explain.depesz.com

PostgreSQL's explain analyze made readable

Result: D7Rr

Settings
# exclusive inclusive rows x rows loops node
1. 0.161 119,534.195 ↑ 1.0 50 1

Limit (cost=1,739,095.14..1,739,095.26 rows=50 width=1,680) (actual time=119,533.966..119,534.195 rows=50 loops=1)

2.          

CTE infra_col_data

3. 230.212 3,318.461 ↓ 6.2 82,454 1

Unique (cost=28,049.08..28,115.42 rows=13,267 width=174) (actual time=2,919.938..3,318.461 rows=82,454 loops=1)

4. 338.137 3,088.249 ↓ 6.4 84,268 1

Sort (cost=28,049.08..28,082.25 rows=13,267 width=174) (actual time=2,919.935..3,088.249 rows=84,268 loops=1)

  • Sort Key: po_infra_instan.id_infra_instan
  • Sort Method: external merge Disk: 11520kB
5. 247.742 2,750.112 ↓ 6.4 84,268 1

Hash Join (cost=10,514.34..27,140.59 rows=13,267 width=174) (actual time=1,479.725..2,750.112 rows=84,268 loops=1)

  • Hash Cond: (po_infra_instan.id_infra_instan = po_proj_sub_infra.id_infra_instan)
6. 376.986 1,132.643 ↓ 1.5 84,771 1

Hash Join (cost=20.84..15,583.75 rows=57,272 width=162) (actual time=99.527..1,132.643 rows=84,771 loops=1)

  • Hash Cond: (po_infra_instan.id_connector_details = po_connector_details.id_connector_details)
7. 675.518 675.518 ↑ 1.0 274,442 1

Seq Scan on po_infra_instan (cost=0.00..13,960.92 rows=274,472 width=162) (actual time=19.316..675.518 rows=274,442 loops=1)

  • Filter: (NOT bl_marked_for_deletion)
  • Rows Removed by Filter: 233
8. 0.082 80.139 ↑ 1.0 53 1

Hash (cost=20.18..20.18 rows=53 width=4) (actual time=80.137..80.139 rows=53 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 10kB
9. 80.057 80.057 ↑ 1.0 53 1

Seq Scan on po_connector_details (cost=0.00..20.18 rows=53 width=4) (actual time=37.295..80.057 rows=53 loops=1)

  • Filter: (id_enterprise = 83)
  • Rows Removed by Filter: 202
10. 134.391 1,369.727 ↓ 1.3 84,697 1

Hash (cost=9,698.11..9,698.11 rows=63,631 width=16) (actual time=1,369.726..1,369.727 rows=84,697 loops=1)

  • Buckets: 131072 (originally 65536) Batches: 2 (originally 1) Memory Usage: 3073kB
11. 383.127 1,235.336 ↓ 1.3 84,697 1

Hash Join (cost=3,538.13..9,698.11 rows=63,631 width=16) (actual time=503.042..1,235.336 rows=84,697 loops=1)

  • Hash Cond: (po_proj_sub_infra.id_project_sub = po_project_sub.id_project_sub)
12. 386.009 386.009 ↓ 1.0 274,533 1

Seq Scan on po_proj_sub_infra (cost=0.00..4,494.22 rows=274,522 width=8) (actual time=36.407..386.009 rows=274,533 loops=1)

13. 10.791 466.200 ↑ 2.1 9,532 1

Hash (cost=3,291.11..3,291.11 rows=19,762 width=12) (actual time=466.198..466.200 rows=9,532 loops=1)

  • Buckets: 32768 Batches: 1 Memory Usage: 666kB
14. 98.316 455.409 ↑ 2.1 9,532 1

Hash Join (cost=989.16..3,291.11 rows=19,762 width=12) (actual time=229.658..455.409 rows=9,532 loops=1)

  • Hash Cond: (po_project_sub.id_project = po_project.id_project)
15. 169.357 169.357 ↓ 1.0 85,261 1

Seq Scan on po_project_sub (cost=0.00..1,784.60 rows=85,260 width=8) (actual time=41.834..169.357 rows=85,261 loops=1)

16. 14.142 187.736 ↓ 1.8 12,498 1

Hash (cost=904.15..904.15 rows=6,801 width=8) (actual time=187.735..187.736 rows=12,498 loops=1)

  • Buckets: 16384 (originally 8192) Batches: 1 (originally 1) Memory Usage: 617kB
17. 43.430 173.594 ↓ 1.8 12,498 1

Hash Join (cost=27.69..904.15 rows=6,801 width=8) (actual time=38.731..173.594 rows=12,498 loops=1)

  • Hash Cond: (po_project.id_organization = org.id_organization)
18. 129.766 129.766 ↓ 1.0 29,343 1

Seq Scan on po_project (cost=0.00..698.42 rows=29,342 width=8) (actual time=37.636..129.766 rows=29,343 loops=1)

19. 0.109 0.398 ↑ 1.0 70 1

Hash (cost=26.81..26.81 rows=70 width=4) (actual time=0.396..0.398 rows=70 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 11kB
20. 0.289 0.289 ↑ 1.0 70 1

Index Only Scan using po_organization_pkey on po_organization org (cost=0.15..26.81 rows=70 width=4) (actual time=0.084..0.289 rows=70 loops=1)

  • Index Cond: (id_organization = ANY ('{126,133,190,191,192,193,194,195,196,197,198,199,203,204,211,272,287,288,289,290,291,292,293,331,333,337,338,339,340,341,342,347,349,350,351,352,353,354,355,356,361,362,363,366,367,368,369,373,374,375,376,377,378,379,380,381,382,383,384,385,386,396,397,398,399,400,401,402,403,424}'::integer[]))
  • Heap Fetches: 70
21. 4,307.673 119,534.034 ↑ 129.5 50 1

Sort (cost=1,710,979.72..1,710,995.91 rows=6,475 width=1,680) (actual time=119,533.958..119,534.034 rows=50 loops=1)

  • Sort Key: _req.id_import_request DESC NULLS LAST
  • Sort Method: top-N heapsort Memory: 42kB
22. 5,438.332 115,226.361 ↓ 354.3 2,294,198 1

Nested Loop (cost=0.00..1,710,764.63 rows=6,475 width=1,680) (actual time=3,116.076..115,226.361 rows=2,294,198 loops=1)

23. 3,587.277 3,587.277 ↓ 6.2 82,454 1

CTE Scan on infra_col_data (cost=0.00..265.34 rows=13,267 width=1,576) (actual time=2,919.944..3,587.277 rows=82,454 loops=1)

24. 5,524.418 106,200.752 ↓ 14.0 28 82,454

Append (cost=0.00..128.91 rows=2 width=108) (actual time=0.347..1.288 rows=28 loops=82,454)

25. 82.454 82.454 ↓ 0.0 0 82,454

Seq Scan on po_import_request_copy _req (cost=0.00..0.00 rows=1 width=107) (actual time=0.001..0.001 rows=0 loops=82,454)

  • Filter: ((id_enterprise = 83) AND (infra_col_data.id_infra_instan = id_infra_instan) AND ((ts_status_last_updated_at)::date >= '2019-03-01'::date) AND ((ts_status_last_updated_at)::date <= '2019-04-01'::date) AND ((nu_extraction_status / 1000) = ANY ('{8,4,9,0,7,5}'::integer[])))
26. 100,593.880 100,593.880 ↓ 28.0 28 82,454

Index Scan using idx_po_import_request_83_ts_status_last_updated_at_infra on po_import_request_83 _req_1 (cost=0.56..128.91 rows=1 width=108) (actual time=0.340..1.220 rows=28 loops=82,454)

  • Index Cond: ((id_infra_instan = infra_col_data.id_infra_instan) AND ((ts_status_last_updated_at)::date >= '2019-03-01'::date) AND ((ts_status_last_updated_at)::date <= '2019-04-01'::date))
  • Filter: ((id_enterprise = 83) AND ((nu_extraction_status / 1000) = ANY ('{8,4,9,0,7,5}'::integer[])))
Planning time : 4,042.051 ms
Execution time : 119,545.946 ms