explain.depesz.com

PostgreSQL's explain analyze made readable

Result: B8K3

Settings
# exclusive inclusive rows x rows loops node
1. 0.000 0.000 ↓ 0.0

Hash Left Join (cost=339.15..23,522,295.45 rows=1,196 width=323) (actual rows= loops=)

  • Hash Cond: (p.family_id = f.id)
2. 0.000 0.000 ↓ 0.0

Hash Left Join (cost=214.28..5,029.05 rows=1,196 width=172) (actual rows= loops=)

  • Hash Cond: (p.brand_id = b.id)
3. 0.000 0.000 ↓ 0.0

Index Scan using parts_pk on parts p (cost=0.56..4,798.89 rows=1,196 width=162) (actual rows= loops=)

  • Index Cond: ((id >= 10000) AND (id <= 11000))
4. 0.000 0.000 ↓ 0.0

Hash (cost=155.54..155.54 rows=4,654 width=14) (actual rows= loops=)

5. 0.000 0.000 ↓ 0.0

Seq Scan on brands b (cost=0.00..155.54 rows=4,654 width=14) (actual rows= loops=)

6. 0.000 0.000 ↓ 0.0

Hash (cost=93.83..93.83 rows=2,483 width=27) (actual rows= loops=)

7. 0.000 0.000 ↓ 0.0

Seq Scan on families f (cost=0.00..93.83 rows=2,483 width=27) (actual rows= loops=)

8.          

SubPlan (forHash Left Join)

9. 0.000 0.000 ↓ 0.0

Index Only Scan using parts_categories_pkey on parts_categories (cost=0.56..4.91 rows=20 width=4) (actual rows= loops=)

  • Index Cond: (part_id = p.id)
10. 0.000 0.000 ↓ 0.0

Aggregate (cost=19,503.16..19,503.18 rows=1 width=32) (actual rows= loops=)

11. 0.000 0.000 ↓ 0.0

Merge Join (cost=0.86..19,502.69 rows=189 width=38) (actual rows= loops=)

  • Merge Cond: (pa.vehicle_id = v.id)
12. 0.000 0.000 ↓ 0.0

Index Only Scan using parts_applicability_pkey on parts_applicability pa (cost=0.57..139.38 rows=4,046 width=4) (actual rows= loops=)

  • Index Cond: (part_id = p.id)
13. 0.000 0.000 ↓ 0.0

Index Scan using vehicles_pk on vehicles v (cost=0.29..19,342.80 rows=3,402 width=38) (actual rows= loops=)

  • Index Cond: (id = ANY 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14. 0.000 0.000 ↓ 0.0

Aggregate (cost=97.31..97.32 rows=1 width=32) (actual rows= loops=)

15. 0.000 0.000 ↓ 0.0

Hash Right Join (cost=30.30..97.29 rows=1 width=62) (actual rows= loops=)

  • Hash Cond: (ups.parent_id = up.id)
16. 0.000 0.000 ↓ 0.0

Seq Scan on user_profiles_supplier ups (cost=0.00..65.62 rows=362 width=8) (actual rows= loops=)

17. 0.000 0.000 ↓ 0.0

Hash (cost=30.29..30.29 rows=1 width=62) (actual rows= loops=)

18. 0.000 0.000 ↓ 0.0

Nested Loop (cost=1.26..30.29 rows=1 width=62) (actual rows= loops=)

  • Join Filter: (date_part('day'::text, (now() - (sp.last_import_at)::timestamp with time zone)) < (up.price_active)::double precision)
19. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.99..24.99 rows=1 width=44) (actual rows= loops=)

20. 0.000 0.000 ↓ 0.0

Index Scan using sp_part_id_rdtree_idx on supplier_parts sp (cost=0.56..16.54 rows=1 width=40) (actual rows= loops=)

  • Index Cond: (part_id = p.id)
  • Filter: (enabled AND (price > '0'::double precision))
21. 0.000 0.000 ↓ 0.0

Index Scan using users_pkey on users u (cost=0.42..8.44 rows=1 width=8) (actual rows= loops=)

  • Index Cond: (user_id = sp.supplier_id)
  • Filter: (state = 1)
22. 0.000 0.000 ↓ 0.0

Index Scan using uniq_a40b9810bf396750 on user_profiles_supplier up (cost=0.27..5.27 rows=1 width=22) (actual rows= loops=)

  • Index Cond: (id = u.profile_supplier_id)
  • Filter: ((status)::text = 'approved'::text)
23. 0.000 0.000 ↓ 0.0

Aggregate (cost=57.73..57.74 rows=1 width=32) (actual rows= loops=)

24. 0.000 0.000 ↓ 0.0

Nested Loop Left Join (cost=1.26..57.72 rows=3 width=22) (actual rows= loops=)

25. 0.000 0.000 ↓ 0.0

Nested Loop Left Join (cost=0.99..41.88 rows=3 width=16) (actual rows= loops=)

26. 0.000 0.000 ↓ 0.0

Index Scan using sp_part_id_rdtree_idx on supplier_parts spp (cost=0.56..16.53 rows=3 width=12) (actual rows= loops=)

  • Index Cond: (part_id = p.id)
27. 0.000 0.000 ↓ 0.0

Index Scan using users_pkey on users u_1 (cost=0.42..8.44 rows=1 width=8) (actual rows= loops=)

  • Index Cond: (user_id = spp.supplier_id)
28. 0.000 0.000 ↓ 0.0

Index Scan using uniq_a40b9810bf396750 on user_profiles_supplier up_1 (cost=0.27..5.27 rows=1 width=14) (actual rows= loops=)

  • Index Cond: (u_1.profile_supplier_id = id)