explain.depesz.com

PostgreSQL's explain analyze made readable

Result: ccGA : Optimization for: Optimization for: plan #DBBQ; plan #DfOA

Settings

Optimization path:

Optimization(s) for this plan:

# exclusive inclusive rows x rows loops node
1. 34.743 3,464.569 ↑ 2.1 940,686 1

Limit (cost=40,669.30..268,319.95 rows=2,000,000 width=243) (actual time=162.344..3,464.569 rows=940,686 loops=1)

2. 2,544.460 3,429.826 ↑ 6.5 940,686 1

Hash Right Join (cost=40,669.30..738,813.07 rows=6,133,466 width=243) (actual time=162.343..3,429.826 rows=940,686 loops=1)

  • Hash Cond: (r.id = e.raw_id)
3. 219.025 723.131 ↑ 1.0 6,147,020 1

Append (cost=0.00..268,829.28 rows=6,155,419 width=199) (actual time=0.006..723.131 rows=6,147,020 loops=1)

4. 2.133 2.133 ↑ 1.0 23,832 1

Seq Scan on raws_00 r (cost=0.00..923.63 rows=23,863 width=199) (actual time=0.005..2.133 rows=23,832 loops=1)

5. 2.119 2.119 ↑ 1.0 24,081 1

Seq Scan on raws_01 r_1 (cost=0.00..933.32 rows=24,132 width=199) (actual time=0.004..2.119 rows=24,081 loops=1)

6. 2.111 2.111 ↑ 1.0 24,135 1

Seq Scan on raws_02 r_2 (cost=0.00..933.86 rows=24,186 width=198) (actual time=0.004..2.111 rows=24,135 loops=1)

7. 2.245 2.245 ↓ 1.0 24,084 1

Seq Scan on raws_03 r_3 (cost=0.00..931.66 rows=24,066 width=199) (actual time=0.004..2.245 rows=24,084 loops=1)

8. 2.196 2.196 ↑ 1.0 24,228 1

Seq Scan on raws_04 r_4 (cost=0.00..938.97 rows=24,297 width=199) (actual time=0.004..2.196 rows=24,228 loops=1)

9. 2.218 2.218 ↓ 1.0 24,133 1

Seq Scan on raws_05 r_5 (cost=0.00..934.20 rows=24,120 width=199) (actual time=0.004..2.218 rows=24,133 loops=1)

10. 2.129 2.129 ↑ 1.0 23,821 1

Seq Scan on raws_06 r_6 (cost=0.00..922.65 rows=23,865 width=199) (actual time=0.004..2.129 rows=23,821 loops=1)

11. 2.110 2.110 ↑ 1.0 24,029 1

Seq Scan on raws_07 r_7 (cost=0.00..929.62 rows=24,062 width=198) (actual time=0.004..2.110 rows=24,029 loops=1)

12. 2.205 2.205 ↑ 1.0 24,049 1

Seq Scan on raws_08 r_8 (cost=0.00..931.77 rows=24,077 width=199) (actual time=0.004..2.205 rows=24,049 loops=1)

13. 2.083 2.083 ↑ 1.0 23,731 1

Seq Scan on raws_09 r_9 (cost=0.00..918.54 rows=23,754 width=199) (actual time=0.004..2.083 rows=23,731 loops=1)

14. 2.078 2.078 ↑ 1.0 23,911 1

Seq Scan on raws_0a r_10 (cost=0.00..926.72 rows=23,972 width=199) (actual time=0.004..2.078 rows=23,911 loops=1)

15. 2.083 2.083 ↑ 1.0 24,006 1

Seq Scan on raws_0b r_11 (cost=0.00..929.61 rows=24,061 width=199) (actual time=0.004..2.083 rows=24,006 loops=1)

16. 2.100 2.100 ↓ 1.0 23,924 1

Seq Scan on raws_0c r_12 (cost=0.00..926.18 rows=23,918 width=199) (actual time=0.004..2.100 rows=23,924 loops=1)

17. 2.150 2.150 ↑ 1.0 23,985 1

Seq Scan on raws_0d r_13 (cost=0.00..928.40 rows=24,040 width=199) (actual time=0.004..2.150 rows=23,985 loops=1)

18. 2.299 2.299 ↑ 1.0 23,908 1

Seq Scan on raws_0e r_14 (cost=0.00..925.40 rows=23,940 width=199) (actual time=0.004..2.299 rows=23,908 loops=1)

19. 2.157 2.157 ↑ 1.0 23,852 1

Seq Scan on raws_0f r_15 (cost=0.00..922.64 rows=23,864 width=199) (actual time=0.004..2.157 rows=23,852 loops=1)

20. 2.138 2.138 ↓ 1.0 24,114 1

Seq Scan on raws_10 r_16 (cost=0.00..932.97 rows=24,097 width=199) (actual time=0.004..2.138 rows=24,114 loops=1)

21. 2.293 2.293 ↑ 1.0 23,998 1

Seq Scan on raws_11 r_17 (cost=0.00..929.40 rows=24,040 width=199) (actual time=0.004..2.293 rows=23,998 loops=1)

22. 2.155 2.155 ↓ 1.0 23,927 1

Seq Scan on raws_12 r_18 (cost=0.00..926.18 rows=23,918 width=199) (actual time=0.004..2.155 rows=23,927 loops=1)

23. 2.205 2.205 ↑ 1.0 24,082 1

Seq Scan on raws_13 r_19 (cost=0.00..932.33 rows=24,133 width=198) (actual time=0.005..2.205 rows=24,082 loops=1)

24. 2.200 2.200 ↑ 1.0 24,069 1

Seq Scan on raws_14 r_20 (cost=0.00..931.76 rows=24,076 width=199) (actual time=0.004..2.200 rows=24,069 loops=1)

25. 2.177 2.177 ↑ 1.0 24,342 1

Seq Scan on raws_15 r_21 (cost=0.00..942.48 rows=24,348 width=199) (actual time=0.004..2.177 rows=24,342 loops=1)

26. 1.993 1.993 ↑ 1.0 24,143 1

Seq Scan on raws_16 r_22 (cost=0.00..935.99 rows=24,199 width=199) (actual time=0.004..1.993 rows=24,143 loops=1)

27. 1.936 1.936 ↑ 1.0 23,846 1

Seq Scan on raws_17 r_23 (cost=0.00..922.78 rows=23,878 width=198) (actual time=0.004..1.936 rows=23,846 loops=1)

28. 1.947 1.947 ↑ 1.0 23,845 1

Seq Scan on raws_18 r_24 (cost=0.00..922.95 rows=23,895 width=198) (actual time=0.003..1.947 rows=23,845 loops=1)

29. 2.079 2.079 ↑ 1.0 23,947 1

Seq Scan on raws_19 r_25 (cost=0.00..928.10 rows=24,010 width=199) (actual time=0.004..2.079 rows=23,947 loops=1)

30. 1.956 1.956 ↑ 1.0 23,712 1

Seq Scan on raws_1a r_26 (cost=0.00..917.64 rows=23,764 width=199) (actual time=0.004..1.956 rows=23,712 loops=1)

31. 2.011 2.011 ↑ 1.0 24,009 1

Seq Scan on raws_1b r_27 (cost=0.00..929.41 rows=24,041 width=199) (actual time=0.003..2.011 rows=24,009 loops=1)

32. 2.010 2.010 ↑ 1.0 24,032 1

Seq Scan on raws_1c r_28 (cost=0.00..930.94 rows=24,094 width=199) (actual time=0.010..2.010 rows=24,032 loops=1)

33. 1.940 1.940 ↑ 1.0 23,724 1

Seq Scan on raws_1d r_29 (cost=0.00..919.69 rows=23,769 width=199) (actual time=0.005..1.940 rows=23,724 loops=1)

34. 2.021 2.021 ↑ 1.0 24,097 1

Seq Scan on raws_1e r_30 (cost=0.00..934.63 rows=24,163 width=199) (actual time=0.003..2.021 rows=24,097 loops=1)

35. 2.099 2.099 ↑ 1.0 23,928 1

Seq Scan on raws_1f r_31 (cost=0.00..926.96 rows=23,996 width=198) (actual time=0.003..2.099 rows=23,928 loops=1)

36. 2.024 2.024 ↑ 1.0 24,059 1

Seq Scan on raws_20 r_32 (cost=0.00..932.37 rows=24,137 width=199) (actual time=0.003..2.024 rows=24,059 loops=1)

37. 1.984 1.984 ↓ 1.0 24,205 1

Seq Scan on raws_21 r_33 (cost=0.00..936.97 rows=24,197 width=199) (actual time=0.005..1.984 rows=24,205 loops=1)

38. 1.934 1.934 ↓ 1.0 24,067 1

Seq Scan on raws_22 r_34 (cost=0.00..930.64 rows=24,064 width=199) (actual time=0.004..1.934 rows=24,067 loops=1)

39. 1.979 1.979 ↑ 1.0 23,970 1

Seq Scan on raws_23 r_35 (cost=0.00..927.97 rows=23,997 width=199) (actual time=0.003..1.979 rows=23,970 loops=1)

40. 1.951 1.951 ↑ 1.0 23,909 1

Seq Scan on raws_24 r_36 (cost=0.00..925.45 rows=23,945 width=198) (actual time=0.004..1.951 rows=23,909 loops=1)

41. 2.014 2.014 ↑ 1.0 24,121 1

Seq Scan on raws_25 r_37 (cost=0.00..933.64 rows=24,164 width=199) (actual time=0.005..2.014 rows=24,121 loops=1)

42. 2.020 2.020 ↑ 1.0 24,047 1

Seq Scan on raws_26 r_38 (cost=0.00..931.66 rows=24,066 width=199) (actual time=0.004..2.020 rows=24,047 loops=1)

43. 1.964 1.964 ↑ 1.0 24,171 1

Seq Scan on raws_27 r_39 (cost=0.00..935.97 rows=24,197 width=199) (actual time=0.004..1.964 rows=24,171 loops=1)

44. 1.959 1.959 ↑ 1.0 23,949 1

Seq Scan on raws_28 r_40 (cost=0.00..927.79 rows=23,979 width=199) (actual time=0.003..1.959 rows=23,949 loops=1)

45. 1.954 1.954 ↑ 1.0 23,853 1

Seq Scan on raws_29 r_41 (cost=0.00..923.58 rows=23,858 width=199) (actual time=0.005..1.954 rows=23,853 loops=1)

46. 2.012 2.012 ↑ 1.0 23,978 1

Seq Scan on raws_2a r_42 (cost=0.00..929.32 rows=24,032 width=199) (actual time=0.004..2.012 rows=23,978 loops=1)

47. 1.974 1.974 ↑ 1.0 24,027 1

Seq Scan on raws_2b r_43 (cost=0.00..930.75 rows=24,075 width=199) (actual time=0.004..1.974 rows=24,027 loops=1)

48. 1.944 1.944 ↓ 1.0 24,038 1

Seq Scan on raws_2c r_44 (cost=0.00..930.30 rows=24,030 width=199) (actual time=0.004..1.944 rows=24,038 loops=1)

49. 1.992 1.992 ↑ 1.0 24,198 1

Seq Scan on raws_2d r_45 (cost=0.00..937.45 rows=24,245 width=199) (actual time=0.005..1.992 rows=24,198 loops=1)

50. 1.940 1.940 ↓ 1.0 23,832 1

Seq Scan on raws_2e r_46 (cost=0.00..922.11 rows=23,811 width=199) (actual time=0.004..1.940 rows=23,832 loops=1)

51. 1.988 1.988 ↑ 1.0 23,994 1

Seq Scan on raws_2f r_47 (cost=0.00..928.20 rows=24,020 width=199) (actual time=0.004..1.988 rows=23,994 loops=1)

52. 1.981 1.981 ↓ 1.0 24,139 1

Seq Scan on raws_30 r_48 (cost=0.00..934.38 rows=24,138 width=199) (actual time=0.005..1.981 rows=24,139 loops=1)

53. 1.988 1.988 ↑ 1.0 23,767 1

Seq Scan on raws_31 r_49 (cost=0.00..919.92 rows=23,792 width=199) (actual time=0.004..1.988 rows=23,767 loops=1)

54. 1.956 1.956 ↑ 1.0 24,123 1

Seq Scan on raws_32 r_50 (cost=0.00..935.02 rows=24,202 width=199) (actual time=0.004..1.956 rows=24,123 loops=1)

55. 1.959 1.959 ↑ 1.0 24,226 1

Seq Scan on raws_33 r_51 (cost=0.00..937.27 rows=24,227 width=199) (actual time=0.003..1.959 rows=24,226 loops=1)

56. 1.984 1.984 ↑ 1.0 23,925 1

Seq Scan on raws_34 r_52 (cost=0.00..926.72 rows=23,972 width=199) (actual time=0.005..1.984 rows=23,925 loops=1)

57. 1.927 1.927 ↑ 1.0 23,982 1

Seq Scan on raws_35 r_53 (cost=0.00..927.84 rows=23,984 width=199) (actual time=0.004..1.927 rows=23,982 loops=1)

58. 1.923 1.923 ↑ 1.0 23,833 1

Seq Scan on raws_36 r_54 (cost=0.00..922.63 rows=23,863 width=199) (actual time=0.003..1.923 rows=23,833 loops=1)

59. 1.937 1.937 ↑ 1.0 23,779 1

Seq Scan on raws_37 r_55 (cost=0.00..921.20 rows=23,820 width=199) (actual time=0.004..1.937 rows=23,779 loops=1)

60. 1.955 1.955 ↑ 1.0 24,062 1

Seq Scan on raws_38 r_56 (cost=0.00..930.86 rows=24,086 width=199) (actual time=0.005..1.955 rows=24,062 loops=1)

61. 1.959 1.959 ↑ 1.0 23,980 1

Seq Scan on raws_39 r_57 (cost=0.00..927.92 rows=23,992 width=199) (actual time=0.003..1.959 rows=23,980 loops=1)

62. 1.951 1.951 ↑ 1.0 23,836 1

Seq Scan on raws_3a r_58 (cost=0.00..923.58 rows=23,858 width=199) (actual time=0.003..1.951 rows=23,836 loops=1)

63. 1.995 1.995 ↑ 1.0 24,222 1

Seq Scan on raws_3b r_59 (cost=0.00..938.58 rows=24,258 width=199) (actual time=0.003..1.995 rows=24,222 loops=1)

64. 1.917 1.917 ↑ 1.0 23,697 1

Seq Scan on raws_3c r_60 (cost=0.00..918.52 rows=23,752 width=199) (actual time=0.005..1.917 rows=23,697 loops=1)

65. 1.984 1.984 ↑ 1.0 24,098 1

Seq Scan on raws_3d r_61 (cost=0.00..933.45 rows=24,145 width=199) (actual time=0.003..1.984 rows=24,098 loops=1)

66. 1.937 1.937 ↑ 1.0 23,989 1

Seq Scan on raws_3e r_62 (cost=0.00..929.42 rows=24,042 width=199) (actual time=0.004..1.937 rows=23,989 loops=1)

67. 1.977 1.977 ↑ 1.0 23,848 1

Seq Scan on raws_3f r_63 (cost=0.00..922.77 rows=23,877 width=198) (actual time=0.004..1.977 rows=23,848 loops=1)

68. 1.921 1.921 ↑ 1.0 23,827 1

Seq Scan on raws_40 r_64 (cost=0.00..922.42 rows=23,842 width=199) (actual time=0.005..1.921 rows=23,827 loops=1)

69. 1.940 1.940 ↑ 1.0 23,954 1

Seq Scan on raws_41 r_65 (cost=0.00..927.56 rows=23,956 width=199) (actual time=0.004..1.940 rows=23,954 loops=1)

70. 1.951 1.951 ↑ 1.0 24,151 1

Seq Scan on raws_42 r_66 (cost=0.00..936.02 rows=24,202 width=199) (actual time=0.003..1.951 rows=24,151 loops=1)

71. 2.009 2.009 ↑ 1.0 24,092 1

Seq Scan on raws_43 r_67 (cost=0.00..933.58 rows=24,158 width=199) (actual time=0.003..2.009 rows=24,092 loops=1)

72. 1.943 1.943 ↑ 1.0 23,631 1

Seq Scan on raws_44 r_68 (cost=0.00..915.92 rows=23,692 width=199) (actual time=0.005..1.943 rows=23,631 loops=1)

73. 1.993 1.993 ↑ 1.0 24,196 1

Seq Scan on raws_45 r_69 (cost=0.00..937.51 rows=24,251 width=199) (actual time=0.003..1.993 rows=24,196 loops=1)

74. 1.976 1.976 ↑ 1.0 23,711 1

Seq Scan on raws_46 r_70 (cost=0.00..918.39 rows=23,739 width=199) (actual time=0.003..1.976 rows=23,711 loops=1)

75. 1.965 1.965 ↑ 1.0 23,964 1

Seq Scan on raws_47 r_71 (cost=0.00..926.96 rows=23,996 width=199) (actual time=0.003..1.965 rows=23,964 loops=1)

76. 1.946 1.946 ↑ 1.0 23,854 1

Seq Scan on raws_48 r_72 (cost=0.00..924.13 rows=23,913 width=199) (actual time=0.005..1.946 rows=23,854 loops=1)

77. 1.974 1.974 ↑ 1.0 23,774 1

Seq Scan on raws_49 r_73 (cost=0.00..919.75 rows=23,775 width=199) (actual time=0.003..1.974 rows=23,774 loops=1)

78. 2.010 2.010 ↑ 1.0 24,169 1

Seq Scan on raws_4a r_74 (cost=0.00..936.01 rows=24,201 width=199) (actual time=0.004..2.010 rows=24,169 loops=1)

79. 2.014 2.014 ↑ 1.0 24,179 1

Seq Scan on raws_4b r_75 (cost=0.00..935.85 rows=24,185 width=199) (actual time=0.004..2.014 rows=24,179 loops=1)

80. 1.935 1.935 ↑ 1.0 23,992 1

Seq Scan on raws_4c r_76 (cost=0.00..929.58 rows=24,058 width=199) (actual time=0.005..1.935 rows=23,992 loops=1)

81. 1.930 1.930 ↑ 1.0 23,894 1

Seq Scan on raws_4d r_77 (cost=0.00..925.48 rows=23,948 width=199) (actual time=0.004..1.930 rows=23,894 loops=1)

82. 1.920 1.920 ↑ 1.0 24,166 1

Seq Scan on raws_4e r_78 (cost=0.00..935.97 rows=24,197 width=199) (actual time=0.004..1.920 rows=24,166 loops=1)

83. 2.008 2.008 ↑ 1.0 24,133 1

Seq Scan on raws_4f r_79 (cost=0.00..934.66 rows=24,166 width=199) (actual time=0.003..2.008 rows=24,133 loops=1)

84. 1.911 1.911 ↓ 1.0 24,039 1

Seq Scan on raws_50 r_80 (cost=0.00..930.36 rows=24,036 width=199) (actual time=0.006..1.911 rows=24,039 loops=1)

85. 1.896 1.896 ↑ 1.0 23,822 1

Seq Scan on raws_51 r_81 (cost=0.00..922.40 rows=23,840 width=199) (actual time=0.003..1.896 rows=23,822 loops=1)

86. 1.911 1.911 ↑ 1.0 24,022 1

Seq Scan on raws_52 r_82 (cost=0.00..930.34 rows=24,034 width=199) (actual time=0.003..1.911 rows=24,022 loops=1)

87. 1.946 1.946 ↑ 1.0 23,725 1

Seq Scan on raws_53 r_83 (cost=0.00..918.80 rows=23,780 width=199) (actual time=0.003..1.946 rows=23,725 loops=1)

88. 1.924 1.924 ↑ 1.0 24,085 1

Seq Scan on raws_54 r_84 (cost=0.00..933.14 rows=24,114 width=199) (actual time=0.005..1.924 rows=24,085 loops=1)

89. 1.899 1.899 ↑ 1.0 23,910 1

Seq Scan on raws_55 r_85 (cost=0.00..926.46 rows=23,946 width=199) (actual time=0.003..1.899 rows=23,910 loops=1)

90. 1.904 1.904 ↓ 1.0 24,050 1

Seq Scan on raws_56 r_86 (cost=0.00..930.34 rows=24,034 width=199) (actual time=0.003..1.904 rows=24,050 loops=1)

91. 1.891 1.891 ↑ 1.0 24,062 1

Seq Scan on raws_57 r_87 (cost=0.00..932.06 rows=24,106 width=199) (actual time=0.003..1.891 rows=24,062 loops=1)

92. 1.903 1.903 ↑ 1.0 24,100 1

Seq Scan on raws_58 r_88 (cost=0.00..933.53 rows=24,153 width=199) (actual time=0.005..1.903 rows=24,100 loops=1)

93. 1.898 1.898 ↓ 1.0 24,171 1

Seq Scan on raws_59 r_89 (cost=0.00..935.68 rows=24,168 width=199) (actual time=0.003..1.898 rows=24,171 loops=1)

94. 1.879 1.879 ↑ 1.0 23,922 1

Seq Scan on raws_5a r_90 (cost=0.00..927.88 rows=23,988 width=199) (actual time=0.003..1.879 rows=23,922 loops=1)

95. 1.893 1.893 ↑ 1.0 24,091 1

Seq Scan on raws_5b r_91 (cost=0.00..933.15 rows=24,115 width=199) (actual time=0.003..1.893 rows=24,091 loops=1)

96. 1.907 1.907 ↑ 1.0 23,915 1

Seq Scan on raws_5c r_92 (cost=0.00..926.20 rows=23,920 width=199) (actual time=0.005..1.907 rows=23,915 loops=1)

97. 1.889 1.889 ↑ 1.0 24,009 1

Seq Scan on raws_5d r_93 (cost=0.00..930.12 rows=24,012 width=199) (actual time=0.004..1.889 rows=24,009 loops=1)

98. 1.909 1.909 ↑ 1.0 24,109 1

Seq Scan on raws_5e r_94 (cost=0.00..933.67 rows=24,167 width=199) (actual time=0.004..1.909 rows=24,109 loops=1)

99. 1.894 1.894 ↑ 1.0 23,893 1

Seq Scan on raws_5f r_95 (cost=0.00..925.40 rows=23,940 width=199) (actual time=0.003..1.894 rows=23,893 loops=1)

100. 1.891 1.891 ↑ 1.0 24,042 1

Seq Scan on raws_60 r_96 (cost=0.00..930.82 rows=24,082 width=199) (actual time=0.005..1.891 rows=24,042 loops=1)

101. 1.899 1.899 ↑ 1.0 23,977 1

Seq Scan on raws_61 r_97 (cost=0.00..928.80 rows=23,980 width=199) (actual time=0.003..1.899 rows=23,977 loops=1)

102. 2.014 2.014 ↑ 1.0 24,185 1

Seq Scan on raws_62 r_98 (cost=0.00..937.40 rows=24,240 width=199) (actual time=0.004..2.014 rows=24,185 loops=1)

103. 1.924 1.924 ↑ 1.0 24,166 1

Seq Scan on raws_63 r_99 (cost=0.00..936.41 rows=24,241 width=199) (actual time=0.004..1.924 rows=24,166 loops=1)

104. 1.920 1.920 ↑ 1.0 23,770 1

Seq Scan on raws_64 r_100 (cost=0.00..921.11 rows=23,811 width=199) (actual time=0.006..1.920 rows=23,770 loops=1)

105. 1.886 1.886 ↑ 1.0 23,865 1

Seq Scan on raws_65 r_101 (cost=0.00..924.18 rows=23,918 width=199) (actual time=0.003..1.886 rows=23,865 loops=1)

106. 1.878 1.878 ↑ 1.0 23,868 1

Seq Scan on raws_66 r_102 (cost=0.00..923.73 rows=23,873 width=199) (actual time=0.004..1.878 rows=23,868 loops=1)

107. 1.918 1.918 ↑ 1.0 24,343 1

Seq Scan on raws_67 r_103 (cost=0.00..941.79 rows=24,379 width=199) (actual time=0.003..1.918 rows=24,343 loops=1)

108. 1.920 1.920 ↑ 1.0 23,949 1

Seq Scan on raws_68 r_104 (cost=0.00..928.29 rows=24,029 width=198) (actual time=0.005..1.920 rows=23,949 loops=1)

109. 1.896 1.896 ↑ 1.0 24,068 1

Seq Scan on raws_69 r_105 (cost=0.00..932.17 rows=24,117 width=198) (actual time=0.003..1.896 rows=24,068 loops=1)

110. 1.936 1.936 ↑ 1.0 24,071 1

Seq Scan on raws_6a r_106 (cost=0.00..933.02 rows=24,102 width=199) (actual time=0.004..1.936 rows=24,071 loops=1)

111. 1.957 1.957 ↑ 1.0 24,035 1

Seq Scan on raws_6b r_107 (cost=0.00..930.70 rows=24,070 width=199) (actual time=0.004..1.957 rows=24,035 loops=1)

112. 1.897 1.897 ↓ 1.0 23,943 1

Seq Scan on raws_6c r_108 (cost=0.00..926.39 rows=23,939 width=199) (actual time=0.005..1.897 rows=23,943 loops=1)

113. 1.886 1.886 ↑ 1.0 23,894 1

Seq Scan on raws_6d r_109 (cost=0.00..925.05 rows=23,905 width=199) (actual time=0.003..1.886 rows=23,894 loops=1)

114. 1.920 1.920 ↑ 1.0 24,166 1

Seq Scan on raws_6e r_110 (cost=0.00..935.83 rows=24,183 width=199) (actual time=0.004..1.920 rows=24,166 loops=1)

115. 1.958 1.958 ↑ 1.0 24,145 1

Seq Scan on raws_6f r_111 (cost=0.00..935.87 rows=24,187 width=199) (actual time=0.004..1.958 rows=24,145 loops=1)

116. 1.893 1.893 ↑ 1.0 24,023 1

Seq Scan on raws_70 r_112 (cost=0.00..929.61 rows=24,061 width=199) (actual time=0.004..1.893 rows=24,023 loops=1)

117. 1.917 1.917 ↑ 1.0 24,149 1

Seq Scan on raws_71 r_113 (cost=0.00..934.51 rows=24,151 width=199) (actual time=0.003..1.917 rows=24,149 loops=1)

118. 1.905 1.905 ↑ 1.0 23,926 1

Seq Scan on raws_72 r_114 (cost=0.00..926.78 rows=23,978 width=199) (actual time=0.004..1.905 rows=23,926 loops=1)

119. 1.889 1.889 ↑ 1.0 23,944 1

Seq Scan on raws_73 r_115 (cost=0.00..928.01 rows=24,001 width=199) (actual time=0.005..1.889 rows=23,944 loops=1)

120. 1.910 1.910 ↑ 1.0 24,134 1

Seq Scan on raws_74 r_116 (cost=0.00..934.72 rows=24,172 width=199) (actual time=0.004..1.910 rows=24,134 loops=1)

121. 1.875 1.875 ↑ 1.0 23,904 1

Seq Scan on raws_75 r_117 (cost=0.00..925.25 rows=23,925 width=199) (actual time=0.004..1.875 rows=23,904 loops=1)

122. 1.912 1.912 ↑ 1.0 24,302 1

Seq Scan on raws_76 r_118 (cost=0.00..941.43 rows=24,343 width=199) (actual time=0.003..1.912 rows=24,302 loops=1)

123. 1.910 1.910 ↓ 1.0 24,106 1

Seq Scan on raws_77 r_119 (cost=0.00..933.01 rows=24,101 width=199) (actual time=0.005..1.910 rows=24,106 loops=1)

124. 1.907 1.907 ↑ 1.0 24,294 1

Seq Scan on raws_78 r_120 (cost=0.00..941.28 rows=24,328 width=199) (actual time=0.003..1.907 rows=24,294 loops=1)

125. 1.900 1.900 ↑ 1.0 23,781 1

Seq Scan on raws_79 r_121 (cost=0.00..921.42 rows=23,842 width=198) (actual time=0.004..1.900 rows=23,781 loops=1)

126. 2.024 2.024 ↑ 1.0 24,203 1

Seq Scan on raws_7a r_122 (cost=0.00..937.30 rows=24,230 width=199) (actual time=0.003..2.024 rows=24,203 loops=1)

127. 1.906 1.906 ↑ 1.0 24,043 1

Seq Scan on raws_7b r_123 (cost=0.00..930.60 rows=24,060 width=199) (actual time=0.005..1.906 rows=24,043 loops=1)

128. 1.941 1.941 ↑ 1.0 24,352 1

Seq Scan on raws_7c r_124 (cost=0.00..943.20 rows=24,420 width=199) (actual time=0.003..1.941 rows=24,352 loops=1)

129. 1.887 1.887 ↑ 1.0 23,976 1

Seq Scan on raws_7d r_125 (cost=0.00..929.20 rows=24,020 width=199) (actual time=0.003..1.887 rows=23,976 loops=1)

130. 1.942 1.942 ↑ 1.0 24,195 1

Seq Scan on raws_7e r_126 (cost=0.00..937.70 rows=24,270 width=198) (actual time=0.010..1.942 rows=24,195 loops=1)

131. 1.920 1.920 ↑ 1.0 23,804 1

Seq Scan on raws_7f r_127 (cost=0.00..921.09 rows=23,809 width=199) (actual time=0.006..1.920 rows=23,804 loops=1)

132. 1.911 1.911 ↑ 1.0 24,081 1

Seq Scan on raws_80 r_128 (cost=0.00..933.17 rows=24,117 width=199) (actual time=0.003..1.911 rows=24,081 loops=1)

133. 1.916 1.916 ↑ 1.0 24,048 1

Seq Scan on raws_81 r_129 (cost=0.00..930.85 rows=24,085 width=199) (actual time=0.003..1.916 rows=24,048 loops=1)

134. 2.000 2.000 ↑ 1.0 24,019 1

Seq Scan on raws_82 r_130 (cost=0.00..929.39 rows=24,039 width=199) (actual time=0.003..2.000 rows=24,019 loops=1)

135. 1.915 1.915 ↑ 1.0 24,165 1

Seq Scan on raws_83 r_131 (cost=0.00..936.04 rows=24,204 width=199) (actual time=0.005..1.915 rows=24,165 loops=1)

136. 1.869 1.869 ↑ 1.0 23,947 1

Seq Scan on raws_84 r_132 (cost=0.00..927.73 rows=23,973 width=199) (actual time=0.003..1.869 rows=23,947 loops=1)

137. 1.887 1.887 ↑ 1.0 23,896 1

Seq Scan on raws_85 r_133 (cost=0.00..925.13 rows=23,913 width=199) (actual time=0.004..1.887 rows=23,896 loops=1)

138. 1.962 1.962 ↑ 1.0 23,949 1

Seq Scan on raws_86 r_134 (cost=0.00..927.98 rows=23,998 width=199) (actual time=0.003..1.962 rows=23,949 loops=1)

139. 1.893 1.893 ↑ 1.0 23,900 1

Seq Scan on raws_87 r_135 (cost=0.00..926.27 rows=23,927 width=199) (actual time=0.005..1.893 rows=23,900 loops=1)

140. 1.883 1.883 ↑ 1.0 24,029 1

Seq Scan on raws_88 r_136 (cost=0.00..929.67 rows=24,067 width=199) (actual time=0.003..1.883 rows=24,029 loops=1)

141. 1.879 1.879 ↑ 1.0 23,914 1

Seq Scan on raws_89 r_137 (cost=0.00..926.65 rows=23,965 width=199) (actual time=0.003..1.879 rows=23,914 loops=1)

142. 1.916 1.916 ↑ 1.0 24,058 1

Seq Scan on raws_8a r_138 (cost=0.00..932.24 rows=24,124 width=199) (actual time=0.003..1.916 rows=24,058 loops=1)

143. 1.908 1.908 ↑ 1.0 24,108 1

Seq Scan on raws_8b r_139 (cost=0.00..934.77 rows=24,177 width=199) (actual time=0.006..1.908 rows=24,108 loops=1)

144. 1.879 1.879 ↑ 1.0 23,769 1

Seq Scan on raws_8c r_140 (cost=0.00..921.26 rows=23,826 width=199) (actual time=0.003..1.879 rows=23,769 loops=1)

145. 2.103 2.103 ↑ 1.0 23,878 1

Seq Scan on raws_8d r_141 (cost=0.00..924.23 rows=23,923 width=198) (actual time=0.003..2.103 rows=23,878 loops=1)

146. 2.169 2.169 ↑ 1.0 24,039 1

Seq Scan on raws_8e r_142 (cost=0.00..932.06 rows=24,106 width=199) (actual time=0.003..2.169 rows=24,039 loops=1)

147. 2.001 2.001 ↑ 1.0 23,940 1

Seq Scan on raws_8f r_143 (cost=0.00..926.77 rows=23,977 width=199) (actual time=0.005..2.001 rows=23,940 loops=1)

148. 1.940 1.940 ↑ 1.0 23,767 1

Seq Scan on raws_90 r_144 (cost=0.00..921.32 rows=23,832 width=199) (actual time=0.003..1.940 rows=23,767 loops=1)

149. 1.951 1.951 ↑ 1.0 24,214 1

Seq Scan on raws_91 r_145 (cost=0.00..938.42 rows=24,242 width=199) (actual time=0.004..1.951 rows=24,214 loops=1)

150. 1.945 1.945 ↑ 1.0 24,149 1

Seq Scan on raws_92 r_146 (cost=0.00..934.77 rows=24,177 width=199) (actual time=0.003..1.945 rows=24,149 loops=1)

151. 1.928 1.928 ↑ 1.0 24,031 1

Seq Scan on raws_93 r_147 (cost=0.00..930.71 rows=24,071 width=199) (actual time=0.006..1.928 rows=24,031 loops=1)

152. 2.113 2.113 ↑ 1.0 24,315 1

Seq Scan on raws_94 r_148 (cost=0.00..941.25 rows=24,325 width=199) (actual time=0.004..2.113 rows=24,315 loops=1)

153. 1.913 1.913 ↑ 1.0 24,152 1

Seq Scan on raws_95 r_149 (cost=0.00..934.97 rows=24,197 width=198) (actual time=0.004..1.913 rows=24,152 loops=1)

154. 1.895 1.895 ↓ 1.0 24,127 1

Seq Scan on raws_96 r_150 (cost=0.00..934.20 rows=24,120 width=199) (actual time=0.003..1.895 rows=24,127 loops=1)

155. 1.906 1.906 ↑ 1.0 24,079 1

Seq Scan on raws_97 r_151 (cost=0.00..932.11 rows=24,111 width=199) (actual time=0.005..1.906 rows=24,079 loops=1)

156. 1.925 1.925 ↑ 1.0 24,102 1

Seq Scan on raws_98 r_152 (cost=0.00..933.30 rows=24,130 width=199) (actual time=0.003..1.925 rows=24,102 loops=1)

157. 2.340 2.340 ↑ 1.0 24,240 1

Seq Scan on raws_99 r_153 (cost=0.00..938.53 rows=24,253 width=199) (actual time=0.004..2.340 rows=24,240 loops=1)

158. 2.000 2.000 ↑ 1.0 24,048 1

Seq Scan on raws_9a r_154 (cost=0.00..930.81 rows=24,081 width=199) (actual time=0.003..2.000 rows=24,048 loops=1)

159. 1.921 1.921 ↓ 1.0 24,168 1

Seq Scan on raws_9b r_155 (cost=0.00..934.63 rows=24,163 width=199) (actual time=0.005..1.921 rows=24,168 loops=1)

160. 1.955 1.955 ↑ 1.0 24,069 1

Seq Scan on raws_9c r_156 (cost=0.00..932.01 rows=24,101 width=199) (actual time=0.003..1.955 rows=24,069 loops=1)

161. 2.018 2.018 ↑ 1.0 24,153 1

Seq Scan on raws_9d r_157 (cost=0.00..934.90 rows=24,190 width=199) (actual time=0.003..2.018 rows=24,153 loops=1)

162. 1.942 1.942 ↓ 1.0 23,969 1

Seq Scan on raws_9e r_158 (cost=0.00..927.60 rows=23,960 width=199) (actual time=0.003..1.942 rows=23,969 loops=1)

163. 1.963 1.963 ↑ 1.0 24,096 1

Seq Scan on raws_9f r_159 (cost=0.00..933.59 rows=24,159 width=199) (actual time=0.005..1.963 rows=24,096 loops=1)

164. 1.932 1.932 ↑ 1.0 24,019 1

Seq Scan on raws_a0 r_160 (cost=0.00..930.19 rows=24,019 width=199) (actual time=0.003..1.932 rows=24,019 loops=1)

165. 1.963 1.963 ↑ 1.0 24,121 1

Seq Scan on raws_a1 r_161 (cost=0.00..934.93 rows=24,193 width=199) (actual time=0.003..1.963 rows=24,121 loops=1)

166. 1.932 1.932 ↑ 1.0 23,835 1

Seq Scan on raws_a2 r_162 (cost=0.00..922.73 rows=23,873 width=199) (actual time=0.003..1.932 rows=23,835 loops=1)

167. 1.915 1.915 ↓ 1.0 24,031 1

Seq Scan on raws_a3 r_163 (cost=0.00..930.25 rows=24,025 width=199) (actual time=0.005..1.915 rows=24,031 loops=1)

168. 1.943 1.943 ↑ 1.0 24,187 1

Seq Scan on raws_a4 r_164 (cost=0.00..936.01 rows=24,201 width=199) (actual time=0.003..1.943 rows=24,187 loops=1)

169. 2.020 2.020 ↑ 1.0 23,811 1

Seq Scan on raws_a5 r_165 (cost=0.00..921.71 rows=23,871 width=198) (actual time=0.004..2.020 rows=23,811 loops=1)

170. 2.054 2.054 ↑ 1.0 24,159 1

Seq Scan on raws_a6 r_166 (cost=0.00..934.63 rows=24,163 width=199) (actual time=0.004..2.054 rows=24,159 loops=1)

171. 2.030 2.030 ↑ 1.0 24,123 1

Seq Scan on raws_a7 r_167 (cost=0.00..934.76 rows=24,176 width=199) (actual time=0.005..2.030 rows=24,123 loops=1)

172. 1.961 1.961 ↑ 1.0 24,113 1

Seq Scan on raws_a8 r_168 (cost=0.00..933.51 rows=24,151 width=199) (actual time=0.004..1.961 rows=24,113 loops=1)

173. 2.098 2.098 ↑ 1.0 23,967 1

Seq Scan on raws_a9 r_169 (cost=0.00..926.99 rows=23,999 width=199) (actual time=0.003..2.098 rows=23,967 loops=1)

174. 1.991 1.991 ↑ 1.0 23,944 1

Seq Scan on raws_aa r_170 (cost=0.00..926.76 rows=23,976 width=199) (actual time=0.003..1.991 rows=23,944 loops=1)

175. 2.022 2.022 ↑ 1.0 24,163 1

Seq Scan on raws_ab r_171 (cost=0.00..934.96 rows=24,196 width=199) (actual time=0.005..2.022 rows=24,163 loops=1)

176. 1.959 1.959 ↑ 1.0 23,991 1

Seq Scan on raws_ac r_172 (cost=0.00..929.42 rows=24,042 width=199) (actual time=0.004..1.959 rows=23,991 loops=1)

177. 1.990 1.990 ↑ 1.0 24,160 1

Seq Scan on raws_ad r_173 (cost=0.00..936.21 rows=24,221 width=199) (actual time=0.003..1.990 rows=24,160 loops=1)

178. 2.058 2.058 ↑ 1.0 23,921 1

Seq Scan on raws_ae r_174 (cost=0.00..926.39 rows=23,939 width=199) (actual time=0.003..2.058 rows=23,921 loops=1)

179. 1.978 1.978 ↑ 1.0 24,094 1

Seq Scan on raws_af r_175 (cost=0.00..933.67 rows=24,167 width=199) (actual time=0.004..1.978 rows=24,094 loops=1)

180. 1.995 1.995 ↑ 1.0 23,955 1

Seq Scan on raws_b0 r_176 (cost=0.00..928.07 rows=24,007 width=199) (actual time=0.003..1.995 rows=23,955 loops=1)

181. 2.017 2.017 ↑ 1.0 23,985 1

Seq Scan on raws_b1 r_177 (cost=0.00..929.31 rows=24,031 width=199) (actual time=0.004..2.017 rows=23,985 loops=1)

182. 2.046 2.046 ↑ 1.0 24,132 1

Seq Scan on raws_b2 r_178 (cost=0.00..934.50 rows=24,150 width=199) (actual time=0.005..2.046 rows=24,132 loops=1)

183. 2.008 2.008 ↑ 1.0 24,309 1

Seq Scan on raws_b3 r_179 (cost=0.00..941.42 rows=24,342 width=199) (actual time=0.004..2.008 rows=24,309 loops=1)

184. 2.038 2.038 ↑ 1.0 24,203 1

Seq Scan on raws_b4 r_180 (cost=0.00..937.42 rows=24,242 width=199) (actual time=0.003..2.038 rows=24,203 loops=1)

185. 1.980 1.980 ↑ 1.0 24,039 1

Seq Scan on raws_b5 r_181 (cost=0.00..931.46 rows=24,046 width=199) (actual time=0.003..1.980 rows=24,039 loops=1)

186. 2.055 2.055 ↓ 1.0 23,799 1

Seq Scan on raws_b6 r_182 (cost=0.00..920.98 rows=23,798 width=199) (actual time=0.006..2.055 rows=23,799 loops=1)

187. 1.963 1.963 ↑ 1.0 24,015 1

Seq Scan on raws_b7 r_183 (cost=0.00..930.52 rows=24,052 width=199) (actual time=0.004..1.963 rows=24,015 loops=1)

188. 2.001 2.001 ↑ 1.0 24,055 1

Seq Scan on raws_b8 r_184 (cost=0.00..932.10 rows=24,110 width=199) (actual time=0.003..2.001 rows=24,055 loops=1)

189. 2.046 2.046 ↑ 1.0 24,015 1

Seq Scan on raws_b9 r_185 (cost=0.00..930.32 rows=24,032 width=199) (actual time=0.004..2.046 rows=24,015 loops=1)

190. 1.961 1.961 ↑ 1.0 23,856 1

Seq Scan on raws_ba r_186 (cost=0.00..922.73 rows=23,873 width=199) (actual time=0.005..1.961 rows=23,856 loops=1)

191. 2.005 2.005 ↑ 1.0 24,038 1

Seq Scan on raws_bb r_187 (cost=0.00..930.68 rows=24,068 width=199) (actual time=0.004..2.005 rows=24,038 loops=1)

192. 1.967 1.967 ↑ 1.0 23,725 1

Seq Scan on raws_bc r_188 (cost=0.00..918.81 rows=23,781 width=199) (actual time=0.003..1.967 rows=23,725 loops=1)

193. 2.094 2.094 ↑ 1.0 24,025 1

Seq Scan on raws_bd r_189 (cost=0.00..930.53 rows=24,053 width=199) (actual time=0.004..2.094 rows=24,025 loops=1)

194. 1.952 1.952 ↓ 1.0 23,634 1

Seq Scan on raws_be r_190 (cost=0.00..914.09 rows=23,609 width=199) (actual time=0.005..1.952 rows=23,634 loops=1)

195. 2.029 2.029 ↑ 1.0 23,902 1

Seq Scan on raws_bf r_191 (cost=0.00..925.85 rows=23,985 width=198) (actual time=0.004..2.029 rows=23,902 loops=1)

196. 1.970 1.970 ↑ 1.0 23,993 1

Seq Scan on raws_c0 r_192 (cost=0.00..929.41 rows=24,041 width=198) (actual time=0.004..1.970 rows=23,993 loops=1)

197. 2.152 2.152 ↑ 1.0 23,899 1

Seq Scan on raws_c1 r_193 (cost=0.00..926.37 rows=23,937 width=199) (actual time=0.003..2.152 rows=23,899 loops=1)

198. 2.016 2.016 ↑ 1.0 23,974 1

Seq Scan on raws_c2 r_194 (cost=0.00..928.06 rows=24,006 width=199) (actual time=0.005..2.016 rows=23,974 loops=1)

199. 2.023 2.023 ↑ 1.0 24,008 1

Seq Scan on raws_c3 r_195 (cost=0.00..929.70 rows=24,070 width=199) (actual time=0.004..2.023 rows=24,008 loops=1)

200. 2.002 2.002 ↑ 1.0 24,046 1

Seq Scan on raws_c4 r_196 (cost=0.00..931.71 rows=24,071 width=199) (actual time=0.003..2.002 rows=24,046 loops=1)

201. 1.974 1.974 ↑ 1.0 23,887 1

Seq Scan on raws_c5 r_197 (cost=0.00..925.11 rows=23,911 width=199) (actual time=0.003..1.974 rows=23,887 loops=1)

202. 1.972 1.972 ↑ 1.0 24,039 1

Seq Scan on raws_c6 r_198 (cost=0.00..930.97 rows=24,097 width=199) (actual time=0.006..1.972 rows=24,039 loops=1)

203. 2.049 2.049 ↑ 1.0 24,075 1

Seq Scan on raws_c7 r_199 (cost=0.00..931.82 rows=24,082 width=199) (actual time=0.003..2.049 rows=24,075 loops=1)

204. 1.977 1.977 ↑ 1.0 23,993 1

Seq Scan on raws_c8 r_200 (cost=0.00..929.11 rows=24,011 width=199) (actual time=0.004..1.977 rows=23,993 loops=1)

205. 1.994 1.994 ↑ 1.0 24,261 1

Seq Scan on raws_c9 r_201 (cost=0.00..939.12 rows=24,312 width=199) (actual time=0.004..1.994 rows=24,261 loops=1)

206. 2.009 2.009 ↑ 1.0 23,982 1

Seq Scan on raws_ca r_202 (cost=0.00..929.25 rows=24,025 width=199) (actual time=0.005..2.009 rows=23,982 loops=1)

207. 2.042 2.042 ↑ 1.0 24,158 1

Seq Scan on raws_cb r_203 (cost=0.00..935.64 rows=24,164 width=199) (actual time=0.003..2.042 rows=24,158 loops=1)

208. 1.977 1.977 ↓ 1.0 24,250 1

Seq Scan on raws_cc r_204 (cost=0.00..938.33 rows=24,233 width=199) (actual time=0.004..1.977 rows=24,250 loops=1)

209. 2.032 2.032 ↑ 1.0 24,091 1

Seq Scan on raws_cd r_205 (cost=0.00..932.06 rows=24,106 width=199) (actual time=0.003..2.032 rows=24,091 loops=1)

210. 1.963 1.963 ↑ 1.0 23,926 1

Seq Scan on raws_ce r_206 (cost=0.00..926.35 rows=23,935 width=199) (actual time=0.006..1.963 rows=23,926 loops=1)

211. 1.916 1.916 ↓ 1.0 23,676 1

Seq Scan on raws_cf r_207 (cost=0.00..915.72 rows=23,672 width=199) (actual time=0.003..1.916 rows=23,676 loops=1)

212. 2.025 2.025 ↑ 1.0 24,046 1

Seq Scan on raws_d0 r_208 (cost=0.00..932.02 rows=24,102 width=199) (actual time=0.003..2.025 rows=24,046 loops=1)

213. 1.929 1.929 ↑ 1.0 23,922 1

Seq Scan on raws_d1 r_209 (cost=0.00..926.40 rows=23,940 width=199) (actual time=0.004..1.929 rows=23,922 loops=1)

214. 1.956 1.956 ↑ 1.0 24,090 1

Seq Scan on raws_d2 r_210 (cost=0.00..933.26 rows=24,126 width=199) (actual time=0.005..1.956 rows=24,090 loops=1)

215. 1.945 1.945 ↑ 1.0 23,869 1

Seq Scan on raws_d3 r_211 (cost=0.00..923.85 rows=23,885 width=199) (actual time=0.003..1.945 rows=23,869 loops=1)

216. 1.986 1.986 ↑ 1.0 24,150 1

Seq Scan on raws_d4 r_212 (cost=0.00..935.84 rows=24,184 width=199) (actual time=0.003..1.986 rows=24,150 loops=1)

217. 1.917 1.917 ↑ 1.0 23,994 1

Seq Scan on raws_d5 r_213 (cost=0.00..929.14 rows=24,014 width=199) (actual time=0.003..1.917 rows=23,994 loops=1)

218. 1.915 1.915 ↑ 1.0 23,900 1

Seq Scan on raws_d6 r_214 (cost=0.00..925.14 rows=23,914 width=199) (actual time=0.005..1.915 rows=23,900 loops=1)

219. 1.897 1.897 ↑ 1.0 24,064 1

Seq Scan on raws_d7 r_215 (cost=0.00..931.75 rows=24,075 width=199) (actual time=0.003..1.897 rows=24,064 loops=1)

220. 1.886 1.886 ↓ 1.0 24,010 1

Seq Scan on raws_d8 r_216 (cost=0.00..930.09 rows=24,009 width=199) (actual time=0.003..1.886 rows=24,010 loops=1)

221. 1.873 1.873 ↑ 1.0 23,860 1

Seq Scan on raws_d9 r_217 (cost=0.00..923.99 rows=23,899 width=199) (actual time=0.003..1.873 rows=23,860 loops=1)

222. 1.901 1.901 ↑ 1.0 24,151 1

Seq Scan on raws_da r_218 (cost=0.00..935.97 rows=24,197 width=199) (actual time=0.005..1.901 rows=24,151 loops=1)

223. 1.885 1.885 ↑ 1.0 23,791 1

Seq Scan on raws_db r_219 (cost=0.00..921.10 rows=23,810 width=199) (actual time=0.003..1.885 rows=23,791 loops=1)

224. 1.921 1.921 ↑ 1.0 24,382 1

Seq Scan on raws_dc r_220 (cost=0.00..944.11 rows=24,411 width=199) (actual time=0.003..1.921 rows=24,382 loops=1)

225. 1.929 1.929 ↑ 1.0 23,825 1

Seq Scan on raws_dd r_221 (cost=0.00..922.71 rows=23,871 width=199) (actual time=0.003..1.929 rows=23,825 loops=1)

226. 1.876 1.876 ↑ 1.0 23,913 1

Seq Scan on raws_de r_222 (cost=0.00..926.40 rows=23,940 width=199) (actual time=0.005..1.876 rows=23,913 loops=1)

227. 1.904 1.904 ↑ 1.0 24,130 1

Seq Scan on raws_df r_223 (cost=0.00..933.44 rows=24,144 width=199) (actual time=0.003..1.904 rows=24,130 loops=1)

228. 1.885 1.885 ↑ 1.0 23,810 1

Seq Scan on raws_e0 r_224 (cost=0.00..921.44 rows=23,844 width=199) (actual time=0.003..1.885 rows=23,810 loops=1)

229. 1.869 1.869 ↑ 1.0 24,009 1

Seq Scan on raws_e1 r_225 (cost=0.00..929.12 rows=24,012 width=199) (actual time=0.003..1.869 rows=24,009 loops=1)

230. 1.900 1.900 ↑ 1.0 24,056 1

Seq Scan on raws_e2 r_226 (cost=0.00..931.93 rows=24,093 width=199) (actual time=0.005..1.900 rows=24,056 loops=1)

231. 1.877 1.877 ↑ 1.0 23,946 1

Seq Scan on raws_e3 r_227 (cost=0.00..927.97 rows=23,997 width=199) (actual time=0.003..1.877 rows=23,946 loops=1)

232. 1.912 1.912 ↑ 1.0 23,776 1

Seq Scan on raws_e4 r_228 (cost=0.00..921.01 rows=23,801 width=199) (actual time=0.003..1.912 rows=23,776 loops=1)

233. 1.887 1.887 ↑ 1.0 23,973 1

Seq Scan on raws_e5 r_229 (cost=0.00..929.06 rows=24,006 width=199) (actual time=0.003..1.887 rows=23,973 loops=1)

234. 1.888 1.888 ↑ 1.0 23,959 1

Seq Scan on raws_e6 r_230 (cost=0.00..928.35 rows=24,035 width=199) (actual time=0.005..1.888 rows=23,959 loops=1)

235. 1.881 1.881 ↑ 1.0 23,857 1

Seq Scan on raws_e7 r_231 (cost=0.00..924.24 rows=23,924 width=198) (actual time=0.004..1.881 rows=23,857 loops=1)

236. 1.894 1.894 ↑ 1.0 23,995 1

Seq Scan on raws_e8 r_232 (cost=0.00..929.48 rows=24,048 width=199) (actual time=0.003..1.894 rows=23,995 loops=1)

237. 1.891 1.891 ↑ 1.0 24,119 1

Seq Scan on raws_e9 r_233 (cost=0.00..934.78 rows=24,178 width=199) (actual time=0.003..1.891 rows=24,119 loops=1)

238. 1.866 1.866 ↑ 1.0 23,888 1

Seq Scan on raws_ea r_234 (cost=0.00..925.26 rows=23,926 width=199) (actual time=0.005..1.866 rows=23,888 loops=1)

239. 1.893 1.893 ↑ 1.0 24,130 1

Seq Scan on raws_eb r_235 (cost=0.00..934.70 rows=24,170 width=199) (actual time=0.003..1.893 rows=24,130 loops=1)

240. 1.969 1.969 ↑ 1.0 24,276 1

Seq Scan on raws_ec r_236 (cost=0.00..939.94 rows=24,294 width=199) (actual time=0.003..1.969 rows=24,276 loops=1)

241. 1.922 1.922 ↑ 1.0 24,101 1

Seq Scan on raws_ed r_237 (cost=0.00..933.30 rows=24,130 width=199) (actual time=0.004..1.922 rows=24,101 loops=1)

242. 1.891 1.891 ↑ 1.0 23,876 1

Seq Scan on raws_ee r_238 (cost=0.00..925.21 rows=23,921 width=199) (actual time=0.005..1.891 rows=23,876 loops=1)

243. 1.925 1.925 ↑ 1.0 24,018 1

Seq Scan on raws_ef r_239 (cost=0.00..930.40 rows=24,040 width=199) (actual time=0.004..1.925 rows=24,018 loops=1)

244. 1.926 1.926 ↑ 1.0 24,240 1

Seq Scan on raws_f0 r_240 (cost=0.00..939.87 rows=24,287 width=199) (actual time=0.003..1.926 rows=24,240 loops=1)

245. 1.886 1.886 ↑ 1.0 24,070 1

Seq Scan on raws_f1 r_241 (cost=0.00..931.98 rows=24,098 width=199) (actual time=0.005..1.886 rows=24,070 loops=1)

246. 1.900 1.900 ↑ 1.0 24,157 1

Seq Scan on raws_f2 r_242 (cost=0.00..935.94 rows=24,194 width=199) (actual time=0.003..1.900 rows=24,157 loops=1)

247. 1.881 1.881 ↑ 1.0 23,903 1

Seq Scan on raws_f3 r_243 (cost=0.00..925.25 rows=23,925 width=199) (actual time=0.004..1.881 rows=23,903 loops=1)

248. 1.921 1.921 ↑ 1.0 24,048 1

Seq Scan on raws_f4 r_244 (cost=0.00..932.15 rows=24,115 width=199) (actual time=0.003..1.921 rows=24,048 loops=1)

249. 1.965 1.965 ↑ 1.0 24,100 1

Seq Scan on raws_f5 r_245 (cost=0.00..933.29 rows=24,129 width=199) (actual time=0.005..1.965 rows=24,100 loops=1)

250. 1.912 1.912 ↑ 1.0 24,022 1

Seq Scan on raws_f6 r_246 (cost=0.00..930.35 rows=24,035 width=199) (actual time=0.003..1.912 rows=24,022 loops=1)

251. 1.885 1.885 ↑ 1.0 23,692 1

Seq Scan on raws_f7 r_247 (cost=0.00..918.41 rows=23,741 width=199) (actual time=0.003..1.885 rows=23,692 loops=1)

252. 1.906 1.906 ↑ 1.0 24,002 1

Seq Scan on raws_f8 r_248 (cost=0.00..929.15 rows=24,015 width=199) (actual time=0.003..1.906 rows=24,002 loops=1)

253. 1.880 1.880 ↑ 1.0 23,873 1

Seq Scan on raws_f9 r_249 (cost=0.00..925.06 rows=23,906 width=199) (actual time=0.006..1.880 rows=23,873 loops=1)

254. 1.881 1.881 ↑ 1.0 24,006 1

Seq Scan on raws_fa r_250 (cost=0.00..929.60 rows=24,060 width=199) (actual time=0.003..1.881 rows=24,006 loops=1)

255. 1.883 1.883 ↑ 1.0 23,918 1

Seq Scan on raws_fb r_251 (cost=0.00..926.54 rows=23,954 width=199) (actual time=0.003..1.883 rows=23,918 loops=1)

256. 1.952 1.952 ↑ 1.0 24,147 1

Seq Scan on raws_fc r_252 (cost=0.00..935.87 rows=24,187 width=199) (actual time=0.003..1.952 rows=24,147 loops=1)

257. 1.854 1.854 ↓ 1.0 23,835 1

Seq Scan on raws_fd r_253 (cost=0.00..922.26 rows=23,826 width=199) (actual time=0.006..1.854 rows=23,835 loops=1)

258. 1.898 1.898 ↑ 1.0 24,197 1

Seq Scan on raws_fe r_254 (cost=0.00..937.55 rows=24,255 width=199) (actual time=0.003..1.898 rows=24,197 loops=1)

259. 1.898 1.898 ↑ 1.0 24,238 1

Seq Scan on raws_ff r_255 (cost=0.00..937.93 rows=24,293 width=198) (actual time=0.003..1.898 rows=24,238 loops=1)

260. 81.704 162.235 ↑ 1.0 940,686 1

Hash (cost=20,635.70..20,635.70 rows=941,008 width=44) (actual time=162.235..162.235 rows=940,686 loops=1)

  • Buckets: 131,072 Batches: 8 Memory Usage: 9,775kB
261. 80.531 80.531 ↑ 1.0 940,686 1

Seq Scan on fast_search_domains_b3 e (cost=0.00..20,635.70 rows=941,008 width=44) (actual time=0.008..80.531 rows=940,686 loops=1)

  • Filter: (domain = '\xb33960790a6de22ca95a61c6d1310b3487304529cb0af6f3e9b80d2e5ddf76b8'::bytea)
  • Rows Removed by Filter: 3,740
Planning time : 8.755 ms
Execution time : 3,483.953 ms