explain.depesz.com

A tool for finding a real cause for slow queries.

Result: DaK

options
Did it help? Consider supporting us - Bitcoin address: 12v2hUztAk2LgzQ9H9LMwuU32urHMjZQnq
# exclusive inclusive rows x rows loops node
1. 0.000 0.000 ↓ 0.0

Limit (cost=467,220.77..467,220.87 rows=10 width=4) (actual time=.. rows= loops=)

2. 0.000 0.000 ↓ 0.0

HashAggregate (cost=467,220.77..467,221.02 rows=25 width=4) (actual time=.. rows= loops=)

3. 0.000 0.000 ↓ 0.0

Hash Semi Join (cost=278,516.90..467,220.71 rows=25 width=4) (actual time=.. rows= loops=)

  • Hash Cond: (candidates.id = subquery_candidates.id)
4. 0.000 0.000 ↓ 0.0

Hash Left Join (cost=277,682.09..459,919.40 rows=2,463,320 width=4) (actual time=.. rows= loops=)

  • Hash Cond: (candidates.id = users.profile_id)
5. 0.000 0.000 ↓ 0.0

Hash Right Join (cost=160,092.76..267,305.85 rows=2,463,320 width=4) (actual time=.. rows= loops=)

  • Hash Cond: (public.employments.candidate_id = candidates.id)
6. 0.000 0.000 ↓ 0.0

Seq Scan on employments (cost=0.00..54,713.90 rows=1,614,090 width=4) (actual time=.. rows= loops=)

7. 0.000 0.000 ↓ 0.0

Hash (cost=119,678.26..119,678.26 rows=2,463,320 width=4) (actual time=.. rows= loops=)

8. 0.000 0.000 ↓ 0.0

Hash Right Join (cost=100,619.70..119,678.26 rows=2,463,320 width=4) (actual time=.. rows= loops=)

  • Hash Cond: (folder_assignements.candidate_id = candidates.id)
9. 0.000 0.000 ↓ 0.0

Seq Scan on folder_assignements (cost=0.00..2,580.63 rows=167,463 width=8) (actual time=.. rows= loops=)

10. 0.000 0.000 ↓ 0.0

Hash (cost=57,800.20..57,800.20 rows=2,463,320 width=12) (actual time=.. rows= loops=)

11. 0.000 0.000 ↓ 0.0

Seq Scan on candidates (cost=0.00..57,800.20 rows=2,463,320 width=12) (actual time=.. rows= loops=)

12. 0.000 0.000 ↓ 0.0

Hash (cost=77,174.70..77,174.70 rows=2,463,330 width=4) (actual time=.. rows= loops=)

13. 0.000 0.000 ↓ 0.0

Seq Scan on users (cost=0.00..77,174.70 rows=2,463,330 width=4) (actual time=.. rows= loops=)

  • Filter: ((profile_type)::text = 'Candidate'::text)
14. 0.000 0.000 ↓ 0.0

Hash (cost=834.50..834.50 rows=25 width=8) (actual time=.. rows= loops=)

15. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.00..834.50 rows=25 width=8) (actual time=.. rows= loops=)

16. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.00..626.09 rows=25 width=4) (actual time=.. rows= loops=)

17. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.00..338.52 rows=20 width=4) (actual time=.. rows= loops=)

18. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.00..162.81 rows=14 width=8) (actual time=.. rows= loops=)

19. 0.000 0.000 ↓ 0.0

Index Scan using index_employments_on_employer_id on employments (cost=0.00..43.10 rows=14 width=4) (actual time=.. rows= loops=)

  • Index Cond: (employer_id = 2710)
20. 0.000 0.000 ↓ 0.0

Index Scan using candidates_pkey on candidates imported_friends (cost=0.00..8.54 rows=1 width=12) (actual time=.. rows= loops=)

  • Index Cond: (id = public.employments.candidate_id)
21. 0.000 0.000 ↓ 0.0

Index Scan using index_facebook_friends_on_fb_id on facebook_friends (cost=0.00..12.53 rows=2 width=12) (actual time=.. rows= loops=)

  • Index Cond: (fb_id = imported_friends.fb_id)
22. 0.000 0.000 ↓ 0.0

Index Scan using index_relationships_on_contact_id_and_contact_type on relationships (cost=0.00..14.34 rows=3 width=8) (actual time=.. rows= loops=)

  • Index Cond: ((contact_id = facebook_friends.id) AND ((contact_type)::text = 'FacebookFriend'::text))
23. 0.000 0.000 ↓ 0.0

Index Scan using candidates_pkey on candidates subquery_candidates (cost=0.00..8.32 rows=1 width=4) (actual time=.. rows= loops=)

  • Index Cond: (id = relationships.candidate_id)