explain.depesz.com

PostgreSQL's explain analyze made readable

Result: fZHR

Settings
# exclusive inclusive rows x rows loops node
1. 0.000 1,391.651 ↑ 267.2 4 1

Finalize GroupAggregate (cost=42,354.34..42,502.48 rows=1,069 width=248) (actual time=1,389.037..1,391.651 rows=4 loops=1)

  • Group Key: n1.n_name, n2.n_name, (date_part('year'::text, (lineitem.l_shipdate)::timestamp without time zone))
2. 0.000 1,440.381 ↑ 74.2 12 1

Gather Merge (cost=42,354.34..42,472.64 rows=890 width=248) (actual time=1,388.844..1,440.381 rows=12 loops=1)

  • Workers Planned: 2
  • Workers Launched: 2
3. 4.035 3,510.846 ↑ 111.2 4 3

Partial GroupAggregate (cost=41,354.32..41,369.89 rows=445 width=248) (actual time=1,169.142..1,170.282 rows=4 loops=3)

  • Group Key: n1.n_name, n2.n_name, (date_part('year'::text, (lineitem.l_shipdate)::timestamp without time zone))
4. 5.781 3,506.811 ↑ 1.3 343 3

Sort (cost=41,354.32..41,355.43 rows=445 width=228) (actual time=1,168.889..1,168.937 rows=343 loops=3)

  • Sort Key: n1.n_name, n2.n_name, (date_part('year'::text, (lineitem.l_shipdate)::timestamp without time zone))
  • Sort Method: quicksort Memory: 79kB
5. 23.892 3,501.030 ↑ 1.3 343 3

Hash Join (cost=374.34..41,334.74 rows=445 width=228) (actual time=17.192..1,167.010 rows=343 loops=3)

  • Hash Cond: (customer.c_nationkey = n2.n_nationkey)
  • Join Filter: (((n1.n_name = 'INDIA'::bpchar) AND (n2.n_name = 'FRANCE'::bpchar)) OR ((n1.n_name = 'FRANCE'::bpchar) AND (n2.n_name = 'INDIA'::bpchar)))
  • Rows Removed by Join Filter: 335
6. 81.451 3,476.136 ↑ 1.2 8,665 3

Nested Loop (cost=372.94..41,303.00 rows=10,705 width=128) (actual time=12.451..1,158.712 rows=8,665 loops=3)

7. 52.070 3,030.741 ↑ 1.2 8,665 3

Nested Loop (cost=372.52..36,451.80 rows=10,705 width=128) (actual time=12.372..1,010.247 rows=8,665 loops=3)

8. 164.592 2,640.723 ↑ 1.2 8,665 3

Hash Join (cost=372.10..28,761.53 rows=10,705 width=128) (actual time=12.211..880.241 rows=8,665 loops=3)

  • Hash Cond: (lineitem.l_suppkey = supplier.s_suppkey)
9. 2,440.788 2,440.788 ↑ 1.3 106,367 3

Parallel Seq Scan on lineitem (cost=0.00..27,780.60 rows=133,808 width=32) (actual time=0.329..813.596 rows=106,367 loops=3)

  • Filter: ((l_shipdate >= '1995-01-01'::date) AND (l_shipdate <= '1996-12-31'::date))
  • Rows Removed by Filter: 243158
10. 2.001 35.343 ↓ 1.0 817 3

Hash (cost=362.10..362.10 rows=800 width=108) (actual time=11.781..11.781 rows=817 loops=3)

  • Buckets: 1024 Batches: 1 Memory Usage: 58kB
11. 13.245 33.342 ↓ 1.0 817 3

Hash Join (cost=1.40..362.10 rows=800 width=108) (actual time=0.367..11.114 rows=817 loops=3)

  • Hash Cond: (supplier.s_nationkey = n1.n_nationkey)
12. 19.908 19.908 ↑ 1.0 10,000 3

Seq Scan on supplier (cost=0.00..330.00 rows=10,000 width=12) (actual time=0.252..6.636 rows=10,000 loops=3)

13. 0.051 0.189 ↑ 1.0 2 3

Hash (cost=1.38..1.38 rows=2 width=108) (actual time=0.063..0.063 rows=2 loops=3)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
14. 0.138 0.138 ↑ 1.0 2 3

Seq Scan on nation n1 (cost=0.00..1.38 rows=2 width=108) (actual time=0.028..0.046 rows=2 loops=3)

  • Filter: ((n_name = 'INDIA'::bpchar) OR (n_name = 'FRANCE'::bpchar))
  • Rows Removed by Filter: 23
15. 337.948 337.948 ↑ 1.0 1 25,996

Index Scan using orders_pkey on orders (cost=0.42..0.72 rows=1 width=12) (actual time=0.013..0.013 rows=1 loops=25,996)

  • Index Cond: (o_orderkey = lineitem.l_orderkey)
16. 363.944 363.944 ↑ 1.0 1 25,996

Index Scan using customer_pkey on customer (cost=0.42..0.45 rows=1 width=12) (actual time=0.014..0.014 rows=1 loops=25,996)

  • Index Cond: (c_custkey = orders.o_custkey)
17. 0.063 1.002 ↑ 1.0 2 3

Hash (cost=1.38..1.38 rows=2 width=108) (actual time=0.334..0.334 rows=2 loops=3)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
18. 0.939 0.939 ↑ 1.0 2 3

Seq Scan on nation n2 (cost=0.00..1.38 rows=2 width=108) (actual time=0.300..0.313 rows=2 loops=3)

  • Filter: ((n_name = 'FRANCE'::bpchar) OR (n_name = 'INDIA'::bpchar))
  • Rows Removed by Filter: 23