explain.depesz.com

PostgreSQL's explain analyze made readable

Result: yJre

Settings
# exclusive inclusive rows x rows loops node
1. 1.220 7,702.851 ↓ 1,000.0 1,000 1

Nested Loop (cost=4.13..643,754.47 rows=1 width=4) (actual time=5,123.592..7,702.851 rows=1,000 loops=1)

  • Buffers: shared hit=9247 read=480214
2. 0.364 7,699.631 ↓ 1,000.0 1,000 1

Nested Loop (cost=3.71..643,752.54 rows=1 width=4) (actual time=5,123.578..7,699.631 rows=1,000 loops=1)

  • Buffers: shared hit=6246 read=480214
3. 1.754 7,696.267 ↓ 1,000.0 1,000 1

Nested Loop (cost=3.29..643,750.6 rows=1 width=8) (actual time=5,123.556..7,696.267 rows=1,000 loops=1)

  • Buffers: shared hit=3245 read=480214
4. 5.929 7,692.513 ↓ 1,000.0 1,000 1

Nested Loop (cost=3.29..643,736.34 rows=1 width=12) (actual time=5,123.546..7,692.513 rows=1,000 loops=1)

  • Buffers: shared hit=2239 read=480214
5. 2.134 7,680.584 ↓ 1,000.0 1,000 1

Nested Loop (cost=3.29..643,734.78 rows=1 width=16) (actual time=5,123.527..7,680.584 rows=1,000 loops=1)

  • Buffers: shared hit=1239 read=480214
6. 3,232.320 7,672.450 ↓ 1,000.0 1,000 1

Hash Join (cost=3.29..643,731.67 rows=1 width=20) (actual time=5,123.507..7,672.45 rows=1,000 loops=1)

  • Buffers: shared hit=239 read=480214
7. 4,438.727 4,438.727 ↑ 1.0 11,876,456 1

Seq Scan on fact_contract_view fact_contract_view (cost=0..599,191.36 rows=11,876,536 width=4) (actual time=0.015..4,438.727 rows=11,876,456 loops=1)

  • Buffers: shared hit=212 read=480214
8. 0.267 1.403 ↓ 1,000.0 1,000 1

Hash (cost=3.27..3.27 rows=1 width=24) (actual time=1.403..1.403 rows=1,000 loops=1)

  • Buffers: shared hit=27
9. 0.206 1.136 ↓ 1,000.0 1,000 1

Subquery Scan on fact_accrual_view (cost=0.43..3.27 rows=1 width=24) (actual time=0.03..1.136 rows=1,000 loops=1)

  • Buffers: shared hit=27
10. 0.125 0.930 ↓ 1,000.0 1,000 1

Limit (cost=0.43..3.26 rows=1 width=568) (actual time=0.03..0.93 rows=1,000 loops=1)

  • Buffers: shared hit=27
11. 0.805 0.805 ↓ 1,000.0 1,000 1

Index Scan using fact_accrual_client_sk_idx on fact_accrual fa (cost=0.43..3.26 rows=1 width=568) (actual time=0.028..0.805 rows=1,000 loops=1)

  • Index Cond: (fa.client_sk = 27)
  • Buffers: shared hit=27
12. 6.000 6.000 ↑ 15.7 6 1,000

Seq Scan on dim_accrual_run dim_accrual_run (cost=0..1.94 rows=94 width=4) (actual time=0.005..0.006 rows=6 loops=1,000)

  • Buffers: shared hit=1000
13. 6.000 6.000 ↑ 1.0 24 1,000

Seq Scan on dim_client dim_client (cost=0..1.25 rows=25 width=4) (actual time=0.002..0.006 rows=24 loops=1,000)

  • Buffers: shared hit=1000
14. 2.000 2.000 ↑ 278.0 1 1,000

Seq Scan on dim_lumpsum dim_lumpsum (cost=0..10.78 rows=278 width=4) (actual time=0.002..0.002 rows=1 loops=1,000)

  • Buffers: shared hit=1006
15. 3.000 3.000 ↑ 1.0 1 1,000

Index Only Scan using dim_product_pkey on dim_product dim_product (cost=0.42..1.94 rows=1 width=4) (actual time=0.003..0.003 rows=1 loops=1,000)

  • Index Cond: (dim_product.product_sk = fact_accrual_view.product_sk)
  • Buffers: shared hit=3001
16. 2.000 2.000 ↑ 1.0 1 1,000

Index Only Scan using dim_company_company_sk_idx on dim_company dim_company (cost=0.42..1.94 rows=1 width=4) (actual time=0.002..0.002 rows=1 loops=1,000)

  • Index Cond: (dim_company.company_sk = fact_accrual_view.accrual_company_sk)
  • Buffers: shared hit=3001