explain.depesz.com

PostgreSQL's explain analyze made readable

Result: 3bZg

Settings
# exclusive inclusive rows x rows loops node
1. 0.006 2.028 ↑ 1.0 1 1

Unique (cost=67.04..67.09 rows=1 width=184) (actual time=2.022..2.028 rows=1 loops=1)

2. 0.043 2.022 ↓ 4.0 4 1

Sort (cost=67.04..67.05 rows=1 width=184) (actual time=2.021..2.022 rows=4 loops=1)

  • Sort Key: policyloss0_.id, policyloss0_.id_roszczenia, policyloss0_.sygnatura_roszczenia, policyloss0_.status_roszczenia_nazwa, policyloss0_.data_powstania, policyloss0_.id_oszacowania, policyloss0_.kod_ubezp, policyloss0_.kod_ryzyka, policyloss0_.data_zgloszenia, policyloss0_.wyplaty, policyloss0_.nr_polisy2, policyloss0_.rezerwa_rbnp, policyloss0_.sygnatura_szkody, policyloss0_.status_obslugi, policyloss0_.taryfa_szablon
  • Sort Method: quicksort Memory: 26kB
3. 0.007 1.979 ↓ 4.0 4 1

Nested Loop (cost=2.43..67.03 rows=1 width=184) (actual time=0.560..1.979 rows=4 loops=1)

  • Join Filter: (productgro4_1_.id = productgro4_.id)
4. 0.003 1.960 ↓ 4.0 4 1

Nested Loop (cost=2.15..66.72 rows=1 width=200) (actual time=0.550..1.960 rows=4 loops=1)

5. 0.051 1.905 ↓ 26.0 26 1

Nested Loop (cost=2.00..66.55 rows=1 width=208) (actual time=0.104..1.905 rows=26 loops=1)

6. 0.068 1.294 ↓ 80.0 80 1

Nested Loop (cost=1.58..66.06 rows=1 width=32) (actual time=0.061..1.294 rows=80 loops=1)

7. 0.021 0.746 ↓ 80.0 80 1

Nested Loop (cost=1.15..65.54 rows=1 width=24) (actual time=0.052..0.746 rows=80 loops=1)

8. 0.031 0.233 ↓ 27.3 164 1

Nested Loop (cost=0.86..63.60 rows=6 width=16) (actual time=0.043..0.233 rows=164 loops=1)

9. 0.024 0.024 ↑ 1.0 1 1

Index Scan using idx_person_pesel on prs_person personenti5_ (cost=0.43..8.45 rows=1 width=8) (actual time=0.024..0.024 rows=1 loops=1)

  • Index Cond: ((pesel)::text = '70072914930'::text)
10. 0.178 0.178 ↓ 11.7 164 1

Index Scan using idx_person_id on pcy_person_value personvalu2_ (cost=0.43..55.01 rows=14 width=24) (actual time=0.015..0.178 rows=164 loops=1)

  • Index Cond: (person_id = personenti5_.id)
11. 0.492 0.492 ↓ 0.0 0 164

Index Scan using pk_prd_item on prd_item productgro4_1_ (cost=0.29..0.31 rows=1 width=8) (actual time=0.003..0.003 rows=0 loops=164)

  • Index Cond: (id = personvalu2_.group_id)
  • Filter: ((alias)::text = 'UBEZPIECZONY'::text)
  • Rows Removed by Filter: 1
12. 0.480 0.480 ↑ 1.0 1 80

Index Scan using pk_pcy_policy on pcy_policy policyenti1_ (cost=0.43..0.51 rows=1 width=24) (actual time=0.006..0.006 rows=1 loops=80)

  • Index Cond: (id = personvalu2_.policy_id)
13. 0.560 0.560 ↓ 0.0 0 80

Index Scan using idx_pcy_loss_ratio_nr_polisy2 on pcy_loss_ratio policyloss0_ (cost=0.42..0.46 rows=2 width=184) (actual time=0.007..0.007 rows=0 loops=80)

  • Index Cond: ((nr_polisy2)::text = (policyenti1_.policy_number)::text)
14. 0.052 0.052 ↓ 0.0 0 26

Index Scan using pk_prd_product on prd_product productent3_ (cost=0.14..0.17 rows=1 width=8) (actual time=0.002..0.002 rows=0 loops=26)

  • Index Cond: (id = policyenti1_.product_id)
  • Filter: ((code)::text = ANY ('{A15,Zodiak,ZPro}'::text[]))
  • Rows Removed by Filter: 1
15. 0.012 0.012 ↑ 1.0 1 4

Index Only Scan using pk_prd_group on prd_group productgro4_ (cost=0.28..0.30 rows=1 width=8) (actual time=0.003..0.003 rows=1 loops=4)

  • Index Cond: (id = personvalu2_.group_id)
  • Heap Fetches: 4