explain.depesz.com

PostgreSQL's explain analyze made readable

Result: kCs

Settings
# exclusive inclusive rows x rows loops node
1. 0.089 1,497.194 ↑ 2.1 430 1

Group (cost=140,823.18..141,045.45 rows=895 width=219) (actual time=1,496.667..1,497.194 rows=430 loops=1)

  • Group Key: pharmacy_dim.juridical_name_id, pharmacy_dim.juridical_name, pharmacy_dim.tin
2. 0.000 1,497.105 ↑ 1.4 1,274 1

Gather Merge (cost=140,823.18..141,032.03 rows=1,790 width=117) (actual time=1,496.666..1,497.105 rows=1,274 loops=1)

  • Workers Planned: 2
  • Workers Launched: 2
3. 0.525 4,467.483 ↑ 2.1 425 3

Sort (cost=139,823.15..139,825.39 rows=895 width=117) (actual time=1,489.128..1,489.161 rows=425 loops=3)

  • Sort Key: pharmacy_dim.juridical_name_id, pharmacy_dim.juridical_name, pharmacy_dim.tin
  • Sort Method: quicksort Memory: 123kB
  • Worker 0: Sort Method: quicksort Memory: 124kB
  • Worker 1: Sort Method: quicksort Memory: 122kB
4. 2,334.750 4,466.958 ↑ 2.1 425 3

Partial HashAggregate (cost=139,770.32..139,779.27 rows=895 width=117) (actual time=1,488.903..1,488.986 rows=425 loops=3)

  • Group Key: pharmacy_dim.juridical_name_id, pharmacy_dim.juridical_name, pharmacy_dim.tin
5. 1,420.278 2,132.208 ↑ 1.3 2,753,766 3

Hash Join (cost=205.99..113,953.39 rows=3,442,258 width=117) (actual time=1.079..710.736 rows=2,753,766 loops=3)

  • Hash Cond: (recommended_goods_facts.pharmacy = pharmacy_dim.id)
6. 708.825 708.825 ↑ 1.3 2,753,766 3

Parallel Seq Scan on recommended_goods_facts (cost=0.00..104,697.58 rows=3,442,258 width=8) (actual time=0.013..236.275 rows=2,753,766 loops=3)

7. 1.602 3.105 ↑ 1.0 2,755 3

Hash (cost=171.55..171.55 rows=2,755 width=125) (actual time=1.034..1.035 rows=2,755 loops=3)

  • Buckets: 4096 Batches: 1 Memory Usage: 466kB
8. 1.503 1.503 ↑ 1.0 2,755 3

Seq Scan on pharmacy_dim (cost=0.00..171.55 rows=2,755 width=125) (actual time=0.008..0.501 rows=2,755 loops=3)