explain.depesz.com

PostgreSQL's explain analyze made readable

Result: wfq5

Settings
# exclusive inclusive rows x rows loops node
1. 0.000 0.000 ↓ 0.0

HashAggregate (cost=413.16..416.40 rows=144 width=40) (actual rows= loops=)

  • Group Key: timezone('Etc/UTC'::text, date_trunc('month'::text, timezone('Etc/UTC'::text, (insights_metrics.calculated_on)::timestamp with time zone)))
  • Group Key: timezone('Etc/UTC'::text, date_trunc('month'::text, timezone('Etc/UTC'::text, (insights_metrics.calculated_on)::timestamp with time zone)))
2. 0.000 0.000 ↓ 0.0

Hash Semi Join (cost=5.72..396.41 rows=1,340 width=108) (actual rows= loops=)

  • Hash Cond: ((insights_metrics.target_id)::integer = "ANY_subquery".id)
3. 0.000 0.000 ↓ 0.0

Seq Scan on insights_metrics (cost=0.00..351.66 rows=2,681 width=106) (actual rows= loops=)

  • Filter: ((calculated_on IS NOT NULL) AND (calculated_on >= '2019-06-10'::date) AND (calculated_on <= '2019-09-10'::date) AND ((type)::text = 'Insights::Metrics::StoreReadership'::text) AND ((target_type)::text = 'Team'::text))
4. 0.000 0.000 ↓ 0.0

Hash (cost=5.08..5.08 rows=51 width=4) (actual rows= loops=)

5. 0.000 0.000 ↓ 0.0

Subquery Scan on ANY_subquery (cost=4.44..5.08 rows=51 width=4) (actual rows= loops=)

6. 0.000 0.000 ↓ 0.0

Sort (cost=4.44..4.57 rows=51 width=18) (actual rows= loops=)

  • Sort Key: teams.name
7. 0.000 0.000 ↓ 0.0

Seq Scan on teams (cost=0.00..3.00 rows=51 width=18) (actual rows= loops=)

8. 0.000 0.000 ↓ 0.0

Filter: ((deleted_at IS NULL) AND ((closed_at IS NULL) OR (closed_at > '2019-06-10 07:00:00'::timestamp without time zone)) AND (created_at < '2019-09-11 06:59:59.999999'::timestamp without time zone) AND (team_type_id = 4))HashAggregate (cost=413.16..416.40 rows=144 width=40) (actual rows= loops=)

9. 0.000 0.000 ↓ 0.0

Hash Semi Join (cost=5.72..396.41 rows=1,340 width=108) (actual rows= loops=)

  • Hash Cond: ((insights_metrics.target_id)::integer = "ANY_subquery".id)
10. 0.000 0.000 ↓ 0.0

Seq Scan on insights_metrics (cost=0.00..351.66 rows=2,681 width=106) (actual rows= loops=)

  • Filter: ((calculated_on IS NOT NULL) AND (calculated_on >= '2019-06-10'::date) AND (calculated_on <= '2019-09-10'::date) AND ((type)::text = 'Insights::Metrics::StoreReadership'::text) AND ((target_type)::text = 'Team'::text))
11. 0.000 0.000 ↓ 0.0

Hash (cost=5.08..5.08 rows=51 width=4) (actual rows= loops=)

12. 0.000 0.000 ↓ 0.0

Subquery Scan on ANY_subquery (cost=4.44..5.08 rows=51 width=4) (actual rows= loops=)

13. 0.000 0.000 ↓ 0.0

Sort (cost=4.44..4.57 rows=51 width=18) (actual rows= loops=)

  • Sort Key: teams.name
14. 0.000 0.000 ↓ 0.0

Seq Scan on teams (cost=0.00..3.00 rows=51 width=18) (actual rows= loops=)

  • Filter: ((deleted_at IS NULL) AND ((closed_at IS NULL) OR (closed_at > '2019-06-10 07:00:00'::timestamp without time zone)) AND (created_at < '2019-09-11 06:59:59.999999'::timestamp without time zone) AND (team_type_id = 4))