explain.depesz.com

PostgreSQL's explain analyze made readable

Result: TKY

Settings
# exclusive inclusive rows x rows loops node
1. 1.001 136.567 ↑ 1.0 1,801 1

Limit (cost=107.52..45,125.14 rows=1,801 width=491) (actual time=1.872..136.567 rows=1,801 loops=1)

2. 63.931 135.566 ↑ 7.8 1,801 1

Hash Join (cost=107.52..349,900.21 rows=13,994 width=491) (actual time=1.871..135.566 rows=1,801 loops=1)

  • Hash Cond: (d.publisher_orgref = publisher.swa_org_ref)
3. 4.319 70.785 ↑ 7.8 1,801 1

Nested Loop (cost=54.04..335,415.42 rows=13,994 width=642) (actual time=0.875..70.785 rows=1,801 loops=1)

  • Join Filter: (d.impact_score = ei.impact_score)
  • Rows Removed by Join Filter: 7201
4. 1.938 64.665 ↑ 7.8 1,801 1

Nested Loop Left Join (cost=54.04..334,364.81 rows=13,994 width=554) (actual time=0.869..64.665 rows=1,801 loops=1)

  • Join Filter: (d.impact_score = ei_lang.impact_score)
5. 1.813 62.727 ↑ 7.8 1,801 1

Hash Join (cost=54.04..334,153.83 rows=13,994 width=336) (actual time=0.862..62.727 rows=1,801 loops=1)

  • Hash Cond: (d.responsible_org_orgref = resporg.swa_org_ref)
6. 60.099 60.099 ↑ 7.8 1,801 1

Index Scan using idx_entity_agg_repopulate_coords_dates_impact on entity_agg_repopulate d (cost=0.57..333,907.80 rows=14,031 width=314) (actual time=0.037..60.099 rows=1,801 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 (impact_score = ANY ('{1,2,3,4}'::integer[])))
  • Rows Removed by Filter: 625
7. 0.379 0.815 ↑ 1.0 1,310 1

Hash (cost=37.10..37.10 rows=1,310 width=26) (actual time=0.815..0.815 rows=1,310 loops=1)

  • Buckets: 2048 Batches: 1 Memory Usage: 82kB
8. 0.436 0.436 ↑ 1.0 1,310 1

Seq Scan on orgref resporg (cost=0.00..37.10 rows=1,310 width=26) (actual time=0.002..0.436 rows=1,310 loops=1)

9. 0.000 0.000 ↓ 0.0 0 1,801

Materialize (cost=0.00..1.07 rows=1 width=222) (actual time=0.000..0.000 rows=0 loops=1,801)

10. 0.004 0.004 ↓ 0.0 0 1

Seq Scan on eton_impact_lang ei_lang (cost=0.00..1.06 rows=1 width=222) (actual time=0.004..0.004 rows=0 loops=1)

  • Filter: ((code)::text = 'en'::text)
  • Rows Removed by Filter: 5
11. 1.797 1.801 ↑ 1.0 5 1,801

Materialize (cost=0.00..1.07 rows=5 width=92) (actual time=0.000..0.001 rows=5 loops=1,801)

12. 0.004 0.004 ↑ 1.0 5 1

Seq Scan on eton_impact ei (cost=0.00..1.05 rows=5 width=92) (actual time=0.002..0.004 rows=5 loops=1)

13. 0.400 0.850 ↑ 1.0 1,310 1

Hash (cost=37.10..37.10 rows=1,310 width=26) (actual time=0.850..0.850 rows=1,310 loops=1)

  • Buckets: 2048 Batches: 1 Memory Usage: 82kB
14. 0.450 0.450 ↑ 1.0 1,310 1

Seq Scan on orgref publisher (cost=0.00..37.10 rows=1,310 width=26) (actual time=0.005..0.450 rows=1,310 loops=1)