explain.depesz.com

PostgreSQL's explain analyze made readable

Result: U9v4

Settings
# exclusive inclusive rows x rows loops node
1. 47,508.472 469,954.499 ↑ 5.1 8,453,415 1

Hash Left Join (cost=53,368,078.42..70,318,835.17 rows=43,086,771 width=634) (actual time=408,305.079..469,954.499 rows=8,453,415 loops=1)

  • Hash Cond: (bs.source_spot_id = inv.usn)
2. 11,916.617 419,344.625 ↑ 5.1 8,453,415 1

Hash Right Join (cost=52,984,955.11..55,608,788.63 rows=43,086,771 width=443) (actual time=405,203.058..419,344.625 rows=8,453,415 loops=1)

  • Hash Cond: (asdhh.usn = bs.source_spot_id)
3. 2,295.473 2,295.473 ↓ 19.4 638,424 1

Seq Scan on aired_spot_delivery asdhh (cost=0.00..179,527.04 rows=32,843 width=12) (actual time=0.163..2,295.473 rows=638,424 loops=1)

  • Filter: (upper((demo_cd)::text) = 'HH'::text)
  • Rows Removed by Filter: 5930084
4. 12,997.652 405,132.535 ↑ 5.1 8,453,415 1

Hash (cost=50,005,908.48..50,005,908.48 rows=43,086,771 width=435) (actual time=405,132.535..405,132.535 rows=8,453,415 loops=1)

  • Buckets: 16384 Batches: 8192 Memory Usage: 536kB
5. 3,499.625 392,134.883 ↑ 5.1 8,453,415 1

Hash Left Join (cost=14,390,317.74..50,005,908.48 rows=43,086,771 width=435) (actual time=147,451.272..392,134.883 rows=8,453,415 loops=1)

  • Hash Cond: (bs.source_spot_id = ssi.admiral_spot_id)
6. 4,497.525 388,634.633 ↑ 5.1 8,453,415 1

Hash Left Join (cost=14,390,248.50..49,844,149.95 rows=43,086,771 width=423) (actual time=147,450.623..388,634.633 rows=8,453,415 loops=1)

  • Hash Cond: ((CASE WHEN ((bs.audience_cd)::text = 'NG'::text) THEN 'No Audience Name'::character varying ELSE bs.audience_cd END)::text = (dmda.audience)::text)
7. 30,780.413 384,137.039 ↑ 5.1 8,453,415 1

Hash Left Join (cost=14,390,241.68..49,197,841.57 rows=43,086,771 width=419) (actual time=147,450.535..384,137.039 rows=8,453,415 loops=1)

  • Hash Cond: (bs.source_spot_id = sta.source_spot_id)
8. 9,354.811 350,750.774 ↑ 5.1 8,453,415 1

Hash Left Join (cost=14,100,090.69..43,349,735.23 rows=43,086,771 width=406) (actual time=144,802.856..350,750.774 rows=8,453,415 loops=1)

  • Hash Cond: (bs.parent_order_id = prnt.order_id)
9. 9,098.379 341,344.008 ↑ 5.1 8,453,415 1

Nested Loop Left Join (cost=14,093,971.15..38,290,281.84 rows=43,086,771 width=398) (actual time=144,750.314..341,344.008 rows=8,453,415 loops=1)

10. 3,984.122 306,885.384 ↑ 5.1 8,453,415 1

Hash Left Join (cost=14,093,970.73..18,368,935.07 rows=43,011,662 width=404) (actual time=144,750.280..306,885.384 rows=8,453,415 loops=1)

  • Hash Cond: (bs.secondary_product_conflict_id = dmpc.product_conflict_id)
11. 3,765.337 302,901.151 ↑ 5.1 8,453,415 1

Hash Left Join (cost=14,093,956.34..18,254,867.92 rows=43,011,662 width=404) (actual time=144,750.156..302,901.151 rows=8,453,415 loops=1)

  • Hash Cond: (bs.team_id = dmtm.team_id)
12. 3,878.803 299,135.732 ↑ 5.1 8,453,415 1

Hash Left Join (cost=14,093,946.38..18,140,147.21 rows=43,011,662 width=404) (actual time=144,750.060..299,135.732 rows=8,453,415 loops=1)

  • Hash Cond: (bs.asr_user_id = dmasr.user_id)
13. 4,012.064 295,255.234 ↑ 5.1 8,453,415 1

Hash Left Join (cost=14,093,654.11..18,026,879.11 rows=43,011,662 width=404) (actual time=144,748.313..295,255.234 rows=8,453,415 loops=1)

  • Hash Cond: (bs.ae_user_id = dmae.user_id)
14. 3,962.105 291,241.270 ↑ 5.1 8,453,415 1

Hash Left Join (cost=14,093,361.84..17,913,611.00 rows=43,011,662 width=404) (actual time=144,746.374..291,241.270 rows=8,453,415 loops=1)

  • Hash Cond: (bs.order_revenue_type_id = dmrt.revenue_type_id)
15. 3,944.843 287,279.155 ↑ 5.1 8,453,415 1

Hash Left Join (cost=14,093,346.44..17,798,696.82 rows=43,011,662 width=404) (actual time=144,746.352..287,279.155 rows=8,453,415 loops=1)

  • Hash Cond: (bs.spot_revenue_type_id = dmspt.spot_revenue_type_id)
16. 138,674.109 283,334.302 ↑ 5.1 8,453,415 1

Hash Right Join (cost=14,093,331.04..17,683,782.65 rows=43,011,662 width=404) (actual time=144,746.322..283,334.302 rows=8,453,415 loops=1)

  • Hash Cond: (stsp1.selling_title_sk = dmst.selling_title_sk)
  • Join Filter: ((bs.broadcast_week_date >= sp.start_date) AND (bs.broadcast_week_date <= sp.end_date))
  • Rows Removed by Join Filter: 221132273
17. 21.376 28.536 ↑ 1.0 80,743 1

Hash Join (cost=5.04..1,704.07 rows=80,743 width=18) (actual time=0.201..28.536 rows=80,743 loops=1)

  • Hash Cond: (stsp1.selling_period_sk = sp.selling_period_sk)
18. 7.110 7.110 ↑ 1.0 80,743 1

Seq Scan on dim_selling_title_selling_period stsp1 (cost=0.00..1,480.43 rows=80,743 width=14) (actual time=0.128..7.110 rows=80,743 loops=1)

19. 0.027 0.050 ↑ 1.0 135 1

Hash (cost=3.35..3.35 rows=135 width=12) (actual time=0.050..0.050 rows=135 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 14kB
20. 0.023 0.023 ↑ 1.0 135 1

Seq Scan on dim_selling_period sp (cost=0.00..3.35 rows=135 width=12) (actual time=0.005..0.023 rows=135 loops=1)

21. 16,191.472 144,631.657 ↑ 5.1 8,453,415 1

Hash (cost=11,287,486.23..11,287,486.23 rows=43,011,662 width=402) (actual time=144,631.657..144,631.657 rows=8,453,415 loops=1)

  • Buckets: 16384 (originally 16384) Batches: 16384 (originally 8192) Memory Usage: 130463kB
22. 5,044.632 128,440.185 ↑ 5.1 8,453,415 1

Hash Left Join (cost=346,483.89..11,287,486.23 rows=43,011,662 width=402) (actual time=2,936.136..128,440.185 rows=8,453,415 loops=1)

  • Hash Cond: (bs.selling_title_id = dmst.selling_title_id)
23. 8,939.513 123,383.980 ↑ 5.1 8,453,415 1

Hash Left Join (cost=344,967.47..11,173,053.02 rows=43,011,662 width=402) (actual time=2,924.303..123,383.980 rows=8,453,415 loops=1)

  • Hash Cond: (lower(btrim(replace((bs.division_cd)::text, ' '::text, ''::text))) = (dmdv.division)::text)
24. 4,523.336 114,444.458 ↑ 2.2 8,453,415 1

Hash Left Join (cost=344,946.90..6,395,992.51 rows=18,302,835 width=402) (actual time=2,924.224..114,444.458 rows=8,453,415 loops=1)

  • Hash Cond: ((bs.spot_status_cd)::text = (dsst.spot_status_cd)::text)
25. 4,320.030 109,921.111 ↑ 2.2 8,453,415 1

Hash Left Join (cost=344,945.58..6,144,382.13 rows=18,302,835 width=398) (actual time=2,924.199..109,921.111 rows=8,453,415 loops=1)

  • Hash Cond: (bs.rate_card_type_id = dmrct.rate_card_type_id)
26. 3,729.600 105,601.070 ↑ 2.2 8,453,415 1

Hash Left Join (cost=344,928.16..6,095,702.73 rows=18,302,835 width=356) (actual time=2,924.175..105,601.070 rows=8,453,415 loops=1)

  • Hash Cond: (bs.property_id = dmdp.property_id)
27. 4,615.106 101,871.456 ↑ 2.2 8,453,415 1

Hash Left Join (cost=344,908.71..6,047,153.68 rows=18,302,835 width=356) (actual time=2,924.148..101,871.456 rows=8,453,415 loops=1)

  • Hash Cond: ((bs.network_cd)::text = (dmdn.network_cd)::text)
28. 11,353.022 97,256.234 ↑ 2.2 8,453,415 1

Hash Left Join (cost=344,896.06..5,795,477.05 rows=18,302,835 width=352) (actual time=2,924.018..97,256.234 rows=8,453,415 loops=1)

  • Hash Cond: (bs.brand_id = dmbd.brand_id)
29. 4,711.845 85,871.720 ↑ 2.2 8,453,415 1

Hash Left Join (cost=340,747.33..4,062,698.57 rows=18,302,835 width=352) (actual time=2,891.922..85,871.720 rows=8,453,415 loops=1)

  • Hash Cond: ((bs.lh_deal_cd)::text = (dmdd.source_deal_id)::text)
30. 4,184.753 81,151.352 ↑ 2.2 8,453,415 1

Hash Left Join (cost=339,200.41..4,013,099.15 rows=18,302,835 width=357) (actual time=2,883.218..81,151.352 rows=8,453,415 loops=1)

  • Hash Cond: (bs.order_type_id = dot.order_type_id)
31. 17,767.135 76,966.592 ↓ 1.2 8,453,415 1

Hash Left Join (cost=339,178.48..3,355,068.67 rows=6,908,803 width=351) (actual time=2,883.087..76,966.592 rows=8,453,415 loops=1)

  • Hash Cond: (bs.order_id = ord_prp.order_id)
32. 3,627.491 59,133.004 ↓ 1.2 8,448,728 1

Hash Left Join (cost=332,995.96..2,541,300.94 rows=6,870,239 width=337) (actual time=2,816.270..59,133.004 rows=8,448,728 loops=1)

  • Hash Cond: (bs.agency_id = dmag.agency_id)
33. 3,702.819 55,499.628 ↓ 1.2 8,448,728 1

Hash Left Join (cost=332,398.14..2,522,664.38 rows=6,870,239 width=337) (actual time=2,810.188..55,499.628 rows=8,448,728 loops=1)

  • Hash Cond: (bs.advertiser_id = dmad.advertiser_id)
34. 22,132.779 51,788.909 ↓ 1.2 8,448,728 1

Hash Left Join (cost=331,422.79..2,503,651.99 rows=6,870,239 width=337) (actual time=2,802.147..51,788.909 rows=8,448,728 loops=1)

  • Hash Cond: (bs.source_spot_id = sds.source_spot_id)
35. 3,282.176 26,909.146 ↓ 1.2 8,448,728 1

Hash Left Join (cost=7,855.73..1,395,057.43 rows=6,870,239 width=325) (actual time=54.514..26,909.146 rows=8,448,728 loops=1)

  • Hash Cond: (bs.order_status_id = dos.order_status_id)
36. 14,951.038 23,626.962 ↓ 1.2 8,448,728 1

Hash Left Join (cost=7,819.62..1,300,555.55 rows=6,870,239 width=325) (actual time=54.487..23,626.962 rows=8,448,728 loops=1)

  • Hash Cond: (bs.order_id = dmo.source_order_id)
37. 8,622.166 8,622.166 ↓ 1.2 8,448,728 1

Seq Scan on blended_spots bs (cost=0.00..620,401.14 rows=6,870,239 width=317) (actual time=0.147..8,622.166 rows=8,448,728 loops=1)

  • Filter: ((source_spot_id_desc = ANY ('{"usn - aired spot","usn - booked spot"}'::text[])) OR (additional_admiral_spot = 1) OR (is_manual_adjustment = 1))
38. 29.846 53.758 ↑ 1.0 179,050 1

Hash (cost=4,706.50..4,706.50 rows=179,050 width=16) (actual time=53.758..53.758 rows=179,050 loops=1)

  • Buckets: 131072 Batches: 4 Memory Usage: 3139kB
39. 23.912 23.912 ↑ 1.0 179,050 1

Seq Scan on dim_order dmo (cost=0.00..4,706.50 rows=179,050 width=16) (actual time=0.102..23.912 rows=179,050 loops=1)

40. 0.004 0.008 ↑ 165.7 7 1

Hash (cost=21.60..21.60 rows=1,160 width=8) (actual time=0.008..0.008 rows=7 loops=1)

  • Buckets: 2048 Batches: 1 Memory Usage: 17kB
41. 0.004 0.004 ↑ 165.7 7 1

Seq Scan on dim_order_status dos (cost=0.00..21.60 rows=1,160 width=8) (actual time=0.003..0.004 rows=7 loops=1)

42. 1,522.703 2,746.984 ↑ 1.0 8,354,625 1

Hash (cost=178,339.25..178,339.25 rows=8,354,625 width=16) (actual time=2,746.984..2,746.984 rows=8,354,625 loops=1)

  • Buckets: 131072 Batches: 256 Memory Usage: 2674kB
43. 1,224.281 1,224.281 ↑ 1.0 8,354,625 1

Seq Scan on stage_deal_to_spot sds (cost=0.00..178,339.25 rows=8,354,625 width=16) (actual time=0.132..1,224.281 rows=8,354,625 loops=1)

44. 4.230 7.900 ↑ 1.0 28,771 1

Hash (cost=615.71..615.71 rows=28,771 width=8) (actual time=7.899..7.900 rows=28,771 loops=1)

  • Buckets: 32768 Batches: 1 Memory Usage: 1380kB
45. 3.670 3.670 ↑ 1.0 28,771 1

Seq Scan on dim_advertiser dmad (cost=0.00..615.71 rows=28,771 width=8) (actual time=0.126..3.670 rows=28,771 loops=1)

46. 3.143 5.885 ↑ 1.0 17,548 1

Hash (cost=378.48..378.48 rows=17,548 width=8) (actual time=5.885..5.885 rows=17,548 loops=1)

  • Buckets: 32768 Batches: 1 Memory Usage: 942kB
47. 2.742 2.742 ↑ 1.0 17,548 1

Seq Scan on dim_agency dmag (cost=0.00..378.48 rows=17,548 width=8) (actual time=0.005..2.742 rows=17,548 loops=1)

48. 39.744 66.453 ↑ 1.0 173,712 1

Hash (cost=2,993.12..2,993.12 rows=173,712 width=22) (actual time=66.453..66.453 rows=173,712 loops=1)

  • Buckets: 65536 Batches: 4 Memory Usage: 2843kB
49. 26.709 26.709 ↑ 1.0 173,712 1

Seq Scan on assign_order_properties ord_prp (cost=0.00..2,993.12 rows=173,712 width=22) (actual time=0.233..26.709 rows=173,712 loops=1)

50. 0.004 0.007 ↑ 132.5 4 1

Hash (cost=15.30..15.30 rows=530 width=12) (actual time=0.007..0.007 rows=4 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
51. 0.003 0.003 ↑ 132.5 4 1

Seq Scan on dim_order_type dot (cost=0.00..15.30 rows=530 width=12) (actual time=0.003..0.003 rows=4 loops=1)

52. 4.028 8.523 ↑ 1.0 20,041 1

Hash (cost=1,296.41..1,296.41 rows=20,041 width=19) (actual time=8.523..8.523 rows=20,041 loops=1)

  • Buckets: 32768 Batches: 1 Memory Usage: 1274kB
53. 4.495 4.495 ↑ 1.0 20,041 1

Seq Scan on dim_deal dmdd (cost=0.00..1,296.41 rows=20,041 width=19) (actual time=0.110..4.495 rows=20,041 loops=1)

54. 17.624 31.492 ↑ 1.0 112,299 1

Hash (cost=2,305.99..2,305.99 rows=112,299 width=8) (actual time=31.492..31.492 rows=112,299 loops=1)

  • Buckets: 131072 Batches: 2 Memory Usage: 3224kB
55. 13.868 13.868 ↑ 1.0 112,299 1

Seq Scan on dim_brand dmbd (cost=0.00..2,305.99 rows=112,299 width=8) (actual time=0.159..13.868 rows=112,299 loops=1)

56. 0.066 0.116 ↑ 1.0 340 1

Hash (cost=8.40..8.40 rows=340 width=14) (actual time=0.116..0.116 rows=340 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 24kB
57. 0.050 0.050 ↑ 1.0 340 1

Seq Scan on dim_network dmdn (cost=0.00..8.40 rows=340 width=14) (actual time=0.005..0.050 rows=340 loops=1)

58. 0.008 0.014 ↑ 12.0 35 1

Hash (cost=14.20..14.20 rows=420 width=8) (actual time=0.014..0.014 rows=35 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 10kB
59. 0.006 0.006 ↑ 12.0 35 1

Seq Scan on dim_property dmdp (cost=0.00..14.20 rows=420 width=8) (actual time=0.003..0.006 rows=35 loops=1)

60. 0.006 0.011 ↑ 16.5 20 1

Hash (cost=13.30..13.30 rows=330 width=46) (actual time=0.011..0.011 rows=20 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
61. 0.005 0.005 ↑ 16.5 20 1

Seq Scan on dim_rate_card_type dmrct (cost=0.00..13.30 rows=330 width=46) (actual time=0.003..0.005 rows=20 loops=1)

62. 0.007 0.011 ↑ 1.0 14 1

Hash (cost=1.14..1.14 rows=14 width=36) (actual time=0.011..0.011 rows=14 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
63. 0.004 0.004 ↑ 1.0 14 1

Seq Scan on dim_spot_status dsst (cost=0.00..1.14 rows=14 width=36) (actual time=0.002..0.004 rows=14 loops=1)

64. 0.005 0.009 ↑ 39.2 12 1

Hash (cost=14.70..14.70 rows=470 width=62) (actual time=0.008..0.009 rows=12 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
65. 0.004 0.004 ↑ 39.2 12 1

Seq Scan on dim_division dmdv (cost=0.00..14.70 rows=470 width=62) (actual time=0.002..0.004 rows=12 loops=1)

66. 6.240 11.573 ↑ 1.0 42,774 1

Hash (cost=981.74..981.74 rows=42,774 width=8) (actual time=11.573..11.573 rows=42,774 loops=1)

  • Buckets: 65536 Batches: 1 Memory Usage: 2183kB
67. 5.333 5.333 ↑ 1.0 42,774 1

Seq Scan on dim_selling_title dmst (cost=0.00..981.74 rows=42,774 width=8) (actual time=0.107..5.333 rows=42,774 loops=1)

68. 0.005 0.010 ↑ 48.0 5 1

Hash (cost=12.40..12.40 rows=240 width=8) (actual time=0.010..0.010 rows=5 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
69. 0.005 0.005 ↑ 48.0 5 1

Seq Scan on dim_spot_revenue_type dmspt (cost=0.00..12.40 rows=240 width=8) (actual time=0.004..0.005 rows=5 loops=1)

70. 0.005 0.010 ↑ 10.0 24 1

Hash (cost=12.40..12.40 rows=240 width=8) (actual time=0.010..0.010 rows=24 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
71. 0.005 0.005 ↑ 10.0 24 1

Seq Scan on dim_revenue_type dmrt (cost=0.00..12.40 rows=240 width=8) (actual time=0.003..0.005 rows=24 loops=1)

72. 0.949 1.900 ↑ 1.0 6,812 1

Hash (cost=207.12..207.12 rows=6,812 width=8) (actual time=1.900..1.900 rows=6,812 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 331kB
73. 0.951 0.951 ↑ 1.0 6,812 1

Seq Scan on dim_user dmae (cost=0.00..207.12 rows=6,812 width=8) (actual time=0.004..0.951 rows=6,812 loops=1)

74. 0.940 1.695 ↑ 1.0 6,812 1

Hash (cost=207.12..207.12 rows=6,812 width=8) (actual time=1.695..1.695 rows=6,812 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 331kB
75. 0.755 0.755 ↑ 1.0 6,812 1

Seq Scan on dim_user dmasr (cost=0.00..207.12 rows=6,812 width=8) (actual time=0.002..0.755 rows=6,812 loops=1)

76. 0.047 0.082 ↑ 1.0 265 1

Hash (cost=6.65..6.65 rows=265 width=8) (actual time=0.082..0.082 rows=265 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 19kB
77. 0.035 0.035 ↑ 1.0 265 1

Seq Scan on dim_team dmtm (cost=0.00..6.65 rows=265 width=8) (actual time=0.004..0.035 rows=265 loops=1)

78. 0.058 0.111 ↑ 1.0 417 1

Hash (cost=9.17..9.17 rows=417 width=8) (actual time=0.111..0.111 rows=417 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 25kB
79. 0.053 0.053 ↑ 1.0 417 1

Seq Scan on dim_product_conflict dmpc (cost=0.00..9.17 rows=417 width=8) (actual time=0.004..0.053 rows=417 loops=1)

80. 25,360.245 25,360.245 ↑ 1.0 1 8,453,415

Index Scan using idx_blnd_genesis_join on genesis_avails ga (cost=0.42..0.45 rows=1 width=15) (actual time=0.003..0.003 rows=1 loops=8,453,415)

  • Index Cond: ((bs.rate_card_type_id = rate_card_type_id) AND (bs.broadcast_week_date_sk = broadcast_date_sk) AND ((bs.network_cd)::text = (network_cd)::text))
81. 28.756 51.955 ↑ 1.0 176,913 1

Hash (cost=3,044.13..3,044.13 rows=176,913 width=12) (actual time=51.955..51.955 rows=176,913 loops=1)

  • Buckets: 131072 Batches: 4 Memory Usage: 2941kB
82. 23.199 23.199 ↑ 1.0 176,913 1

Seq Scan on order_info prnt (cost=0.00..3,044.13 rows=176,913 width=12) (actual time=0.132..23.199 rows=176,913 loops=1)

83. 1,579.244 2,605.852 ↑ 1.0 8,354,625 1

Hash (cost=136,762.55..136,762.55 rows=8,354,755 width=17) (actual time=2,605.852..2,605.852 rows=8,354,625 loops=1)

  • Buckets: 65536 Batches: 256 Memory Usage: 2168kB
84. 1,026.608 1,026.608 ↑ 1.0 8,354,625 1

Seq Scan on spot_tracking_audience sta (cost=0.00..136,762.55 rows=8,354,755 width=17) (actual time=0.109..1,026.608 rows=8,354,625 loops=1)

85. 0.038 0.069 ↑ 1.0 214 1

Hash (cost=4.14..4.14 rows=214 width=10) (actual time=0.069..0.069 rows=214 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 17kB
86. 0.031 0.031 ↑ 1.0 214 1

Seq Scan on dim_audience dmda (cost=0.00..4.14 rows=214 width=10) (actual time=0.005..0.031 rows=214 loops=1)

87. 0.341 0.625 ↑ 1.0 2,233 1

Hash (cost=41.33..41.33 rows=2,233 width=16) (actual time=0.625..0.625 rows=2,233 loops=1)

  • Buckets: 4096 Batches: 1 Memory Usage: 128kB
88. 0.284 0.284 ↑ 1.0 2,233 1

Seq Scan on stage_spot_isci ssi (cost=0.00..41.33 rows=2,233 width=16) (actual time=0.004..0.284 rows=2,233 loops=1)

89. 1,866.997 3,101.402 ↓ 1.0 11,348,823 1

Hash (cost=196,934.36..196,934.36 rows=11,348,636 width=8) (actual time=3,101.402..3,101.402 rows=11,348,823 loops=1)

  • Buckets: 131072 Batches: 256 Memory Usage: 2760kB
90. 1,234.405 1,234.405 ↓ 1.0 11,348,823 1

Seq Scan on invoice_data inv (cost=0.00..196,934.36 rows=11,348,636 width=8) (actual time=0.119..1,234.405 rows=11,348,823 loops=1)

Planning time : 19.231 ms
Execution time : 512,196.773 ms