explain.depesz.com

PostgreSQL's explain analyze made readable

Result: Xe9r

Settings

Optimization(s) for this plan:

# exclusive inclusive rows x rows loops node
1. 0.000 57,088.850 ↑ 2,069.6 7 1

Nested Loop Left Join (cost=2,415,205.07..30,248,074.92 rows=14,487 width=4,057) (actual time=16,713.159..57,088.850 rows=7 loops=1)

2.          

Initplan (for Nested Loop Left Join)

3. 0.119 0.119 ↑ 1.0 1 1

Result (cost=0.00..0.26 rows=1 width=8) (actual time=0.119..0.119 rows=1 loops=1)

4. 0.033 57,088.745 ↑ 2,069.6 7 1

Hash Left Join (cost=2,415,196.50..30,127,325.51 rows=14,487 width=4,024) (actual time=16,713.138..57,088.745 rows=7 loops=1)

  • Hash Cond: (pv.manufacturer_id = manufacturer_per.id)
5. 0.035 57,087.488 ↑ 2,069.6 7 1

Nested Loop Left Join (cost=2,414,999.29..30,127,090.27 rows=14,487 width=4,024) (actual time=16,711.896..57,087.488 rows=7 loops=1)

6. 0.037 57,087.404 ↑ 2,069.6 7 1

Nested Loop Left Join (cost=2,414,999.01..30,006,594.65 rows=14,487 width=4,016) (actual time=16,711.882..57,087.404 rows=7 loops=1)

7. 0.017 57,086.576 ↑ 2,069.6 7 1

Nested Loop Left Join (cost=2,414,983.02..29,774,461.96 rows=14,487 width=3,824) (actual time=16,711.757..57,086.576 rows=7 loops=1)

8. 0.027 57,086.377 ↑ 2,069.6 7 1

Nested Loop Left Join (cost=2,414,983.02..29,774,280.85 rows=14,487 width=3,816) (actual time=16,711.576..57,086.377 rows=7 loops=1)

9. 0.028 57,086.273 ↑ 2,069.6 7 1

Hash Left Join (cost=2,414,971.73..29,610,288.01 rows=14,487 width=3,784) (actual time=16,711.554..57,086.273 rows=7 loops=1)

  • Hash Cond: (pv.country_add = c_8.id)
10. 2,790.103 57,086.098 ↑ 2,069.6 7 1

Nested Loop Left Join (cost=2,414,960.04..29,610,218.92 rows=14,487 width=3,720) (actual time=16,711.397..57,086.098 rows=7 loops=1)

  • Filter: (CASE WHEN pv.engine_number_is_missing THEN (m.name)::text ELSE (string_agg((engine.part_number)::text, ', '::text ORDER BY (engine.part_number)::text)) END ~~ '%23423%'::text)
  • Rows Removed by Filter: 5794127
11. 1,726.095 36,913.593 ↓ 2.0 5,794,134 1

Hash Left Join (cost=2,414,951.59..5,025,491.43 rows=2,897,434 width=3,688) (actual time=11,011.595..36,913.593 rows=5,794,134 loops=1)

  • Hash Cond: (pv.id = pw.pasport_id)
  • Join Filter: (((pv.type_id = ANY ('{1,2}'::bigint[])) AND ((wt.code)::text = '12'::text)) OR ((pv.type_id = '3'::bigint) AND ((wt.code)::text = '27'::text)))
12. 1,364.837 35,149.034 ↓ 2.0 5,794,134 1

Hash Left Join (cost=2,414,527.63..5,014,179.10 rows=2,897,434 width=3,683) (actual time=10,973.120..35,149.034 rows=5,794,134 loops=1)

  • Hash Cond: (pv.ts_cat_id = c_5.id)
13. 1,305.216 33,783.948 ↓ 2.0 5,794,134 1

Hash Left Join (cost=2,414,524.58..5,003,296.40 rows=2,897,434 width=3,029) (actual time=10,972.865..33,783.948 rows=5,794,134 loops=1)

  • Hash Cond: (pv.ecologic_class_id = c_6.id)
14. 1,257.034 32,478.519 ↓ 2.0 5,794,134 1

Hash Left Join (cost=2,414,521.86..4,992,417.49 rows=2,897,434 width=2,375) (actual time=10,972.643..32,478.519 rows=5,794,134 loops=1)

  • Hash Cond: (pv.ts_trademark_id = c_7.id)
15. 2,272.495 31,216.071 ↓ 2.0 5,794,134 1

Nested Loop Left Join (cost=2,414,400.31..4,981,418.82 rows=2,897,434 width=2,367) (actual time=10,967.221..31,216.071 rows=5,794,134 loops=1)

16. 1,234.382 28,943.576 ↓ 2.0 5,794,134 1

Hash Left Join (cost=2,414,400.16..4,945,192.71 rows=2,897,434 width=2,296) (actual time=10,967.172..28,943.576 rows=5,794,134 loops=1)

  • Hash Cond: (pv.ts_cu_cat_id = c_4.id)
17. 1,298.888 27,707.965 ↓ 2.0 5,794,134 1

Hash Left Join (cost=2,414,391.63..4,934,303.79 rows=2,897,434 width=2,155) (actual time=10,965.938..27,707.965 rows=5,794,134 loops=1)

  • Hash Cond: (pv.type_id = c_3.id)
18. 8,189.210 26,408.905 ↓ 2.0 5,794,134 1

Hash Join (cost=2,414,389.24..4,923,420.77 rows=2,897,434 width=1,501) (actual time=10,965.752..26,408.905 rows=5,794,134 loops=1)

  • Hash Cond: (pv.root_id = root.id)
19. 3,591.948 13,099.804 ↑ 1.0 5,794,869 1

Merge Left Join (cost=2,229,701.46..2,629,087.45 rows=5,794,869 width=1,432) (actual time=5,844.508..13,099.804 rows=5,794,869 loops=1)

  • Merge Cond: (pv.id = sh.pasport_id)
20. 2,526.577 2,526.577 ↑ 1.0 5,794,869 1

Index Scan using fdc_pts_ver_pk on fdc_pts_ver pv (cost=0.43..283,606.39 rows=5,794,869 width=930) (actual time=0.015..2,526.577 rows=5,794,869 loops=1)

21. 422.366 6,981.279 ↓ 1.0 5,794,850 1

Materialize (cost=2,229,701.03..2,258,641.84 rows=5,788,163 width=510) (actual time=5,844.481..6,981.279 rows=5,794,850 loops=1)

22. 2,597.295 6,558.913 ↓ 1.0 5,794,850 1

Sort (cost=2,229,701.03..2,244,171.44 rows=5,788,163 width=510) (actual time=5,844.476..6,558.913 rows=5,794,850 loops=1)

  • Sort Key: sh.pasport_id
  • Sort Method: external merge Disk: 384208kB
23. 864.483 3,961.618 ↓ 1.0 5,794,850 1

Hash Left Join (cost=13.58..254,042.05 rows=5,788,163 width=510) (actual time=1.225..3,961.618 rows=5,794,850 loops=1)

  • Hash Cond: (c.id = t.status_id)
24. 849.211 3,096.829 ↓ 1.0 5,794,850 1

Hash Join (cost=11.55..232,406.77 rows=5,788,163 width=493) (actual time=0.915..3,096.829 rows=5,794,850 loops=1)

  • Hash Cond: (sh.status_id = c.id)
25. 719.585 2,247.607 ↓ 1.0 5,794,850 1

Hash Left Join (cost=10.33..210,772.29 rows=5,788,163 width=347) (actual time=0.890..2,247.607 rows=5,794,850 loops=1)

  • Hash Cond: (sh.reason_id = c_1.id)
26. 1,527.149 1,527.149 ↓ 1.0 5,794,850 1

Seq Scan on fdc_pts_status_history sh (cost=0.00..189,056.34 rows=5,788,163 width=24) (actual time=0.005..1,527.149 rows=5,794,850 loops=1)

  • Filter: ((statement_timestamp() >= date_from) AND (statement_timestamp() <= date_to))
  • Rows Removed by Filter: 48817
27. 0.010 0.873 ↑ 1.0 25 1

Hash (cost=10.02..10.02 rows=25 width=331) (actual time=0.873..0.873 rows=25 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 14kB
28. 0.011 0.863 ↑ 1.0 25 1

Hash Join (cost=3.90..10.02 rows=25 width=331) (actual time=0.266..0.863 rows=25 loops=1)

  • Hash Cond: (c_1.object_type_id = c_2.id)
29. 0.023 0.706 ↑ 1.0 25 1

Hash Right Join (cost=1.56..7.56 rows=25 width=339) (actual time=0.114..0.706 rows=25 loops=1)

  • Hash Cond: (t_1.reason_id = c_1.id)
30. 0.671 0.671 ↑ 1.0 25 1

Seq Scan on fdc_change_status_reason_translation t_1 (cost=0.00..5.92 rows=25 width=193) (actual time=0.088..0.671 rows=25 loops=1)

  • Filter: (language_id = lang.get_current_lang_id())
  • Rows Removed by Filter: 103
31. 0.006 0.012 ↑ 1.0 25 1

Hash (cost=1.25..1.25 rows=25 width=154) (actual time=0.012..0.012 rows=25 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 10kB
32. 0.006 0.006 ↑ 1.0 25 1

Seq Scan on fdc_change_status_reason c_1 (cost=0.00..1.25 rows=25 width=154) (actual time=0.004..0.006 rows=25 loops=1)

33. 0.001 0.146 ↑ 1.0 3 1

Hash (cost=2.30..2.30 rows=3 width=8) (actual time=0.146..0.146 rows=3 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
34. 0.009 0.145 ↑ 1.0 3 1

Hash Right Join (cost=1.07..2.30 rows=3 width=8) (actual time=0.067..0.145 rows=3 loops=1)

  • Hash Cond: (t_2.object_type_id = c_2.id)
35. 0.128 0.128 ↓ 3.0 3 1

Seq Scan on fdc_object_type_translation t_2 (cost=0.00..1.23 rows=1 width=8) (actual time=0.053..0.128 rows=3 loops=1)

  • Filter: (language_id = lang.get_current_lang_id())
  • Rows Removed by Filter: 12
36. 0.004 0.008 ↑ 1.0 3 1

Hash (cost=1.03..1.03 rows=3 width=8) (actual time=0.008..0.008 rows=3 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
37. 0.004 0.004 ↑ 1.0 3 1

Seq Scan on fdc_object_type c_2 (cost=0.00..1.03 rows=3 width=8) (actual time=0.004..0.004 rows=3 loops=1)

38. 0.004 0.011 ↑ 1.0 10 1

Hash (cost=1.10..1.10 rows=10 width=146) (actual time=0.011..0.011 rows=10 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
39. 0.007 0.007 ↑ 1.0 10 1

Seq Scan on fdc_status_pts c (cost=0.00..1.10 rows=10 width=146) (actual time=0.006..0.007 rows=10 loops=1)

40. 0.003 0.306 ↑ 1.0 10 1

Hash (cost=1.90..1.90 rows=10 width=33) (actual time=0.306..0.306 rows=10 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
41. 0.303 0.303 ↑ 1.0 10 1

Seq Scan on fdc_status_pts_translation t (cost=0.00..1.90 rows=10 width=33) (actual time=0.064..0.303 rows=10 loops=1)

  • Filter: (language_id = lang.get_current_lang_id())
  • Rows Removed by Filter: 50
42. 730.750 5,119.891 ↓ 2.0 5,440,311 1

Hash (cost=116,143.24..116,143.24 rows=2,720,523 width=77) (actual time=5,119.891..5,119.891 rows=5,440,311 loops=1)

  • Buckets: 524288 Batches: 16 Memory Usage: 19610kB
43. 4,389.141 4,389.141 ↓ 2.0 5,440,311 1

Index Scan using fdc_pts_root_passport_type_i on fdc_pts_root root (cost=0.43..116,143.24 rows=2,720,523 width=77) (actual time=0.165..4,389.141 rows=5,440,311 loops=1)

  • Index Cond: (passport_type_id = $0)
44. 0.002 0.172 ↑ 1.0 3 1

Hash (cost=2.36..2.36 rows=3 width=662) (actual time=0.172..0.172 rows=3 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
45. 0.002 0.170 ↑ 1.0 3 1

Nested Loop Left Join (cost=1.07..2.36 rows=3 width=662) (actual time=0.096..0.170 rows=3 loops=1)

46. 0.009 0.165 ↑ 1.0 3 1

Hash Right Join (cost=1.07..2.30 rows=3 width=662) (actual time=0.091..0.165 rows=3 loops=1)

  • Hash Cond: (t_3.kind_id = c_3.id)
47. 0.145 0.145 ↓ 3.0 3 1

Seq Scan on fdc_ts_kind_translation t_3 (cost=0.00..1.23 rows=1 width=524) (actual time=0.074..0.145 rows=3 loops=1)

  • Filter: (language_id = lang.get_current_lang_id())
  • Rows Removed by Filter: 12
48. 0.002 0.011 ↑ 1.0 3 1

Hash (cost=1.03..1.03 rows=3 width=146) (actual time=0.011..0.011 rows=3 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
49. 0.009 0.009 ↑ 1.0 3 1

Seq Scan on fdc_ts_kind c_3 (cost=0.00..1.03 rows=3 width=146) (actual time=0.008..0.009 rows=3 loops=1)

50. 0.001 0.003 ↑ 1.0 1 3

Materialize (cost=0.00..0.03 rows=1 width=0) (actual time=0.001..0.001 rows=1 loops=3)

51. 0.001 0.002 ↑ 1.0 1 1

Subquery Scan on fdc_translate_messages_boolean_v (cost=0.00..0.02 rows=1 width=0) (actual time=0.002..0.002 rows=1 loops=1)

52. 0.001 0.001 ↑ 1.0 1 1

Result (cost=0.00..0.01 rows=1 width=64) (actual time=0.001..0.001 rows=1 loops=1)

53. 0.009 1.229 ↑ 1.0 49 1

Hash (cost=7.92..7.92 rows=49 width=149) (actual time=1.229..1.229 rows=49 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 11kB
54. 0.018 1.220 ↑ 1.0 49 1

Hash Right Join (cost=2.10..7.92 rows=49 width=149) (actual time=0.036..1.220 rows=49 loops=1)

  • Hash Cond: (t_4.ts_cat_id = c_4.id)
55. 1.186 1.186 ↑ 1.0 49 1

Seq Scan on fdc_ts_cu_cat_translation t_4 (cost=0.00..5.67 rows=49 width=11) (actual time=0.017..1.186 rows=49 loops=1)

  • Filter: (language_id = lang.get_current_lang_id())
  • Rows Removed by Filter: 196
56. 0.005 0.016 ↑ 1.0 49 1

Hash (cost=1.49..1.49 rows=49 width=146) (actual time=0.016..0.016 rows=49 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 11kB
57. 0.011 0.011 ↑ 1.0 49 1

Seq Scan on fdc_ts_cu_cat c_4 (cost=0.00..1.49 rows=49 width=146) (actual time=0.005..0.011 rows=49 loops=1)

58. 0.000 0.000 ↑ 1.0 1 5,794,134

Materialize (cost=0.15..8.18 rows=1 width=71) (actual time=0.000..0.000 rows=1 loops=5,794,134)

59. 0.046 0.046 ↑ 1.0 1 1

Index Scan using fdc_translate_messages_code_date_uk on fdc_translate_messages m (cost=0.15..8.18 rows=1 width=71) (actual time=0.045..0.046 rows=1 loops=1)

  • Index Cond: (((code)::text = 'SYS.IS_MISSING'::text) AND (languages_id = lang.get_current_lang_id()))
  • Filter: ((statement_timestamp() >= date_from) AND (statement_timestamp() <= date_to))
60. 0.090 5.414 ↓ 1.0 855 1

Hash (cost=110.88..110.88 rows=854 width=16) (actual time=5.414..5.414 rows=855 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 49kB
61. 0.175 5.324 ↓ 1.0 855 1

Nested Loop Left Join (cost=51.12..110.88 rows=854 width=16) (actual time=4.725..5.324 rows=855 loops=1)

62. 0.145 5.149 ↓ 1.0 855 1

Hash Right Join (cost=51.12..100.18 rows=854 width=16) (actual time=4.721..5.149 rows=855 loops=1)

  • Hash Cond: (t_7.trademark_id = c_7.id)
63. 0.307 0.405 ↓ 1.0 855 1

Bitmap Heap Scan on fdc_ts_trademark_translation t_7 (cost=18.90..65.71 rows=854 width=16) (actual time=0.117..0.405 rows=855 loops=1)

  • Recheck Cond: (language_id = lang.get_current_lang_id())
  • Heap Blocks: exact=34
64. 0.098 0.098 ↓ 1.0 856 1

Bitmap Index Scan on fdc_ts_trademark_translation_l_i (cost=0.00..18.69 rows=854 width=0) (actual time=0.098..0.098 rows=856 loops=1)

  • Index Cond: (language_id = lang.get_current_lang_id())
65. 0.075 4.599 ↓ 1.0 855 1

Hash (cost=21.54..21.54 rows=854 width=8) (actual time=4.599..4.599 rows=855 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 42kB
66. 4.524 4.524 ↓ 1.0 855 1

Seq Scan on fdc_ts_trademark c_7 (cost=0.00..21.54 rows=854 width=8) (actual time=0.008..4.524 rows=855 loops=1)

67. 0.000 0.000 ↑ 1.0 1 855

Materialize (cost=0.00..0.03 rows=1 width=0) (actual time=0.000..0.000 rows=1 loops=855)

68. 0.000 0.001 ↑ 1.0 1 1

Subquery Scan on fdc_translate_messages_boolean_v_2 (cost=0.00..0.02 rows=1 width=0) (actual time=0.001..0.001 rows=1 loops=1)

69. 0.001 0.001 ↑ 1.0 1 1

Result (cost=0.00..0.01 rows=1 width=64) (actual time=0.001..0.001 rows=1 loops=1)

70. 0.002 0.213 ↑ 1.0 7 1

Hash (cost=2.63..2.63 rows=7 width=662) (actual time=0.213..0.213 rows=7 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
71. 0.008 0.211 ↑ 1.0 7 1

Hash Left Join (cost=1.54..2.63 rows=7 width=662) (actual time=0.209..0.211 rows=7 loops=1)

  • Hash Cond: (c_6.id = t_6.ecolog_class_id)
72. 0.004 0.004 ↑ 1.0 7 1

Seq Scan on fdc_ecolog_class c_6 (cost=0.00..1.07 rows=7 width=146) (actual time=0.004..0.004 rows=7 loops=1)

73. 0.002 0.199 ↓ 7.0 7 1

Hash (cost=1.52..1.52 rows=1 width=524) (actual time=0.199..0.199 rows=7 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
74. 0.197 0.197 ↓ 7.0 7 1

Seq Scan on fdc_ecolog_class_translation t_6 (cost=0.00..1.52 rows=1 width=524) (actual time=0.038..0.197 rows=7 loops=1)

  • Filter: (language_id = lang.get_current_lang_id())
  • Rows Removed by Filter: 28
75. 0.003 0.249 ↑ 1.0 9 1

Hash (cost=2.94..2.94 rows=9 width=662) (actual time=0.248..0.249 rows=9 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
76. 0.005 0.246 ↑ 1.0 9 1

Nested Loop Left Join (cost=1.69..2.94 rows=9 width=662) (actual time=0.242..0.246 rows=9 loops=1)

77. 0.007 0.241 ↑ 1.0 9 1

Hash Left Join (cost=1.69..2.80 rows=9 width=662) (actual time=0.239..0.241 rows=9 loops=1)

  • Hash Cond: (c_5.id = t_5.ts_cat_id)
78. 0.004 0.004 ↑ 1.0 9 1

Seq Scan on fdc_ts_cat c_5 (cost=0.00..1.09 rows=9 width=146) (actual time=0.004..0.004 rows=9 loops=1)

79. 0.002 0.230 ↓ 9.0 9 1

Hash (cost=1.67..1.67 rows=1 width=524) (actual time=0.230..0.230 rows=9 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
80. 0.228 0.228 ↓ 9.0 9 1

Seq Scan on fdc_ts_cat_translation t_5 (cost=0.00..1.67 rows=1 width=524) (actual time=0.015..0.228 rows=9 loops=1)

  • Filter: (language_id = lang.get_current_lang_id())
  • Rows Removed by Filter: 36
81. 0.000 0.000 ↑ 1.0 1 9

Materialize (cost=0.00..0.03 rows=1 width=0) (actual time=0.000..0.000 rows=1 loops=9)

82. 0.001 0.001 ↑ 1.0 1 1

Subquery Scan on fdc_translate_messages_boolean_v_1 (cost=0.00..0.02 rows=1 width=0) (actual time=0.001..0.001 rows=1 loops=1)

83. 0.000 0.000 ↑ 1.0 1 1

Result (cost=0.00..0.01 rows=1 width=64) (actual time=0.000..0.000 rows=1 loops=1)

84. 0.361 38.464 ↓ 1.3 2,961 1

Hash (cost=395.21..395.21 rows=2,300 width=151) (actual time=38.464..38.464 rows=2,961 loops=1)

  • Buckets: 4096 Batches: 1 Memory Usage: 180kB
85. 0.521 38.103 ↓ 1.3 2,961 1

Hash Left Join (cost=21.74..395.21 rows=2,300 width=151) (actual time=0.436..38.103 rows=2,961 loops=1)

  • Hash Cond: (measure_unit.id = measure_unit_tr.measure_unit_id)
86. 0.365 37.481 ↓ 1.3 2,961 1

Hash Left Join (cost=8.22..375.38 rows=2,300 width=159) (actual time=0.327..37.481 rows=2,961 loops=1)

  • Hash Cond: (pw.measure_unit_id = measure_unit.id)
87. 0.379 37.092 ↓ 1.3 2,961 1

Hash Left Join (cost=4.15..364.99 rows=2,300 width=159) (actual time=0.299..37.092 rows=2,961 loops=1)

  • Hash Cond: (wt.id = wt_tr.weight_type_id)
88. 1.920 36.437 ↓ 1.3 2,961 1

Hash Join (cost=1.19..353.66 rows=2,300 width=167) (actual time=0.019..36.437 rows=2,961 loops=1)

  • Hash Cond: (pw.weight_type_id = wt.id)
89. 34.510 34.510 ↑ 1.0 12,648 1

Seq Scan on fdc_pts_weight pw (cost=0.00..306.48 rows=12,648 width=29) (actual time=0.004..34.510 rows=12,648 loops=1)

90. 0.001 0.007 ↑ 1.0 2 1

Hash (cost=1.17..1.17 rows=2 width=146) (actual time=0.007..0.007 rows=2 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
91. 0.006 0.006 ↑ 1.0 2 1

Seq Scan on fdc_weight_type wt (cost=0.00..1.17 rows=2 width=146) (actual time=0.005..0.006 rows=2 loops=1)

  • Filter: (((code)::text = '12'::text) OR ((code)::text = '27'::text))
  • Rows Removed by Filter: 9
92. 0.002 0.276 ↑ 1.0 11 1

Hash (cost=2.83..2.83 rows=11 width=8) (actual time=0.276..0.276 rows=11 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
93. 0.274 0.274 ↑ 1.0 11 1

Seq Scan on fdc_weight_type_translation wt_tr (cost=0.00..2.83 rows=11 width=8) (actual time=0.080..0.274 rows=11 loops=1)

  • Filter: (language_id = lang.get_current_lang_id())
  • Rows Removed by Filter: 44
94. 0.008 0.024 ↑ 1.0 92 1

Hash (cost=2.92..2.92 rows=92 width=8) (actual time=0.024..0.024 rows=92 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 12kB
95. 0.016 0.016 ↑ 1.0 92 1

Seq Scan on fdc_measure_unit measure_unit (cost=0.00..2.92 rows=92 width=8) (actual time=0.004..0.016 rows=92 loops=1)

96. 0.008 0.101 ↑ 1.0 92 1

Hash (cost=12.37..12.37 rows=92 width=8) (actual time=0.101..0.101 rows=92 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 12kB
97. 0.056 0.093 ↑ 1.0 92 1

Bitmap Heap Scan on fdc_measure_unit_translation measure_unit_tr (cost=4.99..12.37 rows=92 width=8) (actual time=0.055..0.093 rows=92 loops=1)

  • Recheck Cond: (language_id = lang.get_current_lang_id())
  • Heap Blocks: exact=6
98. 0.037 0.037 ↑ 1.0 92 1

Bitmap Index Scan on fdc_measure_unit_translation_l_i (cost=0.00..4.97 rows=92 width=0) (actual time=0.036..0.037 rows=92 loops=1)

  • Index Cond: (language_id = lang.get_current_lang_id())
99. 5,794.134 17,382.402 ↑ 1.0 1 5,794,134

Aggregate (cost=8.45..8.46 rows=1 width=32) (actual time=0.003..0.003 rows=1 loops=5,794,134)

100. 11,588.268 11,588.268 ↓ 0.0 0 5,794,134

Index Scan using fdc_pts_part_number_psp_i on fdc_pts_part_number engine (cost=0.42..8.45 rows=1 width=10) (actual time=0.002..0.002 rows=0 loops=5,794,134)

  • Index Cond: (pasport_id = pv.id)
  • Filter: (equipment_type_id = nsi.get_equipment_type_id('ENGINE_NUMBER'::character varying))
101. 0.002 0.147 ↑ 1.0 5 1

Hash (cost=11.62..11.62 rows=5 width=72) (actual time=0.147..0.147 rows=5 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
102. 0.068 0.145 ↑ 1.0 5 1

Nested Loop Left Join (cost=1.39..11.62 rows=5 width=72) (actual time=0.072..0.145 rows=5 loops=1)

103. 0.029 0.052 ↑ 1.0 5 1

Hash Join (cost=1.11..7.41 rows=5 width=12) (actual time=0.018..0.052 rows=5 loops=1)

  • Hash Cond: (c_8.id = sl.country_id)
104. 0.016 0.016 ↑ 1.0 236 1

Seq Scan on fdc_country c_8 (cost=0.00..5.36 rows=236 width=12) (actual time=0.005..0.016 rows=236 loops=1)

105. 0.002 0.007 ↑ 1.0 5 1

Hash (cost=1.05..1.05 rows=5 width=8) (actual time=0.007..0.007 rows=5 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
106. 0.005 0.005 ↑ 1.0 5 1

Seq Scan on fdc_server_list sl (cost=0.00..1.05 rows=5 width=8) (actual time=0.004..0.005 rows=5 loops=1)

107. 0.025 0.025 ↑ 1.0 1 5

Index Scan using fdc_country_translation_vl_i on fdc_country_translation t_8 (cost=0.28..0.84 rows=1 width=68) (actual time=0.005..0.005 rows=1 loops=5)

  • Index Cond: ((c_8.id = country_id) AND (language_id = lang.get_current_lang_id()))
108. 0.028 0.077 ↑ 1.0 1 7

Aggregate (cost=11.29..11.30 rows=1 width=32) (actual time=0.011..0.011 rows=1 loops=7)

109. 0.007 0.049 ↓ 0.0 0 7

Nested Loop Left Join (cost=0.28..11.28 rows=1 width=516) (actual time=0.007..0.007 rows=0 loops=7)

  • Join Filter: (c_9.id = t_9.color_id)
110. 0.007 0.042 ↓ 0.0 0 7

Nested Loop (cost=0.28..9.52 rows=1 width=8) (actual time=0.006..0.006 rows=0 loops=7)

  • Join Filter: (pc.color_id = c_9.id)
111. 0.035 0.035 ↓ 0.0 0 7

Index Scan using fdc_pts_colors_psp_i on fdc_pts_color pc (cost=0.28..8.30 rows=1 width=8) (actual time=0.005..0.005 rows=0 loops=7)

  • Index Cond: (pasport_id = pv.id)
112. 0.000 0.000 ↓ 0.0 0

Seq Scan on fdc_color c_9 (cost=0.00..1.10 rows=10 width=8) (never executed)

113. 0.000 0.000 ↓ 0.0 0

Seq Scan on fdc_color_translation t_9 (cost=0.00..1.75 rows=1 width=524) (never executed)

  • Filter: (language_id = lang.get_current_lang_id())
114. 0.003 0.182 ↑ 1.0 1 7

Materialize (cost=0.00..0.03 rows=1 width=8) (actual time=0.026..0.026 rows=1 loops=7)

115. 0.179 0.179 ↑ 1.0 1 1

Result (cost=0.00..0.01 rows=1 width=8) (actual time=0.178..0.179 rows=1 loops=1)

116. 0.105 0.791 ↑ 1.0 1 7

Aggregate (cost=15.99..16.00 rows=1 width=208) (actual time=0.113..0.113 rows=1 loops=7)

117. 0.023 0.686 ↑ 1.0 1 7

Nested Loop Left Join (cost=0.97..15.96 rows=1 width=727) (actual time=0.097..0.098 rows=1 loops=7)

  • Join Filter: (c_11.id = t_11.payment_execution_id)
118. 0.043 0.609 ↑ 1.0 1 7

Nested Loop Left Join (cost=0.97..14.72 rows=1 width=211) (actual time=0.086..0.087 rows=1 loops=7)

  • Join Filter: (c_11.id = rdv.payment_execution_id)
119. 0.017 0.560 ↑ 1.0 1 7

Nested Loop Left Join (cost=0.97..13.65 rows=1 width=73) (actual time=0.079..0.080 rows=1 loops=7)

120. 0.023 0.525 ↑ 1.0 1 7

Nested Loop Left Join (cost=0.84..13.46 rows=1 width=81) (actual time=0.074..0.075 rows=1 loops=7)

121. 0.196 0.196 ↑ 1.0 1 7

Index Scan using fdc_pts_recycling_duty_date_uk on fdc_pts_recycling_duty rdv (cost=0.41..8.44 rows=1 width=33) (actual time=0.027..0.028 rows=1 loops=7)

  • Index Cond: (pasport_root_id = pv.root_id)
  • Filter: ((statement_timestamp() >= date_from) AND (statement_timestamp() <= date_to))
122. 0.240 0.306 ↑ 1.0 1 6

Nested Loop Left Join (cost=0.43..5.01 rows=1 width=48) (actual time=0.051..0.051 rows=1 loops=6)

123. 0.030 0.030 ↑ 1.0 1 6

Index Only Scan using fdc_country_pk on fdc_country c_10 (cost=0.14..4.16 rows=1 width=8) (actual time=0.005..0.005 rows=1 loops=6)

  • Index Cond: (id = rdv.country_id)
  • Heap Fetches: 0
124. 0.036 0.036 ↑ 1.0 1 6

Index Scan using fdc_country_translation_vl_i on fdc_country_translation t_10 (cost=0.28..0.84 rows=1 width=48) (actual time=0.006..0.006 rows=1 loops=6)

  • Index Cond: ((c_10.id = country_id) AND (language_id = lang.get_current_lang_id()))
125. 0.018 0.018 ↑ 1.0 1 6

Index Only Scan using fdc_server_list_country_i on fdc_server_list sl_1 (cost=0.13..0.18 rows=1 width=8) (actual time=0.003..0.003 rows=1 loops=6)

  • Index Cond: (country_id = c_10.id)
  • Heap Fetches: 0
126. 0.006 0.006 ↑ 3.0 1 6

Seq Scan on fdc_payment_execution c_11 (cost=0.00..1.03 rows=3 width=146) (actual time=0.001..0.001 rows=1 loops=6)

127. 0.054 0.054 ↑ 1.0 1 6

Seq Scan on fdc_payment_execution_translation t_11 (cost=0.00..1.23 rows=1 width=524) (actual time=0.009..0.009 rows=1 loops=6)

  • Filter: (language_id = lang.get_current_lang_id())
128. 0.007 0.049 ↓ 0.0 0 7

Limit (cost=0.28..8.30 rows=1 width=136) (actual time=0.007..0.007 rows=0 loops=7)

129. 0.042 0.042 ↓ 0.0 0 7

Index Scan using fdc_pts_owner_root_i on fdc_pts_owner own (cost=0.28..8.30 rows=1 width=136) (actual time=0.006..0.006 rows=0 loops=7)

  • Index Cond: (pasport_root_id = pv.root_id)
  • Filter: is_actual
130. 0.529 1.224 ↓ 1.0 6,367 1

Hash (cost=117.65..117.65 rows=6,365 width=16) (actual time=1.224..1.224 rows=6,367 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 363kB
131. 0.695 0.695 ↓ 1.0 6,367 1

Seq Scan on fdc_person manufacturer_per (cost=0.00..117.65 rows=6,365 width=16) (actual time=0.004..0.695 rows=6,367 loops=1)

132. 0.014 0.077 ↓ 0.0 0 7

Limit (cost=8.31..8.31 rows=1 width=108) (actual time=0.011..0.011 rows=0 loops=7)

133. 0.028 0.063 ↓ 0.0 0 7

Sort (cost=8.31..8.31 rows=1 width=108) (actual time=0.009..0.009 rows=0 loops=7)

  • Sort Key: engine_1.engine_kind_id
  • Sort Method: quicksort Memory: 25kB
134. 0.035 0.035 ↓ 0.0 0 7

Index Scan using fdc_pts_engine_psp_i on fdc_pts_engine engine_1 (cost=0.28..8.30 rows=1 width=108) (actual time=0.005..0.005 rows=0 loops=7)

  • Index Cond: (pasport_id = pv.id)
Planning time : 11.422 ms
Execution time : 57,135.136 ms