying END
8. 0.000 0.002 ↓ 0.0 0 1

Nested Loop (cost=0.29..10.30 rows=2 width=36) (actual time=0.002..0.002 rows=0 loops=1)

  • Output: _prm_1.is_detail, suo.org_id
9. 0.002 0.002 ↓ 0.0 0 1

CTE Scan on _prm _prm_1 (cost=0.00..0.02 rows=1 width=36) (actual time=0.002..0.002 rows=0 loops=1)

  • Output: _prm_1.cln, _prm_1.d1, _prm_1.d2, _prm_1.is_detail, _prm_1.us, _prm_1.dep
  • Filter: (_prm_1.cln IS NULL)
  • Rows Removed by Filter: 1
10. 0.000 0.000 ↓ 0.0 0

Index Scan using sec_user_org_user_id_idx on public.sec_user_org suo (cost=0.29..10.26 rows=2 width=8) (never executed)

  • Output: suo.id, suo.user_id, suo.org_id, suo.aud_who, suo.aud_when, suo.aud_source, suo.aud_who_create, suo.aud_when_create, suo.aud_source_create
  • Index Cond: (suo.user_id = _prm_1.us)
11. 0.000 0.000 ↓ 0.0 0

Index Scan using md_clinic_pk on public.md_clinic mc (cost=0.14..0.16 rows=1 width=63) (never executed)

  • Output: mc.short_name, mc.id
  • Index Cond: (mc.id = suo.org_id)
12.          

CTE all_deps

13. 0.000 0.000 ↓ 0.0 0

Recursive Union (cost=0.28..2,073.26 rows=731 width=4) (never executed)

14. 0.000 0.000 ↓ 0.0 0

Nested Loop (cost=0.28..8.33 rows=1 width=4) (never executed)

  • Output: pd_1.id
15. 0.000 0.000 ↓ 0.0 0

CTE Scan on prm prm_1 (cost=0.00..0.02 rows=1 width=8) (never executed)

  • Output: prm_1.cln, prm_1.d1, prm_1.d2, prm_1.is_detail, prm_1.dep, prm_1.d1_last, prm_1.d2_last
16. 0.000 0.000 ↓ 0.0 0

Index Scan using pim_department_pk on public.pim_department pd_1 (cost=0.28..8.30 rows=1 width=8) (never executed)

  • Output: pd_1.id, pd_1.is_available_diagnosis, pd_1.code, pd_1.from_dt, pd_1.name, pd_1.to_dt, pd_1.accounting_center_id, pd_1.type_id, pd_1.funding_id, pd_1.org_id, pd_1.parent_id, pd_1.sphere_id, pd_1.is_payment, pd_1.unit_id, pd_1.kind_id, pd_1.e_code, pd_1.scope_id, pd_1.aud_who, pd_1.aud_when, pd_1.aud_source, pd_1.aud_who_create, pd_1.aud_when_create, pd_1.aud_source_create, pd_1.is_separate, pd_1.is_social_significant, pd_1.age_group_id, pd_1.is_branch_type, pd_1.visits_per_shift, pd_1.departures_per_shift, pd_1.visits_per_day, pd_1.necropsies_per_day, pd_1.clinical_trials_per_shift, pd_1.brigades_amount, pd_1.ose, pd_1.ose_reject, pd_1.at_home, pd_1.longitude, pd_1.latitude, pd_1.amb_reception_exists, pd_1.cadastral_number, pd_1.hospital_mode_id, pd_1.type_profile_id
  • Index Cond: (pd_1.id = prm_1.dep)
  • Filter: (prm_1.cln = pd_1.org_id)
17. 0.000 0.000 ↓ 0.0 0

Nested Loop (cost=0.28..205.03 rows=73 width=4) (never executed)

  • Output: pd_2.id
18. 0.000 0.000 ↓ 0.0 0

WorkTable Scan on all_deps (cost=0.00..0.20 rows=10 width=4) (never executed)

  • Output: all_deps.id
19. 0.000 0.000 ↓ 0.0 0

Index Scan using pim_department_parent_id_idx on public.pim_department pd_2 (cost=0.28..20.41 rows=7 width=8) (never executed)

  • Output: pd_2.id, pd_2.is_available_diagnosis, pd_2.code, pd_2.from_dt, pd_2.name, pd_2.to_dt, pd_2.accounting_center_id, pd_2.type_id, pd_2.funding_id, pd_2.org_id, pd_2.parent_id, pd_2.sphere_id, pd_2.is_payment, pd_2.unit_id, pd_2.kind_id, pd_2.e_code, pd_2.scope_id, pd_2.aud_who, pd_2.aud_when, pd_2.aud_source, pd_2.aud_who_create, pd_2.aud_when_create, pd_2.aud_source_create, pd_2.is_separate, pd_2.is_social_significant, pd_2.age_group_id, pd_2.is_branch_type, pd_2.visits_per_shift, pd_2.departures_per_shift, pd_2.visits_per_day, pd_2.necropsies_per_day, pd_2.clinical_trials_per_shift, pd_2.brigades_amount, pd_2.ose, pd_2.ose_reject, pd_2.at_home, pd_2.longitude, pd_2.latitude, pd_2.amb_reception_exists, pd_2.cadastral_number, pd_2.hospital_mode_id, pd_2.type_profile_id
  • Index Cond: (pd_2.parent_id = all_deps.id)
20.          

CTE _pd

21. 0.317 6.333 ↑ 1.8 288 1

Recursive Union (cost=4.32..2,685.43 rows=505 width=66) (actual time=0.075..6.333 rows=288 loops=1)

  • Buffers: shared hit=383
22. 0.083 0.310 ↓ 34.8 174 1

Nested Loop (cost=4.32..21.86 rows=5 width=66) (actual time=0.070..0.310 rows=174 loops=1)

  • Output: pd_3.id, pd_3.parent_id, pd_3.name
  • Buffers: shared hit=49
23. 0.002 0.002 ↑ 1.0 1 1

CTE Scan on prm prm_2 (cost=0.00..0.02 rows=1 width=4) (actual time=0.001..0.002 rows=1 loops=1)

  • Output: prm_2.cln, prm_2.d1, prm_2.d2, prm_2.is_detail, prm_2.dep, prm_2.d1_last, prm_2.d2_last
24. 0.179 0.225 ↓ 34.8 174 1

Bitmap Heap Scan on public.pim_department pd_3 (cost=4.32..21.79 rows=5 width=70) (actual time=0.062..0.225 rows=174 loops=1)

  • Output: pd_3.id, pd_3.is_available_diagnosis, pd_3.code, pd_3.from_dt, pd_3.name, pd_3.to_dt, pd_3.accounting_center_id, pd_3.type_id, pd_3.funding_id, pd_3.org_id, pd_3.parent_id, pd_3.sphere_id, pd_3.is_payment, pd_3.unit_id, pd_3.kind_id, pd_3.e_code, pd_3.scope_id, pd_3.aud_who, pd_3.aud_when, pd_3.aud_source, pd_3.aud_who_create, pd_3.aud_when_create, pd_3.aud_source_create, pd_3.is_separate, pd_3.is_social_significant, pd_3.age_group_id, pd_3.is_branch_type, pd_3.visits_per_shift, pd_3.departures_per_shift, pd_3.visits_per_day, pd_3.necropsies_per_day, pd_3.clinical_trials_per_shift, pd_3.brigades_amount, pd_3.ose, pd_3.ose_reject, pd_3.at_home, pd_3.longitude, pd_3.latitude, pd_3.amb_reception_exists, pd_3.cadastral_number, pd_3.hospital_mode_id, pd_3.type_profile_id
  • Recheck Cond: (pd_3.org_id = prm_2.cln)
  • Heap Blocks: exact=46
  • Buffers: shared hit=49
25. 0.046 0.046 ↓ 34.8 174 1

Bitmap Index Scan on pim_department_org_id_idx (cost=0.00..4.32 rows=5 width=0) (actual time=0.046..0.046 rows=174 loops=1)

  • Index Cond: (pd_3.org_id = prm_2.cln)
  • Buffers: shared hit=3
26. 3.138 5.706 ↑ 1.3 38 3

Hash Join (cost=1.62..265.35 rows=50 width=66) (actual time=0.874..1.902 rows=38 loops=3)

  • Output: _pd.id, d.parent_id, d.name
  • Hash Cond: (d.id = _pd.parent_id)
  • Buffers: shared hit=334
27. 2.442 2.442 ↓ 1.0 7,009 2

Seq Scan on public.pim_department d (cost=0.00..236.98 rows=6,998 width=66) (actual time=0.005..1.221 rows=7,009 loops=2)

  • Output: d.id, d.is_available_diagnosis, d.code, d.from_dt, d.name, d.to_dt, d.accounting_center_id, d.type_id, d.funding_id, d.org_id, d.parent_id, d.sphere_id, d.is_payment, d.unit_id, d.kind_id, d.e_code, d.scope_id, d.aud_who, d.aud_when, d.aud_source, d.aud_who_create, d.aud_when_create, d.aud_source_create, d.is_separate, d.is_social_significant, d.age_group_id, d.is_branch_type, d.visits_per_shift, d.departures_per_shift, d.visits_per_day, d.necropsies_per_day, d.clinical_trials_per_shift, d.brigades_amount, d.ose, d.ose_reject, d.at_home, d.longitude, d.latitude, d.amb_reception_exists, d.cadastral_number, d.hospital_mode_id, d.type_profile_id
  • Buffers: shared hit=334
28. 0.054 0.126 ↑ 1.3 38 3

Hash (cost=1.00..1.00 rows=50 width=8) (actual time=0.042..0.042 rows=38 loops=3)

  • Output: _pd.id, _pd.parent_id
  • Buckets: 1024 Batches: 1 Memory Usage: 8kB
29. 0.072 0.072 ↓ 1.9 96 3

WorkTable Scan on _pd (cost=0.00..1.00 rows=50 width=8) (actual time=0.001..0.024 rows=96 loops=3)

  • Output: _pd.id, _pd.parent_id
30.          

CTE pd

31. 6.580 6.580 ↓ 58.0 174 1

CTE Scan on _pd _pd_1 (cost=0.00..10.10 rows=3 width=520) (actual time=0.091..6.580 rows=174 loops=1)

  • Output: _pd_1.id, _pd_1.dep_name
  • Filter: (_pd_1.parent_id IS NULL)
  • Rows Removed by Filter: 114
  • Buffers: shared hit=383
32. 1.041 51.348 ↓ 19.6 1,372 1

Nested Loop (cost=16.58..2,086.71 rows=70 width=122) (actual time=1.292..51.348 rows=1,372 loops=1)

  • Output: prm.dep, prm.d2, prm.d2_last, sec_org.short_name, pp.department_id, r.e_code, cat.e_code, pep.employee_id, pep.start_date, pep.end_date, pe.individual_id, pe.number, i.surname, i.name, i.patr_name
  • Buffers: shared hit=13046
33. 1.789 42.075 ↓ 19.6 1,372 1

Nested Loop (cost=16.16..1,732.94 rows=70 width=73) (actual time=1.278..42.075 rows=1,372 loops=1)

  • Output: prm.dep, prm.d2, prm.d2_last, sec_org.short_name, pp.department_id, r.e_code, cat.e_code, pep.employee_id, pep.start_date, pep.end_date, pe.individual_id, pe.number
  • Buffers: shared hit=7545
34. 1.367 34.798 ↓ 19.6 1,372 1

Nested Loop (cost=15.87..1,707.71 rows=70 width=66) (actual time=1.261..34.798 rows=1,372 loops=1)

  • Output: prm.dep, prm.d2, prm.d2_last, sec_org.short_name, pp.department_id, r.e_code, cat.e_code, pep.employee_id, pep.start_date, pep.end_date
  • Buffers: shared hit=3428
35. 3.797 25.895 ↓ 19.6 628 1

Hash Join (cost=15.58..1,689.12 rows=32 width=58) (actual time=0.608..25.895 rows=628 loops=1)

  • Output: prm.dep, prm.d2, prm.d2_last, sec_org.short_name, pp.department_id, pp.id, r.e_code, cat.e_code
  • Hash Cond: (pp.organization_id = COALESCE(prm.cln, sec_org.org_id))
  • Join Filter: (((prm.dep IS NOT NULL) AND (alternatives: SubPlan 8 or hashed SubPlan 9)) OR (prm.dep IS NULL))
  • Buffers: shared hit=991
36. 16.250 22.058 ↓ 2.9 18,449 1

Hash Join (cost=15.47..1,396.84 rows=6,467 width=18) (actual time=0.482..22.058 rows=18,449 loops=1)

  • Output: pp.organization_id, pp.department_id, pp.id, r.e_code, cat.e_code
  • Hash Cond: (pp.role_id = r.id)
  • Buffers: shared hit=991
37. 5.344 5.344 ↑ 1.0 24,202 1

Seq Scan on public.pim_position pp (cost=0.00..1,226.02 rows=24,202 width=16) (actual time=0.008..5.344 rows=24,202 loops=1)

  • Output: pp.id, pp.code, pp.start_date, pp.name, pp.end_date, pp.department_id, pp.organization_id, pp.role_id, pp.speciality_id, pp.rate, pp.aud_who, pp.aud_when, pp.aud_source, pp.aud_who_create, pp.aud_when_create, pp.aud_source_create, pp.pref_prescription, pp.payment_fond, pp.staff_event1, pp.staff_event2, pp.note, pp.fact_employment, pp.external_rate, pp.billing_code
  • Buffers: shared hit=984
38. 0.093 0.464 ↓ 2.7 243 1

Hash (cost=14.33..14.33 rows=91 width=10) (actual time=0.464..0.464 rows=243 loops=1)

  • Output: r.e_code, r.id, cat.e_code
  • Buckets: 1024 Batches: 1 Memory Usage: 19kB
  • Buffers: shared hit=7
39. 0.281 0.371 ↓ 2.7 243 1

Hash Join (cost=1.25..14.33 rows=91 width=10) (actual time=0.035..0.371 rows=243 loops=1)

  • Output: r.e_code, r.id, cat.e_code
  • Hash Cond: (r.category_id = cat.id)
  • Join Filter: (((cat.e_code)::text = ANY ('{1,2,3}'::text[])) OR (((cat.e_code)::text = '10'::text) AND ((r.e_code)::text = ANY ('{10002,10003,10233,10235}'::text[]))))
  • Rows Removed by Join Filter: 19
  • Buffers: shared hit=7
40. 0.070 0.070 ↑ 1.0 341 1

Seq Scan on public.pim_position_role r (cost=0.00..9.41 rows=341 width=12) (actual time=0.004..0.070 rows=341 loops=1)

  • Output: r.id, r.code, r.name, r.category_id, r.e_code, r.parent_id, r.aud_who, r.aud_when, r.aud_source, r.aud_who_create, r.aud_when_create, r.aud_source_create, r.from_dt, r.to_dt
  • Buffers: shared hit=6
41. 0.004 0.020 ↑ 1.0 4 1

Hash (cost=1.20..1.20 rows=4 width=6) (actual time=0.020..0.020 rows=4 loops=1)

  • Output: cat.e_code, cat.id
  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
  • Buffers: shared hit=1
42. 0.016 0.016 ↑ 1.0 4 1

Seq Scan on public.pim_position_category cat (cost=0.00..1.20 rows=4 width=6) (actual time=0.006..0.016 rows=4 loops=1)

  • Output: cat.e_code, cat.id
  • Filter: (((cat.e_code)::text = ANY ('{1,2,3}'::text[])) OR ((cat.e_code)::text = '10'::text))
  • Rows Removed by Filter: 8
  • Buffers: shared hit=1
43. 0.003 0.040 ↑ 2.0 1 1

Hash (cost=0.08..0.08 rows=2 width=52) (actual time=0.040..0.040 rows=1 loops=1)

  • Output: prm.dep, prm.d2, prm.d2_last, prm.cln, sec_org.short_name, sec_org.org_id
  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
44. 0.002 0.037 ↑ 2.0 1 1

Nested Loop Left Join (cost=0.00..0.08 rows=2 width=52) (actual time=0.036..0.037 rows=1 loops=1)

  • Output: prm.dep, prm.d2, prm.d2_last, prm.cln, sec_org.short_name, sec_org.org_id
45. 0.032 0.032 ↑ 1.0 1 1

CTE Scan on prm (cost=0.00..0.02 rows=1 width=16) (actual time=0.031..0.032 rows=1 loops=1)

  • Output: prm.cln, prm.d1, prm.d2, prm.is_detail, prm.dep, prm.d1_last, prm.d2_last
46. 0.003 0.003 ↓ 0.0 0 1

CTE Scan on sec_org (cost=0.00..0.04 rows=2 width=36) (actual time=0.003..0.003 rows=0 loops=1)

  • Output: sec_org.org_id, sec_org.short_name
47.          

SubPlan (for Hash Join)

48. 0.000 0.000 ↓ 0.0 0

CTE Scan on all_deps all_deps_1 (cost=0.00..16.45 rows=4 width=0) (never executed)

  • Filter: (all_deps_1.id = pp.department_id)
49. 0.000 0.000 ↓ 0.0 0

CTE Scan on all_deps all_deps_2 (cost=0.00..14.62 rows=731 width=4) (never executed)

  • Output: all_deps_2.id
50. 7.536 7.536 ↑ 2.0 2 628

Index Scan using pim_employee_position_position_id_idx on public.pim_employee_position pep (cost=0.29..0.54 rows=4 width=16) (actual time=0.004..0.012 rows=2 loops=628)

  • Output: pep.id, pep.dismissal_order_code, pep.start_date, pep.hiring_order_code, pep.rate, pep.end_date, pep.dismissal_reason_id, pep.employee_id, pep.employment_type_id, pep.hiring_type_id, pep.position_id, pep.position_type_id, pep.unit_id, pep.code, pep.aud_who, pep.aud_when, pep.aud_source, pep.aud_who_create, pep.aud_when_create, pep.aud_source_create, pep.pref_prescription, pep.extra_payment, pep.target_training, pep.leaving_reason_id
  • Index Cond: (pep.position_id = pp.id)
  • Buffers: shared hit=2437
51. 5.488 5.488 ↑ 1.0 1 1,372

Index Scan using pim_employee_pk on public.pim_employee pe (cost=0.29..0.35 rows=1 width=11) (actual time=0.004..0.004 rows=1 loops=1,372)

  • Output: pe.id, pe.note, pe.number, pe.photo, pe.callup_subject_id, pe.individual_id, pe.organization_id, pe.is_dismissed, pe.employment_dt, pe.dismissal_dt, pe.aud_who, pe.aud_when, pe.aud_source, pe.aud_who_create, pe.aud_when_create, pe.aud_source_create, pe.accreditation_id
  • Index Cond: (pe.id = pep.employee_id)
  • Buffers: shared hit=4117
52. 8.232 8.232 ↑ 1.0 1 1,372

Index Scan using pim_individual_pk on public.pim_individual i (cost=0.43..5.04 rows=1 width=53) (actual time=0.005..0.006 rows=1 loops=1,372)

  • Output: i.id, i.birth_dt, i.death_dt, i.has_citizenship, i.name, i.patr_name, i.surname, i.gender_id, i.nationality_id, i.list_identity_doc, i.list_oms_doc, i.list_job_org, i.list_reg_name, i.list_snils, i.list_uid, i.aud_who, i.aud_when, i.aud_source, i.aud_who_create, i.aud_when_create, i.aud_source_create, i.birth_place, i.age_year, i.age_month, i.age_day, i.list_main_contact, i.is_only_birth_year
  • Index Cond: (i.id = pe.individual_id)
  • Buffers: shared hit=5501
53. 0.081 6.804 ↓ 58.0 174 1

Hash (cost=0.06..0.06 rows=3 width=520) (actual time=6.804..6.804 rows=174 loops=1)

  • Output: pd.dep_name, pd.id
  • Buckets: 1024 Batches: 1 Memory Usage: 25kB
  • Buffers: shared hit=383
54. 6.723 6.723 ↓ 58.0 174 1

CTE Scan on pd (cost=0.00..0.06 rows=3 width=520) (actual time=0.094..6.723 rows=174 loops=1)

  • Output: pd.dep_name, pd.id
  • Buffers: shared hit=383
55.          

SubPlan (for Hash Left Join)

56. 2.744 12.348 ↑ 1.0 1 1,372

Aggregate (cost=16.65..16.66 rows=1 width=11) (actual time=0.009..0.009 rows=1 loops=1,372)

  • Output: array_agg(lower((su.login)::text))
  • Buffers: shared hit=4691
57. 2.156 9.604 ↓ 0.0 0 1,372

Nested Loop (cost=0.56..16.64 rows=1 width=11) (actual time=0.006..0.007 rows=0 loops=1,372)

  • Output: su.login
  • Buffers: shared hit=4691
58. 1.372 5.488 ↓ 0.0 0 1,372

Nested Loop (cost=0.28..8.33 rows=1 width=4) (actual time=0.004..0.004 rows=0 loops=1,372)

  • Output: sup.id
  • Buffers: shared hit=3217
59. 0.000 0.000 ↑ 1.0 1 1,372

CTE Scan on prm t (cost=0.00..0.02 rows=1 width=0) (actual time=0.000..0.000 rows=1 loops=1,372)

  • Output: t.cln, t.d1, t.d2, t.is_detail, t.dep, t.d1_last, t.d2_last
60. 4.116 4.116 ↓ 0.0 0 1,372

Index Scan using idx_sec_user_party on public.sec_user_party sup (cost=0.28..8.30 rows=1 width=4) (actual time=0.003..0.003 rows=0 loops=1,372)

  • Output: sup.id, sup.party_id, sup.aud_who, sup.aud_when, sup.aud_source, sup.aud_who_create, sup.aud_when_create, sup.aud_source_create
  • Index Cond: (sup.party_id = pe.individual_id)
  • Buffers: shared hit=3217
61. 1.960 1.960 ↑ 1.0 1 490

Index Scan using sec_user_pk on public.sec_user su (cost=0.28..8.30 rows=1 width=15) (actual time=0.004..0.004 rows=1 loops=490)

  • Output: su.id, su.close_dt, su.comment, su.cr_dt, su.email, su.login, su.password, su.version, su.blocked, su.scope_id, su.use_global_context, su.aud_who, su.aud_when, su.aud_source, su.aud_who_create, su.aud_when_create, su.aud_source_create
  • Index Cond: (su.id = sup.id)
  • Buffers: shared hit=1474
Planning time : 5.892 ms
Execution time : 80.518 ms