explain.depesz.com

PostgreSQL's explain analyze made readable

Result: P7y9

Settings
# exclusive inclusive rows x rows loops node
1. 0.000 1,132.535 ↑ 267.2 4 1

Finalize GroupAggregate (cost=42,354.34..42,502.48 rows=1,069 width=248) (actual time=1,131.765..1,132.535 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 1,162.096 ↑ 74.2 12 1

Gather Merge (cost=42,354.34..42,472.64 rows=890 width=248) (actual time=1,131.560..1,162.096 rows=12 loops=1)

  • Workers Planned: 2
  • Workers Launched: 2
3. 2.259 3,101.727 ↑ 111.2 4 3

Partial GroupAggregate (cost=41,354.32..41,369.89 rows=445 width=248) (actual time=1,033.354..1,033.909 rows=4 loops=3)

  • Group Key: n1.n_name, n2.n_name, (date_part('year'::text, (lineitem.l_shipdate)::timestamp without time zone))
4. 5.202 3,099.468 ↑ 1.3 343 3

Sort (cost=41,354.32..41,355.43 rows=445 width=228) (actual time=1,033.114..1,033.156 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: 82kB
5. 28.914 3,094.266 ↑ 1.3 343 3

Hash Join (cost=374.34..41,334.74 rows=445 width=228) (actual time=14.539..1,031.422 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. 80.999 3,064.458 ↑ 1.2 8,665 3

Nested Loop (cost=372.94..41,303.00 rows=10,705 width=128) (actual time=10.592..1,021.486 rows=8,665 loops=3)

7. 54.419 2,645.511 ↑ 1.2 8,665 3

Nested Loop (cost=372.52..36,451.80 rows=10,705 width=128) (actual time=10.522..881.837 rows=8,665 loops=3)

8. 150.081 2,253.144 ↑ 1.2 8,665 3

Hash Join (cost=372.10..28,761.53 rows=10,705 width=128) (actual time=10.397..751.048 rows=8,665 loops=3)

  • Hash Cond: (lineitem.l_suppkey = supplier.s_suppkey)
9. 2,072.904 2,072.904 ↑ 1.3 106,367 3

Parallel Seq Scan on lineitem (cost=0.00..27,780.60 rows=133,808 width=32) (actual time=0.283..690.968 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. 1.644 30.159 ↓ 1.0 817 3

Hash (cost=362.10..362.10 rows=800 width=108) (actual time=10.053..10.053 rows=817 loops=3)

  • Buckets: 1024 Batches: 1 Memory Usage: 58kB
11. 10.917 28.515 ↓ 1.0 817 3

Hash Join (cost=1.40..362.10 rows=800 width=108) (actual time=0.307..9.505 rows=817 loops=3)

  • Hash Cond: (supplier.s_nationkey = n1.n_nationkey)
12. 17.469 17.469 ↑ 1.0 10,000 3

Seq Scan on supplier (cost=0.00..330.00 rows=10,000 width=12) (actual time=0.221..5.823 rows=10,000 loops=3)

13. 0.048 0.129 ↑ 1.0 2 3

Hash (cost=1.38..1.38 rows=2 width=108) (actual time=0.043..0.043 rows=2 loops=3)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
14. 0.081 0.081 ↑ 1.0 2 3

Seq Scan on nation n1 (cost=0.00..1.38 rows=2 width=108) (actual time=0.020..0.027 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. 337.948 337.948 ↑ 1.0 1 25,996

Index Scan using customer_pkey on customer (cost=0.42..0.45 rows=1 width=12) (actual time=0.013..0.013 rows=1 loops=25,996)

  • Index Cond: (c_custkey = orders.o_custkey)
17. 0.060 0.894 ↑ 1.0 2 3

Hash (cost=1.38..1.38 rows=2 width=108) (actual time=0.298..0.298 rows=2 loops=3)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
18. 0.834 0.834 ↑ 1.0 2 3

Seq Scan on nation n2 (cost=0.00..1.38 rows=2 width=108) (actual time=0.266..0.278 rows=2 loops=3)

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