explain.depesz.com

PostgreSQL's explain analyze made readable

Result: QRJ4

Settings
# exclusive inclusive rows x rows loops node
1. 0.001 378.015 ↓ 0.0 0 1

Limit (cost=0.57..336,853.12 rows=70 width=491) (actual time=378.015..378.015 rows=0 loops=1)

2. 0.449 378.014 ↓ 0.0 0 1

Nested Loop (cost=0.57..336,853.12 rows=70 width=491) (actual time=378.014..378.014 rows=0 loops=1)

  • Join Filter: (d.responsible_org_orgref = resporg.swa_org_ref)
3. 0.285 0.285 ↑ 1.0 1,310 1

Seq Scan on orgref resporg (cost=0.00..37.10 rows=1,310 width=26) (actual time=0.005..0.285 rows=1,310 loops=1)

4. 0.330 377.280 ↓ 0.0 0 1,310

Materialize (cost=0.57..335,369.47 rows=70 width=642) (actual time=0.288..0.288 rows=0 loops=1,310)

5. 0.665 376.950 ↓ 0.0 0 1

Nested Loop (cost=0.57..335,369.12 rows=70 width=642) (actual time=376.950..376.950 rows=0 loops=1)

  • Join Filter: (d.publisher_orgref = publisher.swa_org_ref)
6. 0.315 0.315 ↑ 1.0 1,310 1

Seq Scan on orgref publisher (cost=0.00..37.10 rows=1,310 width=26) (actual time=0.001..0.315 rows=1,310 loops=1)

7. 0.111 375.970 ↓ 0.0 0 1,310

Materialize (cost=0.57..333,956.70 rows=70 width=620) (actual time=0.287..0.287 rows=0 loops=1,310)

8. 0.001 375.859 ↓ 0.0 0 1

Nested Loop Left Join (cost=0.57..333,956.35 rows=70 width=620) (actual time=375.859..375.859 rows=0 loops=1)

  • Join Filter: (d.impact_score = ei_lang.impact_score)
9. 0.001 375.858 ↓ 0.0 0 1

Nested Loop (cost=0.57..333,954.23 rows=70 width=402) (actual time=375.858..375.858 rows=0 loops=1)

  • Join Filter: (d.impact_score = ei.impact_score)
10. 375.857 375.857 ↓ 0.0 0 1

Index Scan using idx_entity_agg_repopulate_coords_dates_impact on entity_agg_repopulate d (cost=0.57..333,947.92 rows=70 width=314) (actual time=375.857..375.857 rows=0 loops=1)

  • Index Cond: ((location_point_easting >= 500000) AND (location_point_easting <= 550000) AND (location_point_northing >= 200000) AND (location_point_northing <= 250000) AND (start_date <= to_timestamp('30/11/2018 23:59:59'::text, 'DD/MM/YYYY HH24:MI:SS'::text)) AND (end_date >= to_timestamp('01/11/2018 00:00:00'::text, 'DD/MM/YYYY HH24:MI:SS'::text)))
  • Filter: ((entity_type = 1) AND (COALESCE(responsible_org_organisation_id, 0) = 1440) AND (impact_score = ANY ('{1,2,3,4}'::integer[])))
  • Rows Removed by Filter: 10989
11. 0.000 0.000 ↓ 0.0 0

Materialize (cost=0.00..1.07 rows=5 width=92) (never executed)

12. 0.000 0.000 ↓ 0.0 0

Seq Scan on eton_impact ei (cost=0.00..1.05 rows=5 width=92) (never executed)

13. 0.000 0.000 ↓ 0.0 0

Materialize (cost=0.00..1.07 rows=1 width=222) (never executed)

14. 0.000 0.000 ↓ 0.0 0

Seq Scan on eton_impact_lang ei_lang (cost=0.00..1.06 rows=1 width=222) (never executed)

  • Filter: ((code)::text = 'en'::text)