explain.depesz.com

PostgreSQL's explain analyze made readable

Result: MtEX

Settings
# exclusive inclusive rows x rows loops node
1. 0.000 0.000 ↓ 0.0

HashAggregate (cost=7,852,481.44..7,852,683.92 rows=11,570 width=80) (actual rows= loops=)

  • Group Key: (l.labels ->> 'cms_id'::text), (l.labels ->> 'patch_id'::text)
2. 0.000 0.000 ↓ 0.0

Hash Join (cost=15,769.34..7,786,407.06 rows=5,285,951 width=80) (actual rows= loops=)

  • Hash Cond: (m.labels_id = l.id)
3. 0.000 0.000 ↓ 0.0

Append (cost=0.00..6,872,758.46 rows=331,978,841 width=4) (actual rows= loops=)

4. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2357_chunk m (cost=0.00..62,156.59 rows=3,007,377 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
5. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2370_chunk m_1 (cost=0.00..61,959.25 rows=2,995,604 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
6. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2385_chunk m_2 (cost=0.00..64,644.33 rows=3,085,850 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
7. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2401_chunk m_3 (cost=0.00..74,477.44 rows=3,518,653 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
8. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2419_chunk m_4 (cost=0.00..75,496.27 rows=3,535,410 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
9. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2435_chunk m_5 (cost=0.00..84,605.27 rows=3,821,262 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
10. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2453_chunk m_6 (cost=0.00..77,224.10 rows=3,656,944 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
11. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2478_chunk m_7 (cost=0.00..75,472.51 rows=3,604,501 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
12. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2513_chunk m_8 (cost=0.00..74,362.71 rows=3,566,812 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
13. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2527_chunk m_9 (cost=0.00..76,410.66 rows=3,603,573 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
14. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2544_chunk m_10 (cost=0.00..72,842.44 rows=3,359,532 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
15. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2560_chunk m_11 (cost=0.00..77,467.27 rows=3,513,800 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
16. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2579_chunk m_12 (cost=0.00..82,260.10 rows=3,855,213 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
17. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2733_chunk m_13 (cost=0.00..83,415.06 rows=3,930,627 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
18. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2751_chunk m_14 (cost=0.00..77,954.43 rows=3,835,030 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
19. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2770_chunk m_15 (cost=0.00..74,000.18 rows=3,606,075 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
20. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2786_chunk m_16 (cost=0.00..72,893.98 rows=3,463,922 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
21. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2804_chunk m_17 (cost=0.00..72,237.02 rows=3,433,871 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
22. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2823_chunk m_18 (cost=0.00..87,855.21 rows=4,199,949 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
23. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2843_chunk m_19 (cost=0.00..83,025.31 rows=3,913,674 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
24. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2861_chunk m_20 (cost=0.00..73,075.69 rows=3,372,924 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
25. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2879_chunk m_21 (cost=0.00..62,480.41 rows=3,020,256 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
26. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2897_chunk m_22 (cost=0.00..61,133.76 rows=2,955,038 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
27. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2913_chunk m_23 (cost=0.00..64,235.81 rows=3,095,313 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
28. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2930_chunk m_24 (cost=0.00..71,047.79 rows=3,322,353 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
29. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2948_chunk m_25 (cost=0.00..81,268.16 rows=3,790,403 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
30. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2964_chunk m_26 (cost=0.00..75,866.20 rows=3,627,258 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
31. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_2982_chunk m_27 (cost=0.00..74,081.38 rows=3,720,464 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
32. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3000_chunk m_28 (cost=0.00..69,575.24 rows=3,533,414 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
33. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3018_chunk m_29 (cost=0.00..54,174.58 rows=2,722,830 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
34. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3037_chunk m_30 (cost=0.00..49,051.14 rows=2,452,398 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
35. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3056_chunk m_31 (cost=0.00..55,312.40 rows=2,612,649 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
36. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3075_chunk m_32 (cost=0.00..57,896.29 rows=2,669,567 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
37. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3092_chunk m_33 (cost=0.00..47,231.65 rows=2,244,712 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
38. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3109_chunk m_34 (cost=0.00..45,301.74 rows=2,159,772 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
39. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3128_chunk m_35 (cost=0.00..45,693.53 rows=2,194,723 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
40. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3148_chunk m_36 (cost=0.00..43,102.66 rows=2,099,006 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
41. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3165_chunk m_37 (cost=0.00..38,662.98 rows=1,854,220 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
42. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3187_chunk m_38 (cost=0.00..43,265.86 rows=2,054,483 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
43. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3206_chunk m_39 (cost=0.00..53,618.12 rows=2,545,851 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
44. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3224_chunk m_40 (cost=0.00..59,978.99 rows=2,781,112 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
45. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3243_chunk m_41 (cost=0.00..89,556.68 rows=4,032,213 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
46. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3265_chunk m_42 (cost=0.00..93,502.86 rows=4,383,459 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
47. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3285_chunk m_43 (cost=0.00..81,808.29 rows=4,039,550 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
48. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3305_chunk m_44 (cost=0.00..73,018.68 rows=3,598,422 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
49. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3325_chunk m_45 (cost=0.00..79,863.09 rows=3,884,799 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
50. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3346_chunk m_46 (cost=0.00..84,392.64 rows=4,079,953 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
51. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3365_chunk m_47 (cost=0.00..75,746.18 rows=3,602,393 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
52. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3386_chunk m_48 (cost=0.00..68,527.95 rows=3,450,656 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
53. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3408_chunk m_49 (cost=0.00..44,309.07 rows=2,219,012 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
54. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3428_chunk m_50 (cost=0.00..45,625.38 rows=2,315,442 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
55. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3448_chunk m_51 (cost=0.00..44,863.30 rows=2,235,273 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
56. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3468_chunk m_52 (cost=0.00..64,030.71 rows=2,797,276 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
57. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3489_chunk m_53 (cost=0.00..56,395.83 rows=2,642,033 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
58. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3512_chunk m_54 (cost=0.00..71,816.94 rows=3,365,876 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
59. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3533_chunk m_55 (cost=0.00..68,341.21 rows=3,237,315 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
60. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3554_chunk m_56 (cost=0.00..62,553.16 rows=2,994,220 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
61. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3576_chunk m_57 (cost=0.00..59,896.28 rows=2,863,464 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
62. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3597_chunk m_58 (cost=0.00..64,804.70 rows=3,035,055 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
63. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3620_chunk m_59 (cost=0.00..67,741.55 rows=3,198,486 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
64. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3641_chunk m_60 (cost=0.00..81,260.65 rows=3,577,368 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
65. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3663_chunk m_61 (cost=0.00..68,930.24 rows=3,363,947 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
66. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3685_chunk m_62 (cost=0.00..61,964.51 rows=3,049,277 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
67. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3707_chunk m_63 (cost=0.00..62,287.03 rows=3,170,498 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
68. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3729_chunk m_64 (cost=0.00..59,843.38 rows=3,094,795 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
69. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3750_chunk m_65 (cost=0.00..66,045.76 rows=3,298,164 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
70. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3771_chunk m_66 (cost=0.00..77,902.44 rows=3,806,962 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
71. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3792_chunk m_67 (cost=0.00..79,814.09 rows=3,980,717 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
72. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3817_chunk m_68 (cost=0.00..82,802.40 rows=4,119,997 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
73. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3838_chunk m_69 (cost=0.00..74,728.48 rows=3,589,847 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
74. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3850_chunk m_70 (cost=0.00..75,811.48 rows=3,519,642 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
75. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3882_chunk m_71 (cost=0.00..60,132.91 rows=2,976,072 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
76. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3903_chunk m_72 (cost=0.00..69,473.39 rows=3,147,245 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
77. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3921_chunk m_73 (cost=0.00..89,510.99 rows=3,508,479 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
78. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3929_chunk m_74 (cost=0.00..79,366.51 rows=3,776,961 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
79. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3965_chunk m_75 (cost=0.00..91,199.02 rows=4,389,894 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
80. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_3986_chunk m_76 (cost=0.00..104,631.91 rows=5,131,223 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
81. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4005_chunk m_77 (cost=0.00..87,409.79 rows=4,408,439 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
82. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4025_chunk m_78 (cost=0.00..60,533.60 rows=3,059,055 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
83. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4044_chunk m_79 (cost=0.00..71,336.34 rows=3,595,704 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
84. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4063_chunk m_80 (cost=0.00..89,340.01 rows=4,273,867 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
85. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4085_chunk m_81 (cost=0.00..79,156.50 rows=3,995,880 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
86. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4104_chunk m_82 (cost=0.00..79,162.51 rows=3,989,428 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
87. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4123_chunk m_83 (cost=0.00..79,331.77 rows=4,014,430 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
88. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4144_chunk m_84 (cost=0.00..83,584.43 rows=4,248,599 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
89. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4163_chunk m_85 (cost=0.00..84,567.86 rows=4,308,285 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
90. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4183_chunk m_86 (cost=0.00..87,058.51 rows=4,425,295 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
91. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4202_chunk m_87 (cost=0.00..89,636.60 rows=4,598,656 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
92. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4220_chunk m_88 (cost=0.00..90,599.40 rows=4,664,023 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
93. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4238_chunk m_89 (cost=0.00..63,026.50 rows=3,189,699 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
94. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4256_chunk m_90 (cost=0.00..58,873.93 rows=2,973,278 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
95. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4275_chunk m_91 (cost=0.00..58,254.99 rows=2,955,951 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
96. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4296_chunk m_92 (cost=0.00..60,364.95 rows=3,055,945 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
97. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4315_chunk m_93 (cost=0.00..64,482.15 rows=3,140,206 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
98. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4335_chunk m_94 (cost=0.00..66,787.88 rows=3,289,958 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
99. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4356_chunk m_95 (cost=0.00..65,574.54 rows=3,311,119 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
100. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4382_chunk m_96 (cost=0.00..67,834.43 rows=3,387,743 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
101. 0.000 0.000 ↓ 0.0

Seq Scan on _hyper_14_4410_chunk m_97 (cost=0.00..66,527.64 rows=3,280,871 width=4) (actual rows= loops=)

  • Filter: (value > '0'::double precision)
102. 0.000 0.000 ↓ 0.0

Hash (cost=15,623.62..15,623.62 rows=11,658 width=236) (actual rows= loops=)

103. 0.000 0.000 ↓ 0.0

Bitmap Heap Scan on metrics_labels l (cost=5,155.69..15,623.62 rows=11,658 width=236) (actual rows= loops=)

  • Recheck Cond: (((metric_name = ANY ('{patching_state,version_id}'::text[])) AND (patch_id_end_time >= (now() - '1 day'::interval)) AND (patch_id_end_time <= now())) OR ((metric_name = ANY ('{patching_state,version_id}'::text[])) AND (end_time >= (now() - '7 days'::interval)) AND (end_time <= now())))
  • Filter: ((metric_name = ANY ('{patching_state,version_id}'::text[])) AND (((patch_id_end_time >= (now() - '1 day'::interval)) AND (patch_id_end_time <= now())) OR ((end_time >= (now() - '7 days'::interval)) AND (end_time <= now()))))
104. 0.000 0.000 ↓ 0.0

BitmapOr (cost=5,155.69..5,155.69 rows=11,782 width=0) (actual rows= loops=)

105. 0.000 0.000 ↓ 0.0

Bitmap Index Scan on metrics_labels_name_end_times_index (cost=0.00..111.86 rows=5,713 width=0) (actual rows= loops=)

  • Index Cond: ((metric_name = ANY ('{patching_state,version_id}'::text[])) AND (patch_id_end_time >= (now() - '1 day'::interval)) AND (patch_id_end_time <= now()))
106. 0.000 0.000 ↓ 0.0

Bitmap Index Scan on metrics_labels_name_end_times_index (cost=0.00..5,038.01 rows=6,069 width=0) (actual rows= loops=)

  • Index Cond: ((metric_name = ANY ('{patching_state,version_id}'::text[])) AND (end_time >= (now() - '7 days'::interval)) AND (end_time <= now()))