explain.depesz.com

PostgreSQL's explain analyze made readable

Result: WXRz

Settings
# exclusive inclusive rows x rows loops node
1. 1,258.813 4,585.127 ↑ 43.1 82,211 1

Sort (cost=33,885,469.18..33,894,325.15 rows=3,542,388 width=5,394) (actual time=4,392.831..4,585.127 rows=82,211 loops=1)

  • Sort Key: per.st_register_id, ((f_ipasumi_query.nosauk)::character varying(50)), nogab.kad, nogab.kv, nogab.nog, nogab.anog
  • Sort Method: external merge Disk: 39992kB
2.          

CTE klas_aat

3. 0.054 5.506 ↑ 1.0 24 1

Nested Loop Left Join (cost=0.82..409.66 rows=24 width=88) (actual time=0.985..5.506 rows=24 loops=1)

4. 0.087 5.380 ↑ 1.0 24 1

Nested Loop Left Join (cost=0.82..405.91 rows=24 width=1,334) (actual time=0.919..5.380 rows=24 loops=1)

5. 0.083 3.925 ↑ 1.0 24 1

Nested Loop Left Join (cost=0.41..203.58 rows=24 width=737) (actual time=0.851..3.925 rows=24 loops=1)

6. 0.098 0.098 ↑ 1.0 24 1

Seq Scan on klas_aat klt (cost=0.00..1.24 rows=24 width=140) (actual time=0.087..0.098 rows=24 loops=1)

7. 3.744 3.744 ↑ 1.0 1 24

Index Scan using uniq_per_lang_per_module_newlang on config_langs_new cfl_1 (cost=0.41..8.43 rows=1 width=623) (actual time=0.156..0.156 rows=1 loops=24)

  • Index Cond: (((klt.nosaukums)::text = (basestr)::text) AND (module_id = 8))
8. 1.368 1.368 ↑ 1.0 1 24

Index Scan using uniq_per_lang_per_module_newlang on config_langs_new cfl_1_1 (cost=0.41..8.43 rows=1 width=623) (actual time=0.057..0.057 rows=1 loops=24)

  • Index Cond: (((klt.rinda)::text = (basestr)::text) AND (module_id = 8))
9. 0.014 0.072 ↑ 1.0 1 24

Materialize (cost=0.00..2.85 rows=1 width=3) (actual time=0.003..0.003 rows=1 loops=24)

10. 0.058 0.058 ↑ 1.0 1 1

Seq Scan on config_users_data (cost=0.00..2.84 rows=1 width=3) (actual time=0.056..0.058 rows=1 loops=1)

  • Filter: (((object_category)::text = 'internationalization'::text) AND ((object_name)::text = 'language'::text) AND ((user_name)::name = CURRENT_USER))
  • Rows Removed by Filter: 81
11.          

CTE k_zk

12. 0.045 4.170 ↑ 1.0 37 1

Nested Loop Left Join (cost=0.41..313.16 rows=37 width=520) (actual time=0.401..4.170 rows=37 loops=1)

13. 0.125 4.014 ↑ 1.0 37 1

Nested Loop Left Join (cost=0.41..309.30 rows=37 width=1,117) (actual time=0.316..4.014 rows=37 loops=1)

14. 0.041 0.041 ↑ 1.0 37 1

Seq Scan on k_zemeskategorija klt_1 (cost=0.00..1.37 rows=37 width=520) (actual time=0.026..0.041 rows=37 loops=1)

15. 3.848 3.848 ↑ 1.0 1 37

Index Scan using uniq_per_lang_per_module_newlang on config_langs_new cfl_1_2 (cost=0.41..8.32 rows=1 width=623) (actual time=0.104..0.104 rows=1 loops=37)

  • Index Cond: (((klt_1.nosaukums)::text = (basestr)::text) AND (module_id = 8))
16. 0.050 0.111 ↑ 1.0 1 37

Materialize (cost=0.00..2.85 rows=1 width=3) (actual time=0.002..0.003 rows=1 loops=37)

17. 0.061 0.061 ↑ 1.0 1 1

Seq Scan on config_users_data config_users_data_1 (cost=0.00..2.84 rows=1 width=3) (actual time=0.060..0.061 rows=1 loops=1)

  • Filter: (((object_category)::text = 'internationalization'::text) AND ((object_name)::text = 'language'::text) AND ((user_name)::name = CURRENT_USER))
  • Rows Removed by Filter: 81
18.          

CTE k_sg

19. 0.102 5.873 ↑ 1.0 55 1

Nested Loop Left Join (cost=0.41..457.44 rows=55 width=60) (actual time=0.148..5.873 rows=55 loops=1)

20. 0.168 5.716 ↑ 1.0 55 1

Nested Loop Left Join (cost=0.41..453.22 rows=55 width=693) (actual time=0.082..5.716 rows=55 loops=1)

21. 0.048 0.048 ↑ 1.0 55 1

Seq Scan on klas_sugas klt_2 (cost=0.00..1.55 rows=55 width=96) (actual time=0.027..0.048 rows=55 loops=1)

22. 5.500 5.500 ↑ 1.0 1 55

Index Scan using uniq_per_lang_per_module_newlang on config_langs_new cfl_1_3 (cost=0.41..8.21 rows=1 width=623) (actual time=0.100..0.100 rows=1 loops=55)

  • Index Cond: (((klt_2.nosaukums)::text = (basestr)::text) AND (module_id = 8))
23. 0.001 0.055 ↑ 1.0 1 55

Materialize (cost=0.00..2.85 rows=1 width=3) (actual time=0.001..0.001 rows=1 loops=55)

24. 0.054 0.054 ↑ 1.0 1 1

Seq Scan on config_users_data config_users_data_2 (cost=0.00..2.84 rows=1 width=3) (actual time=0.052..0.054 rows=1 loops=1)

  • Filter: (((object_category)::text = 'internationalization'::text) AND ((object_name)::text = 'language'::text) AND ((user_name)::name = CURRENT_USER))
  • Rows Removed by Filter: 81
25.          

CTE k_psd

26. 0.021 1.087 ↑ 1.0 11 1

Nested Loop Left Join (cost=0.41..97.01 rows=11 width=520) (actual time=0.332..1.087 rows=11 loops=1)

27. 0.037 0.989 ↑ 1.0 11 1

Nested Loop Left Join (cost=0.41..93.86 rows=11 width=1,117) (actual time=0.250..0.989 rows=11 loops=1)

28. 0.039 0.039 ↑ 1.0 11 1

Seq Scan on k_pedsaimndarbveids klt_3 (cost=0.00..1.11 rows=11 width=520) (actual time=0.036..0.039 rows=11 loops=1)

29. 0.913 0.913 ↑ 1.0 1 11

Index Scan using uniq_per_lang_per_module_newlang on config_langs_new cfl_1_4 (cost=0.41..8.43 rows=1 width=623) (actual time=0.083..0.083 rows=1 loops=11)

  • Index Cond: (((klt_3.nosaukums)::text = (basestr)::text) AND (module_id = 8))
30. 0.014 0.077 ↑ 1.0 1 11

Materialize (cost=0.00..2.85 rows=1 width=3) (actual time=0.007..0.007 rows=1 loops=11)

31. 0.063 0.063 ↑ 1.0 1 1

Seq Scan on config_users_data config_users_data_3 (cost=0.00..2.84 rows=1 width=3) (actual time=0.061..0.063 rows=1 loops=1)

  • Filter: (((object_category)::text = 'internationalization'::text) AND ((object_name)::text = 'language'::text) AND ((user_name)::name = CURRENT_USER))
  • Rows Removed by Filter: 81
32.          

CTE k_pcp

33. 0.021 1.453 ↑ 1.0 25 1

Nested Loop Left Join (cost=0.41..215.55 rows=25 width=520) (actual time=0.145..1.453 rows=25 loops=1)

34. 0.050 1.357 ↑ 1.0 25 1

Nested Loop Left Join (cost=0.41..212.02 rows=25 width=1,117) (actual time=0.085..1.357 rows=25 loops=1)

35. 0.032 0.032 ↑ 1.0 25 1

Seq Scan on k_pedcirsanaspan klt_4 (cost=0.00..1.25 rows=25 width=520) (actual time=0.025..0.032 rows=25 loops=1)

36. 1.275 1.275 ↑ 1.0 1 25

Index Scan using uniq_per_lang_per_module_newlang on config_langs_new cfl_1_5 (cost=0.41..8.43 rows=1 width=623) (actual time=0.051..0.051 rows=1 loops=25)

  • Index Cond: (((klt_4.nosaukums)::text = (basestr)::text) AND (module_id = 8))
37. 0.028 0.075 ↑ 1.0 1 25

Materialize (cost=0.00..2.85 rows=1 width=3) (actual time=0.002..0.003 rows=1 loops=25)

38. 0.047 0.047 ↑ 1.0 1 1

Seq Scan on config_users_data config_users_data_4 (cost=0.00..2.84 rows=1 width=3) (actual time=0.045..0.047 rows=1 loops=1)

  • Filter: (((object_category)::text = 'internationalization'::text) AND ((object_name)::text = 'language'::text) AND ((user_name)::name = CURRENT_USER))
  • Rows Removed by Filter: 81
39.          

CTE k_aprb

40. 0.006 0.333 ↑ 1.0 7 1

Nested Loop Left Join (cost=0.41..63.12 rows=7 width=36) (actual time=0.120..0.333 rows=7 loops=1)

41. 0.017 0.257 ↑ 1.0 7 1

Nested Loop Left Join (cost=0.41..60.10 rows=7 width=729) (actual time=0.052..0.257 rows=7 loops=1)

42. 0.023 0.023 ↑ 1.0 7 1

Seq Scan on k_aprob klt_5 (cost=0.00..1.07 rows=7 width=132) (actual time=0.021..0.023 rows=7 loops=1)

43. 0.217 0.217 ↑ 1.0 1 7

Index Scan using uniq_per_lang_per_module_newlang on config_langs_new cfl_1_6 (cost=0.41..8.43 rows=1 width=623) (actual time=0.031..0.031 rows=1 loops=7)

  • Index Cond: (((klt_5.nosaukums)::text = (basestr)::text) AND (module_id = 8))
44. 0.019 0.070 ↑ 1.0 1 7

Materialize (cost=0.00..2.85 rows=1 width=3) (actual time=0.009..0.010 rows=1 loops=7)

45. 0.051 0.051 ↑ 1.0 1 1

Seq Scan on config_users_data config_users_data_5 (cost=0.00..2.84 rows=1 width=3) (actual time=0.050..0.051 rows=1 loops=1)

  • Filter: (((object_category)::text = 'internationalization'::text) AND ((object_name)::text = 'language'::text) AND ((user_name)::name = CURRENT_USER))
  • Rows Removed by Filter: 81
46.          

CTE k_bon

47. 0.044 0.044 ↑ 1.0 8 1

Seq Scan on klas_bonit (cost=0.00..1.08 rows=8 width=130) (actual time=0.042..0.044 rows=8 loops=1)

48.          

CTE k_aizs

49. 0.958 25.420 ↑ 1.0 1,013 1

Nested Loop Left Join (cost=49.79..1,142.48 rows=1,013 width=520) (actual time=24.185..25.420 rows=1,013 loops=1)

50. 0.705 24.462 ↑ 1.0 1,013 1

Hash Right Join (cost=49.79..1,111.78 rows=1,013 width=670) (actual time=24.082..24.462 rows=1,013 loops=1)

  • Hash Cond: ((cfl_1_7.basestr)::text = (kaizs.nosaukums)::text)
51. 22.237 22.237 ↑ 1.0 1,036 1

Seq Scan on config_langs_new cfl_1_7 (cost=0.00..1,056.91 rows=1,036 width=623) (actual time=16.540..22.237 rows=1,036 loops=1)

  • Filter: (module_id = 8)
  • Rows Removed by Filter: 13884
52. 0.401 1.520 ↑ 1.0 1,013 1

Hash (cost=37.13..37.13 rows=1,013 width=73) (actual time=1.520..1.520 rows=1,013 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 113kB
53. 1.119 1.119 ↑ 1.0 1,013 1

Seq Scan on k_aizspazime kaizs (cost=0.00..37.13 rows=1,013 width=73) (actual time=0.840..1.119 rows=1,013 loops=1)

54. 0.000 0.000 ↑ 1.0 1 1,013

Materialize (cost=0.00..2.85 rows=1 width=3) (actual time=0.000..0.000 rows=1 loops=1,013)

55. 0.077 0.077 ↑ 1.0 1 1

Seq Scan on config_users_data config_users_data_6 (cost=0.00..2.84 rows=1 width=3) (actual time=0.075..0.077 rows=1 loops=1)

  • Filter: (((object_category)::text = 'internationalization'::text) AND ((object_name)::text = 'language'::text) AND ((user_name)::name = CURRENT_USER))
  • Rows Removed by Filter: 81
56.          

CTE k_aizs_2

57. 0.902 6.190 ↑ 1.0 1,013 1

Nested Loop Left Join (cost=49.79..1,142.48 rows=1,013 width=520) (actual time=5.178..6.190 rows=1,013 loops=1)

58. 0.662 5.288 ↑ 1.0 1,013 1

Hash Right Join (cost=49.79..1,111.78 rows=1,013 width=670) (actual time=5.002..5.288 rows=1,013 loops=1)

  • Hash Cond: ((cfl_1_8.basestr)::text = (kaizs_1.nosaukums)::text)
59. 3.975 3.975 ↑ 1.0 1,036 1

Seq Scan on config_langs_new cfl_1_8 (cost=0.00..1,056.91 rows=1,036 width=623) (actual time=0.466..3.975 rows=1,036 loops=1)

  • Filter: (module_id = 8)
  • Rows Removed by Filter: 13884
60. 0.483 0.651 ↑ 1.0 1,013 1

Hash (cost=37.13..37.13 rows=1,013 width=73) (actual time=0.651..0.651 rows=1,013 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 113kB
61. 0.168 0.168 ↑ 1.0 1,013 1

Seq Scan on k_aizspazime kaizs_1 (cost=0.00..37.13 rows=1,013 width=73) (actual time=0.047..0.168 rows=1,013 loops=1)

62. 0.000 0.000 ↑ 1.0 1 1,013

Materialize (cost=0.00..2.85 rows=1 width=3) (actual time=0.000..0.000 rows=1 loops=1,013)

63. 0.136 0.136 ↑ 1.0 1 1

Seq Scan on config_users_data config_users_data_7 (cost=0.00..2.84 rows=1 width=3) (actual time=0.134..0.136 rows=1 loops=1)

  • Filter: (((object_category)::text = 'internationalization'::text) AND ((object_name)::text = 'language'::text) AND ((user_name)::name = CURRENT_USER))
  • Rows Removed by Filter: 81
64.          

CTE k_aizs_3

65. 0.606 4.230 ↑ 1.0 1,013 1

Nested Loop Left Join (cost=49.79..1,142.48 rows=1,013 width=520) (actual time=3.494..4.230 rows=1,013 loops=1)

66. 0.390 3.624 ↑ 1.0 1,013 1

Hash Right Join (cost=49.79..1,111.78 rows=1,013 width=670) (actual time=3.425..3.624 rows=1,013 loops=1)

  • Hash Cond: ((cfl_1_9.basestr)::text = (kaizs_2.nosaukums)::text)
67. 2.761 2.761 ↑ 1.0 1,036 1

Seq Scan on config_langs_new cfl_1_9 (cost=0.00..1,056.91 rows=1,036 width=623) (actual time=0.457..2.761 rows=1,036 loops=1)

  • Filter: (module_id = 8)
  • Rows Removed by Filter: 13884
68. 0.345 0.473 ↑ 1.0 1,013 1

Hash (cost=37.13..37.13 rows=1,013 width=73) (actual time=0.472..0.473 rows=1,013 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 113kB
69. 0.128 0.128 ↑ 1.0 1,013 1

Seq Scan on k_aizspazime kaizs_2 (cost=0.00..37.13 rows=1,013 width=73) (actual time=0.036..0.128 rows=1,013 loops=1)

70. 0.000 0.000 ↑ 1.0 1 1,013

Materialize (cost=0.00..2.85 rows=1 width=3) (actual time=0.000..0.000 rows=1 loops=1,013)

71. 0.050 0.050 ↑ 1.0 1 1

Seq Scan on config_users_data config_users_data_8 (cost=0.00..2.84 rows=1 width=3) (actual time=0.049..0.050 rows=1 loops=1)

  • Filter: (((object_category)::text = 'internationalization'::text) AND ((object_name)::text = 'language'::text) AND ((user_name)::name = CURRENT_USER))
  • Rows Removed by Filter: 81
72.          

CTE admu

73. 0.336 0.336 ↑ 1.0 586 1

Seq Scan on klas_adm_local_units_state (cost=0.00..277.86 rows=586 width=24) (actual time=0.011..0.336 rows=586 loops=1)

74.          

CTE admu_reg

75. 0.067 0.067 ↑ 1.0 119 1

Seq Scan on klas_adm_regional_units_state (cost=0.00..4.19 rows=119 width=19) (actual time=0.025..0.067 rows=119 loops=1)

76.          

CTE vmdadm

77. 0.057 0.057 ↑ 1.0 59 1

Seq Scan on klas_adm_local_units_sfs (cost=0.00..1.59 rows=59 width=17) (actual time=0.044..0.057 rows=59 loops=1)

78.          

CTE vmdadm_reg

79. 0.038 0.038 ↑ 1.0 10 1

Seq Scan on klas_adm_regional_units_sfs (cost=0.00..1.10 rows=10 width=72) (actual time=0.036..0.038 rows=10 loops=1)

80.          

CTE k_izc

81. 0.021 0.021 ↑ 1.0 2 1

Seq Scan on k_izc k_izc_1 (cost=0.00..1.02 rows=2 width=520) (actual time=0.020..0.021 rows=2 loops=1)

82.          

CTE k_va

83. 0.026 0.026 ↑ 1.0 49 1

Seq Scan on k_va_kods (cost=0.00..1.49 rows=49 width=520) (actual time=0.020..0.026 rows=49 loops=1)

84.          

CTE k_va_2

85. 0.014 0.014 ↑ 1.0 49 1

Seq Scan on k_va_kods k_va_kods_1 (cost=0.00..1.49 rows=49 width=520) (actual time=0.009..0.014 rows=49 loops=1)

86.          

CTE k_va_3

87. 0.009 0.009 ↑ 1.0 49 1

Seq Scan on k_va_kods k_va_kods_2 (cost=0.00..1.49 rows=49 width=520) (actual time=0.006..0.009 rows=49 loops=1)

88. 837.979 3,326.314 ↑ 43.1 82,211 1

Hash Left Join (cost=233.37..658,562.37 rows=3,542,388 width=5,394) (actual time=150.459..3,326.314 rows=82,211 loops=1)

  • Hash Cond: (f_ipasumi_query.iecirknis_mezizstrades = iecirkni_mezizstr.numurs)
89. 59.542 2,488.314 ↑ 43.1 82,211 1

Hash Left Join (cost=231.99..427,665.92 rows=3,542,388 width=6,586) (actual time=150.393..2,488.314 rows=82,211 loops=1)

  • Hash Cond: (f_ipasumi_query.iecirkna_nr = iecirkni_mezsaimn.numurs)
90. 45.458 2,428.742 ↑ 43.1 82,211 1

Hash Left Join (cost=230.60..418,168.72 rows=3,542,388 width=6,472) (actual time=150.355..2,428.742 rows=82,211 loops=1)

  • Hash Cond: (nogab.biotopa_atzinums = kbea.kods)
91. 47.556 2,383.263 ↑ 43.1 82,211 1

Hash Left Join (cost=229.51..408,843.58 rows=3,542,388 width=6,348) (actual time=150.320..2,383.263 rows=82,211 loops=1)

  • Hash Cond: (nogab.suggested_work_period = kidp.id)
92. 48.210 2,335.681 ↑ 43.1 82,211 1

Hash Left Join (cost=228.45..398,980.63 rows=3,542,388 width=6,224) (actual time=150.280..2,335.681 rows=82,211 loops=1)

  • Hash Cond: (nogab.suggested_work = kid.id)
93. 48.672 2,287.438 ↑ 43.1 82,211 1

Hash Left Join (cost=227.33..387,432.06 rows=3,542,388 width=6,100) (actual time=150.236..2,287.438 rows=82,211 loops=1)

  • Hash Cond: (nogab.fsc_kategorija = category2.kods)
94. 46.020 2,238.725 ↑ 43.1 82,211 1

Hash Left Join (cost=226.18..377,426.52 rows=3,542,388 width=5,976) (actual time=150.186..2,238.725 rows=82,211 loops=1)

  • Hash Cond: (nogab.va_kods3 = k_va_3.kods)
95. 70.567 2,192.662 ↑ 43.1 82,211 1

Hash Left Join (cost=224.58..329,953.39 rows=3,542,388 width=5,464) (actual time=150.133..2,192.662 rows=82,211 loops=1)

  • Hash Cond: (f_zemesgabali_query.adm_local_units_gid = admu.gid)
96. 48.091 2,121.141 ↑ 14.7 82,211 1

Hash Left Join (cost=195.98..202,314.20 rows=1,209,006 width=5,332) (actual time=149.165..2,121.141 rows=82,211 loops=1)

  • Hash Cond: (nogab.va_kods2 = k_va_2.kods)
97. 51.307 2,073.005 ↑ 14.7 82,211 1

Hash Left Join (cost=194.39..186,110.71 rows=1,209,006 width=4,820) (actual time=149.105..2,073.005 rows=82,211 loops=1)

  • Hash Cond: (nogab.va_kods1 = k_va.kods)
98. 67.946 2,021.618 ↑ 14.7 82,211 1

Hash Left Join (cost=192.80..169,907.23 rows=1,209,006 width=4,308) (actual time=149.014..2,021.618 rows=82,211 loops=1)

  • Hash Cond: (nogab.izc = k_izc.kods)
99. 76.206 1,953.637 ↑ 14.7 82,211 1

Hash Left Join (cost=192.73..157,313.35 rows=1,209,006 width=3,796) (actual time=148.965..1,953.637 rows=82,211 loops=1)

  • Hash Cond: (f_zemesgabali_query.adm_local_units_sfs_gid = vmdadm.gid)
100. 50.212 1,877.261 ↑ 14.7 82,211 1

Hash Left Join (cost=190.17..149,210.44 rows=1,209,006 width=3,664) (actual time=148.779..1,877.261 rows=82,211 loops=1)

  • Hash Cond: ((nogab.aizs_3)::text = (k_aizs_3.kods)::text)
101. 58.314 1,822.028 ↑ 3.0 82,211 1

Hash Left Join (cost=157.25..42,786.42 rows=247,347 width=3,148) (actual time=143.732..1,822.028 rows=82,211 loops=1)

  • Hash Cond: ((nogab.aizs_2)::text = (k_aizs_2.kods)::text)
102. 60.684 1,756.318 ↓ 1.6 82,211 1

Hash Left Join (cost=124.33..20,987.25 rows=50,604 width=2,632) (actual time=136.309..1,756.318 rows=82,211 loops=1)

  • Hash Cond: ((nogab.aizs)::text = (k_aizs.kods)::text)
103. 127.927 1,668.540 ↓ 7.9 82,211 1

Hash Left Join (cost=91.40..16,501.21 rows=10,353 width=2,116) (actual time=109.198..1,668.540 rows=82,211 loops=1)

  • Hash Cond: (((nogab.bon)::character varying(2))::text = (k_bon.kods)::text)
104. 58.019 1,540.549 ↓ 7.9 82,211 1

Hash Left Join (cost=91.14..16,419.16 rows=10,353 width=2,116) (actual time=109.111..1,540.549 rows=82,211 loops=1)

  • Hash Cond: (nogab.aprob = k_aprb.kods)
105. 51.915 1,482.174 ↓ 7.9 82,211 1

Hash Left Join (cost=90.92..16,276.58 rows=10,353 width=2,088) (actual time=108.733..1,482.174 rows=82,211 loops=1)

  • Hash Cond: (nogab.p_cirp = k_pcp.kods)
106. 54.372 1,428.749 ↓ 7.9 82,211 1

Hash Left Join (cost=90.10..16,137.02 rows=10,353 width=1,576) (actual time=107.192..1,428.749 rows=82,211 loops=1)

  • Hash Cond: (nogab.p_darb_v = k_psd.kods)
107. 60.025 1,373.252 ↓ 7.9 82,211 1

Hash Join (cost=89.75..15,997.92 rows=10,353 width=1,064) (actual time=106.042..1,373.252 rows=82,211 loops=1)

  • Hash Cond: (f_ipasumi_query.pers_id = per.id)
108. 73.169 1,309.955 ↓ 7.9 82,211 1

Hash Join (cost=39.75..15,920.66 rows=10,353 width=1,041) (actual time=102.745..1,309.955 rows=82,211 loops=1)

  • Hash Cond: (f_zemesgabali_query.mip_id = f_ipasumi_query.mip_id)
109. 55.733 1,186.103 ↓ 39.8 82,524 1

Hash Left Join (cost=17.00..15,530.31 rows=2,071 width=965) (actual time=52.026..1,186.103 rows=82,524 loops=1)

  • Hash Cond: (nogab.s10 = k_sg.kods)
110. 55.735 1,124.339 ↓ 39.8 82,524 1

Hash Left Join (cost=15.22..15,500.76 rows=2,071 width=945) (actual time=45.958..1,124.339 rows=82,524 loops=1)

  • Hash Cond: (nogab.zkat = k_zk.kods)
111. 70.705 1,064.335 ↓ 39.8 82,524 1

Hash Left Join (cost=14.01..15,471.08 rows=2,071 width=433) (actual time=41.657..1,064.335 rows=82,524 loops=1)

  • Hash Cond: (nogab.aat = klas_aat.kods)
112. 335.993 988.019 ↓ 39.8 82,524 1

Nested Loop (cost=13.23..15,441.82 rows=2,071 width=385) (actual time=36.024..988.019 rows=82,524 loops=1)

113. 58.659 321.910 ↓ 39.9 82,529 1

Hash Join (cost=12.81..11,743.77 rows=2,069 width=16) (actual time=35.957..321.910 rows=82,529 loops=1)

  • Hash Cond: (tbl_management_units.cadastral_sys_id = f_zemesgabali_query.zgab_id)
114. 9.974 227.368 ↓ 1.0 82,774 1

Append (cost=0.00..11,399.99 rows=82,743 width=8) (actual time=0.056..227.368 rows=82,774 loops=1)

115. 0.015 0.015 ↓ 0.0 0 1

Seq Scan on tbl_management_units (cost=0.00..0.00 rows=1 width=8) (actual time=0.015..0.015 rows=0 loops=1)

  • Filter: (((state)::text = 'LV'::text) AND (inventory_status = 0) AND (inventory_type = 1))
116. 217.379 217.379 ↓ 1.0 82,774 1

Seq Scan on tbl_management_units_1_0_lv (cost=0.00..11,399.99 rows=82,742 width=8) (actual time=0.041..217.379 rows=82,774 loops=1)

  • Filter: (((state)::text = 'LV'::text) AND (inventory_status = 0) AND (inventory_type = 1))
117. 1.919 35.883 ↓ 1,619.2 8,096 1

Hash (cost=12.75..12.75 rows=5 width=16) (actual time=35.883..35.883 rows=8,096 loops=1)

  • Buckets: 8192 (originally 1024) Batches: 1 (originally 1) Memory Usage: 444kB
118. 33.964 33.964 ↓ 1,619.2 8,096 1

Function Scan on f_zemesgabali_query (cost=0.25..12.75 rows=5 width=16) (actual time=27.105..33.964 rows=8,096 loops=1)

  • Filter: (zg_status = 0)
  • Rows Removed by Filter: 15
119. 330.116 330.116 ↑ 1.0 1 82,529

Index Scan using tbl_management_units_forest_base_id_idx on tbl_management_units_forest nogab (cost=0.42..1.78 rows=1 width=373) (actual time=0.004..0.004 rows=1 loops=82,529)

  • Index Cond: (inventory_base_id = tbl_management_units.gid)
120. 0.045 5.611 ↑ 1.0 24 1

Hash (cost=0.48..0.48 rows=24 width=56) (actual time=5.611..5.611 rows=24 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 10kB
121. 5.566 5.566 ↑ 1.0 24 1

CTE Scan on klas_aat (cost=0.00..0.48 rows=24 width=56) (actual time=0.989..5.566 rows=24 loops=1)

122. 0.036 4.269 ↑ 1.0 37 1

Hash (cost=0.74..0.74 rows=37 width=520) (actual time=4.269..4.269 rows=37 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 11kB
123. 4.233 4.233 ↑ 1.0 37 1

CTE Scan on k_zk (cost=0.00..0.74 rows=37 width=520) (actual time=0.403..4.233 rows=37 loops=1)

124. 0.060 6.031 ↑ 1.0 55 1

Hash (cost=1.10..1.10 rows=55 width=28) (actual time=6.031..6.031 rows=55 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 11kB
125. 5.971 5.971 ↑ 1.0 55 1

CTE Scan on k_sg (cost=0.00..1.10 rows=55 width=28) (actual time=0.150..5.971 rows=55 loops=1)

126. 2.047 50.683 ↓ 5.1 5,061 1

Hash (cost=10.25..10.25 rows=1,000 width=80) (actual time=50.683..50.683 rows=5,061 loops=1)

  • Buckets: 8192 (originally 1024) Batches: 1 (originally 1) Memory Usage: 401kB
127. 48.636 48.636 ↓ 5.1 5,061 1

Function Scan on f_ipasumi_query (cost=0.25..10.25 rows=1,000 width=80) (actual time=46.671..48.636 rows=5,061 loops=1)

128. 0.773 3.272 ↓ 1.0 1,335 1

Hash (cost=33.33..33.33 rows=1,333 width=31) (actual time=3.272..3.272 rows=1,335 loops=1)

  • Buckets: 2048 Batches: 1 Memory Usage: 102kB
129. 2.499 2.499 ↓ 1.0 1,335 1

Seq Scan on tbl_persons per (cost=0.00..33.33 rows=1,333 width=31) (actual time=0.070..2.499 rows=1,335 loops=1)

130. 0.021 1.125 ↑ 1.0 11 1

Hash (cost=0.22..0.22 rows=11 width=520) (actual time=1.125..1.125 rows=11 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
131. 1.104 1.104 ↑ 1.0 11 1

CTE Scan on k_psd (cost=0.00..0.22 rows=11 width=520) (actual time=0.334..1.104 rows=11 loops=1)

132. 0.025 1.510 ↑ 1.0 25 1

Hash (cost=0.50..0.50 rows=25 width=520) (actual time=1.510..1.510 rows=25 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 10kB
133. 1.485 1.485 ↑ 1.0 25 1

CTE Scan on k_pcp (cost=0.00..0.50 rows=25 width=520) (actual time=0.147..1.485 rows=25 loops=1)

134. 0.013 0.356 ↑ 1.0 7 1

Hash (cost=0.14..0.14 rows=7 width=36) (actual time=0.356..0.356 rows=7 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
135. 0.343 0.343 ↑ 1.0 7 1

CTE Scan on k_aprb (cost=0.00..0.14 rows=7 width=36) (actual time=0.122..0.343 rows=7 loops=1)

136. 0.013 0.064 ↑ 1.0 8 1

Hash (cost=0.16..0.16 rows=8 width=12) (actual time=0.063..0.064 rows=8 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
137. 0.051 0.051 ↑ 1.0 8 1

CTE Scan on k_bon (cost=0.00..0.16 rows=8 width=12) (actual time=0.045..0.051 rows=8 loops=1)

138. 0.796 27.094 ↑ 1.0 1,013 1

Hash (cost=20.26..20.26 rows=1,013 width=520) (actual time=27.094..27.094 rows=1,013 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 115kB
139. 26.298 26.298 ↑ 1.0 1,013 1

CTE Scan on k_aizs (cost=0.00..20.26 rows=1,013 width=520) (actual time=24.189..26.298 rows=1,013 loops=1)

140. 0.542 7.396 ↑ 1.0 1,013 1

Hash (cost=20.26..20.26 rows=1,013 width=520) (actual time=7.396..7.396 rows=1,013 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 115kB
141. 6.854 6.854 ↑ 1.0 1,013 1

CTE Scan on k_aizs_2 (cost=0.00..20.26 rows=1,013 width=520) (actual time=5.181..6.854 rows=1,013 loops=1)

142. 0.350 5.021 ↑ 1.0 1,013 1

Hash (cost=20.26..20.26 rows=1,013 width=520) (actual time=5.020..5.021 rows=1,013 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 115kB
143. 4.671 4.671 ↑ 1.0 1,013 1

CTE Scan on k_aizs_3 (cost=0.00..20.26 rows=1,013 width=520) (actual time=3.497..4.671 rows=1,013 loops=1)

144. 0.016 0.170 ↑ 1.0 59 1

Hash (cost=1.83..1.83 rows=59 width=140) (actual time=0.170..0.170 rows=59 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 12kB
145. 0.028 0.154 ↑ 1.0 59 1

Hash Left Join (cost=0.33..1.83 rows=59 width=140) (actual time=0.111..0.154 rows=59 loops=1)

  • Hash Cond: (vmdadm.reg_unit_gid = vmdadm_reg.gid)
146. 0.073 0.073 ↑ 1.0 59 1

CTE Scan on vmdadm (cost=0.00..1.18 rows=59 width=76) (actual time=0.047..0.073 rows=59 loops=1)

147. 0.008 0.053 ↑ 1.0 10 1

Hash (cost=0.20..0.20 rows=10 width=72) (actual time=0.053..0.053 rows=10 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
148. 0.045 0.045 ↑ 1.0 10 1

CTE Scan on vmdadm_reg (cost=0.00..0.20 rows=10 width=72) (actual time=0.038..0.045 rows=10 loops=1)

149. 0.010 0.035 ↑ 1.0 2 1

Hash (cost=0.04..0.04 rows=2 width=520) (actual time=0.035..0.035 rows=2 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
150. 0.025 0.025 ↑ 1.0 2 1

CTE Scan on k_izc (cost=0.00..0.04 rows=2 width=520) (actual time=0.023..0.025 rows=2 loops=1)

151. 0.026 0.080 ↑ 1.0 49 1

Hash (cost=0.98..0.98 rows=49 width=520) (actual time=0.080..0.080 rows=49 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 13kB
152. 0.054 0.054 ↑ 1.0 49 1

CTE Scan on k_va (cost=0.00..0.98 rows=49 width=520) (actual time=0.022..0.054 rows=49 loops=1)

153. 0.014 0.045 ↑ 1.0 49 1

Hash (cost=0.98..0.98 rows=49 width=520) (actual time=0.045..0.045 rows=49 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 13kB
154. 0.031 0.031 ↑ 1.0 49 1

CTE Scan on k_va_2 (cost=0.00..0.98 rows=49 width=520) (actual time=0.011..0.031 rows=49 loops=1)

155. 0.125 0.954 ↑ 1.0 586 1

Hash (cost=21.27..21.27 rows=586 width=140) (actual time=0.954..0.954 rows=586 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 49kB
156. 0.177 0.829 ↑ 1.0 586 1

Hash Left Join (cost=3.87..21.27 rows=586 width=140) (actual time=0.159..0.829 rows=586 loops=1)

  • Hash Cond: (admu.reg_unit_gid = admu_reg.gid)
157. 0.516 0.516 ↑ 1.0 586 1

CTE Scan on admu (cost=0.00..11.72 rows=586 width=76) (actual time=0.012..0.516 rows=586 loops=1)

158. 0.026 0.136 ↑ 1.0 119 1

Hash (cost=2.38..2.38 rows=119 width=72) (actual time=0.136..0.136 rows=119 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 15kB
159. 0.110 0.110 ↑ 1.0 119 1

CTE Scan on admu_reg (cost=0.00..2.38 rows=119 width=72) (actual time=0.028..0.110 rows=119 loops=1)

160. 0.016 0.043 ↑ 1.0 49 1

Hash (cost=0.98..0.98 rows=49 width=520) (actual time=0.043..0.043 rows=49 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 13kB
161. 0.027 0.027 ↑ 1.0 49 1

CTE Scan on k_va_3 (cost=0.00..0.98 rows=49 width=520) (actual time=0.007..0.027 rows=49 loops=1)

162. 0.011 0.041 ↑ 1.0 7 1

Hash (cost=1.07..1.07 rows=7 width=132) (actual time=0.040..0.041 rows=7 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
163. 0.030 0.030 ↑ 1.0 7 1

Seq Scan on k_fsc_categories category2 (cost=0.00..1.07 rows=7 width=132) (actual time=0.029..0.030 rows=7 loops=1)

164. 0.013 0.033 ↑ 1.0 5 1

Hash (cost=1.05..1.05 rows=5 width=132) (actual time=0.032..0.033 rows=5 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
165. 0.020 0.020 ↑ 1.0 5 1

Seq Scan on k_ieteicamas_darbibas kid (cost=0.00..1.05 rows=5 width=132) (actual time=0.019..0.020 rows=5 loops=1)

166. 0.007 0.026 ↑ 1.0 3 1

Hash (cost=1.03..1.03 rows=3 width=132) (actual time=0.026..0.026 rows=3 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
167. 0.019 0.019 ↑ 1.0 3 1

Seq Scan on k_ieteicamas_darbibas_periodi kidp (cost=0.00..1.03 rows=3 width=132) (actual time=0.017..0.019 rows=3 loops=1)

168. 0.006 0.021 ↑ 1.0 4 1

Hash (cost=1.04..1.04 rows=4 width=132) (actual time=0.021..0.021 rows=4 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
169. 0.015 0.015 ↑ 1.0 4 1

Seq Scan on k_biotopu_eksperta_atzinumi kbea (cost=0.00..1.04 rows=4 width=132) (actual time=0.015..0.015 rows=4 loops=1)

170. 0.008 0.030 ↑ 1.0 17 1

Hash (cost=1.17..1.17 rows=17 width=122) (actual time=0.030..0.030 rows=17 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
171. 0.022 0.022 ↑ 1.0 17 1

Seq Scan on klas_iecirkni iecirkni_mezsaimn (cost=0.00..1.17 rows=17 width=122) (actual time=0.019..0.022 rows=17 loops=1)

172. 0.013 0.021 ↑ 1.0 17 1

Hash (cost=1.17..1.17 rows=17 width=122) (actual time=0.021..0.021 rows=17 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
173. 0.008 0.008 ↑ 1.0 17 1

Seq Scan on klas_iecirkni iecirkni_mezizstr (cost=0.00..1.17 rows=17 width=122) (actual time=0.007..0.008 rows=17 loops=1)