explain.depesz.com

PostgreSQL's explain analyze made readable

Result: x3rM

Settings
# exclusive inclusive rows x rows loops node
1. 1.547 748.019 ↑ 1.0 10,000 1

Limit (cost=2,719.95..17,999.29 rows=10,000 width=2,165) (actual time=27.994..748.019 rows=10,000 loops=1)

2. 585.569 746.472 ↑ 1.9 10,000 1

Hash Left Join (cost=2,719.95..32,474.95 rows=19,474 width=2,165) (actual time=27.992..746.472 rows=10,000 loops=1)

  • Hash Cond: (jobs."functionLevelId" = function_levels.id)
3. 4.403 160.885 ↑ 1.9 10,000 1

Hash Left Join (cost=2,718.82..31,868.64 rows=19,474 width=3,581) (actual time=27.892..160.885 rows=10,000 loops=1)

  • Hash Cond: (jobs."contractTypeId" = contract_types.id)
4. 4.740 156.464 ↑ 1.9 10,000 1

Hash Left Join (cost=2,717.73..31,724.60 rows=19,474 width=3,377) (actual time=27.861..156.464 rows=10,000 loops=1)

  • Hash Cond: (jobs."industryId" = industries.id)
5. 3.908 151.694 ↑ 1.9 10,000 1

Hash Left Join (cost=2,715.01..31,467.62 rows=19,474 width=3,244) (actual time=27.807..151.694 rows=10,000 loops=1)

  • Hash Cond: (jobs."yearsOfExperienceId" = years_of_experiences.id)
6. 5.088 147.755 ↑ 1.9 10,000 1

Hash Left Join (cost=2,713.89..31,342.41 rows=19,474 width=3,036) (actual time=27.763..147.755 rows=10,000 loops=1)

  • Hash Cond: (jobs."categoryId" = categories.id)
7. 6.747 142.635 ↑ 1.9 10,000 1

Hash Left Join (cost=2,712.20..31,072.94 rows=19,474 width=2,899) (actual time=27.710..142.635 rows=10,000 loops=1)

  • Hash Cond: (jobs."educationId" = educations.id)
8. 4.350 135.865 ↑ 1.9 10,000 1

Hash Left Join (cost=2,711.02..30,938.84 rows=19,474 width=2,738) (actual time=27.674..135.865 rows=10,000 loops=1)

  • Hash Cond: (jobs."employmentTypeId" = employment_types.id)
9. 4.802 131.473 ↑ 1.9 10,000 1

Hash Left Join (cost=2,709.88..30,718.61 rows=19,474 width=2,498) (actual time=27.605..131.473 rows=10,000 loops=1)

  • Hash Cond: (jobs."countryId" = countries.id)
10. 10.454 126.540 ↑ 1.9 10,000 1

Hash Left Join (cost=2,698.19..30,439.16 rows=19,474 width=2,408) (actual time=27.454..126.540 rows=10,000 loops=1)

  • Hash Cond: (jobs."languageId" = languages.id)
11. 9.893 116.053 ↑ 1.9 10,000 1

Hash Join (cost=2,696.85..30,170.06 rows=19,474 width=2,267) (actual time=27.395..116.053 rows=10,000 loops=1)

  • Hash Cond: (jobs."companyId" = companies.id)
12. 78.852 78.852 ↑ 2.2 12,198 1

Seq Scan on jobs (cost=0.00..27,178.52 rows=26,653 width=1,845) (actual time=0.016..78.852 rows=12,198 loops=1)

  • Filter: (("closedAt" IS NULL) AND ((deadline IS NULL) OR (deadline > now())))
  • Rows Removed by Filter: 9,494
13. 3.261 27.308 ↑ 1.1 5,330 1

Hash (cost=2,625.99..2,625.99 rows=5,669 width=426) (actual time=27.308..27.308 rows=5,330 loops=1)

  • Buckets: 8,192 Batches: 1 Memory Usage: 2,205kB
14. 24.047 24.047 ↑ 1.1 5,330 1

Seq Scan on companies (cost=0.00..2,625.99 rows=5,669 width=426) (actual time=0.037..24.047 rows=5,330 loops=1)

  • Filter: ((offline IS FALSE) AND ((state)::text = 'APPROVED'::text))
  • Rows Removed by Filter: 1,897
15. 0.010 0.033 ↑ 1.0 15 1

Hash (cost=1.15..1.15 rows=15 width=145) (actual time=0.033..0.033 rows=15 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 10kB
16. 0.023 0.023 ↑ 1.0 15 1

Seq Scan on languages (cost=0.00..1.15 rows=15 width=145) (actual time=0.020..0.023 rows=15 loops=1)

17. 0.062 0.131 ↑ 1.0 253 1

Hash (cost=8.53..8.53 rows=253 width=94) (actual time=0.131..0.131 rows=253 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 43kB
18. 0.069 0.069 ↑ 1.0 253 1

Seq Scan on countries (cost=0.00..8.53 rows=253 width=94) (actual time=0.015..0.069 rows=253 loops=1)

19. 0.024 0.042 ↓ 1.5 9 1

Hash (cost=1.06..1.06 rows=6 width=244) (actual time=0.041..0.042 rows=9 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 10kB
20. 0.018 0.018 ↓ 1.5 9 1

Seq Scan on employment_types (cost=0.00..1.06 rows=6 width=244) (actual time=0.017..0.018 rows=9 loops=1)

21. 0.004 0.023 ↑ 1.0 8 1

Hash (cost=1.08..1.08 rows=8 width=165) (actual time=0.023..0.023 rows=8 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 10kB
22. 0.019 0.019 ↑ 1.0 8 1

Seq Scan on educations (cost=0.00..1.08 rows=8 width=165) (actual time=0.017..0.019 rows=8 loops=1)

23. 0.011 0.032 ↑ 1.0 31 1

Hash (cost=1.31..1.31 rows=31 width=141) (actual time=0.031..0.032 rows=31 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 14kB
24. 0.021 0.021 ↑ 1.0 31 1

Seq Scan on categories (cost=0.00..1.31 rows=31 width=141) (actual time=0.016..0.021 rows=31 loops=1)

25. 0.006 0.031 ↑ 1.0 5 1

Hash (cost=1.05..1.05 rows=5 width=212) (actual time=0.031..0.031 rows=5 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 9kB
26. 0.025 0.025 ↑ 1.0 5 1

Seq Scan on years_of_experiences (cost=0.00..1.05 rows=5 width=212) (actual time=0.024..0.025 rows=5 loops=1)

27. 0.009 0.030 ↑ 1.0 32 1

Hash (cost=2.32..2.32 rows=32 width=137) (actual time=0.030..0.030 rows=32 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 14kB
28. 0.021 0.021 ↑ 1.0 32 1

Seq Scan on industries (cost=0.00..2.32 rows=32 width=137) (actual time=0.011..0.021 rows=32 loops=1)

29. 0.004 0.018 ↑ 1.0 4 1

Hash (cost=1.04..1.04 rows=4 width=208) (actual time=0.018..0.018 rows=4 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 9kB
30. 0.014 0.014 ↑ 1.0 4 1

Seq Scan on contract_types (cost=0.00..1.04 rows=4 width=208) (actual time=0.013..0.014 rows=4 loops=1)

31. 0.005 0.018 ↑ 1.0 6 1

Hash (cost=1.06..1.06 rows=6 width=212) (actual time=0.018..0.018 rows=6 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 9kB
32. 0.013 0.013 ↑ 1.0 6 1

Seq Scan on function_levels (cost=0.00..1.06 rows=6 width=212) (actual time=0.013..0.013 rows=6 loops=1)

Planning time : 17.260 ms
Execution time : 749.128 ms