explain.depesz.com

PostgreSQL's explain analyze made readable

Result: BRlu

Settings
# exclusive inclusive rows x rows loops node
1. 0.007 6,141.962 ↓ 1.5 6 1

Unique (cost=261,117.28..261,117.39 rows=4 width=98) (actual time=6,141.952..6,141.962 rows=6 loops=1)

  • Planning time: 2.172 ms
  • Execution time: 6159.195 ms
2. 0.077 6,141.955 ↓ 3.5 14 1

Sort (cost=261,117.28..261,117.29 rows=4 width=98) (actual time=6,141.951..6,141.955 rows=14 loops=1)

  • Sort Key: harvester_stems.machine_key, harvester_stems.machine_name, o.start_date, o.end_date, o.object_user_id, o.object_name, o.object_key, o.sub_object_user_id, o.sub_object_name, o.sub_object
  • Sort Method: quicksort Memory: 27kB
3. 0.380 6,141.878 ↓ 3.5 14 1

Hash Join (cost=260,000.42..261,117.24 rows=4 width=98) (actual time=6,140.839..6,141.878 rows=14 loops=1)

  • Hash Cond: (((harvester_stems.machine_key)::text = b.machine_key) AND (o.object_key = b.object_key))
4. 1,108.975 6,141.469 ↑ 27.0 1,505 1

HashAggregate (cost=259,978.66..260,384.76 rows=40,610 width=317) (actual time=6,140.547..6,141.469 rows=1,505 loops=1)

  • Group Key: harvester_stems.machine_key, harvester_stems.machine_name, harvester_stems.contractor_id, o.object_key, o.fo_email, o.fo_business_name, o.object_user_id, o.sub_object_key,
5. 717.242 5,032.494 ↓ 27.9 1,132,891 1

Hash Join (cost=202,002.11..258,252.74 rows=40,610 width=141) (actual time=1,685.341..5,032.494 rows=1,132,891 loops=1)

  • Hash Cond: (((harvester_stems.machine_key)::text = (s.machine_key)::text) AND (harvester_stems.species_group_key = s.species_group_key))
6. 907.107 4,314.945 ↓ 7.1 1,132,891 1

Merge Join (cost=201,985.49..253,046.75 rows=159,442 width=153) (actual time=1,685.020..4,314.945 rows=1,132,891 loops=1)

  • Merge Cond: (((harvester_stems.machine_key)::text = (o.machine_key)::text) AND (harvester_stems.object_key = o.object_key) AND (harvester_stems.sub_object_key = o.sub_obje
7. 1,106.387 3,138.258 ↓ 1.0 1,137,086 1

WindowAgg (cost=201,945.39..230,105.64 rows=1,126,410 width=221) (actual time=1,684.019..3,138.258 rows=1,137,086 loops=1)

8. 1,559.040 2,031.871 ↓ 1.0 1,137,086 1

Sort (cost=201,945.39..204,761.42 rows=1,126,410 width=65) (actual time=1,683.016..2,031.871 rows=1,137,086 loops=1)

  • Sort Key: harvester_stems.machine_key, harvester_stems.object_key, harvester_stems.sub_object_key
  • Sort Method: external merge Disk: 70616kB
9. 472.831 472.831 ↓ 1.0 1,137,086 1

Seq Scan on harvester_stems (cost=0.00..42,519.10 rows=1,126,410 width=65) (actual time=0.042..472.831 rows=1,137,086 loops=1)

10. 269.350 269.580 ↓ 2,149.4 1,132,724 1

Sort (cost=40.09..41.41 rows=527 width=96) (actual time=0.994..269.580 rows=1,132,724 loops=1)

  • Sort Key: o.machine_key, o.object_key, o.sub_object_key
  • Sort Method: quicksort Memory: 110kB
11. 0.230 0.230 ↑ 1.0 527 1

Seq Scan on objects o (cost=0.00..16.27 rows=527 width=96) (actual time=0.018..0.230 rows=527 loops=1)

12. 0.156 0.307 ↑ 1.1 398 1

Hash (cost=10.25..10.25 rows=425 width=41) (actual time=0.307..0.307 rows=398 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 36kB
13. 0.151 0.151 ↑ 1.1 398 1

Seq Scan on species s (cost=0.00..10.25 rows=425 width=41) (actual time=0.008..0.151 rows=398 loops=1)

14. 0.009 0.029 ↓ 2.0 8 1

Hash (cost=21.70..21.70 rows=4 width=36) (actual time=0.029..0.029 rows=8 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
15. 0.020 0.020 ↓ 2.0 8 1

Seq Scan on forest_owner_access b (cost=0.00..21.70 rows=4 width=36) (actual time=0.015..0.020 rows=8 loops=1)

  • Filter: ((active <> 0) AND (t4e_fo_email = 'thomas.solvin@nibio.no'::text))
  • Rows Removed by Filter: 26