explain.depesz.com

PostgreSQL's explain analyze made readable

Result: ziKn

Settings
# exclusive inclusive rows x rows loops node
1. 0.002 126.280 ↓ 2.0 2 1

Limit (cost=1,138.59..1,138.59 rows=1 width=9,396) (actual time=126.279..126.280 rows=2 loops=1)

2. 0.043 126.278 ↓ 2.0 2 1

Sort (cost=1,138.59..1,138.59 rows=1 width=9,396) (actual time=126.278..126.278 rows=2 loops=1)

  • Sort Key: liste_polys.liste_polygones
  • Sort Method: quicksort Memory: 28kB
3. 0.262 126.235 ↓ 2.0 2 1

Nested Loop Left Join (cost=744.00..1,138.58 rows=1 width=9,396) (actual time=122.644..126.235 rows=2 loops=1)

  • Join Filter: _st_within(points_gps.geom, polygones.geom)
4. 0.004 125.619 ↓ 2.0 2 1

Nested Loop (cost=744.00..1,137.72 rows=1 width=9,265) (actual time=122.285..125.619 rows=2 loops=1)

5. 0.013 125.605 ↓ 2.0 2 1

Nested Loop (cost=744.00..1,137.44 rows=1 width=8,741) (actual time=122.275..125.605 rows=2 loops=1)

6. 0.008 125.564 ↓ 2.0 2 1

Nested Loop (cost=739.70..1,129.12 rows=1 width=8,392) (actual time=122.248..125.564 rows=2 loops=1)

7. 0.030 125.542 ↓ 2.0 2 1

Hash Join (cost=739.70..1,127.91 rows=1 width=504) (actual time=122.233..125.542 rows=2 loops=1)

  • Hash Cond: (points.id_point_gps = liste_polys.id_point_gps)
8. 3.428 3.428 ↑ 6.5 2 1

Seq Scan on points (cost=0.00..387.73 rows=13 width=468) (actual time=0.122..3.428 rows=2 loops=1)

  • Filter: (((nom)::text ~~* '%alpette%'::text) AND (modele <> 1) AND (id_point_type <> 26) AND ((ferme)::text = ''::text) AND (id_point_type = ANY ('{7,9,10}'::integer[])))
9. 0.577 122.084 ↓ 9.3 2,507 1

Hash (cost=736.34..736.34 rows=269 width=36) (actual time=122.084..122.084 rows=2,507 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 118kB
10. 0.246 121.507 ↓ 9.3 2,507 1

Subquery Scan on liste_polys (cost=726.92..736.34 rows=269 width=36) (actual time=114.035..121.507 rows=2,507 loops=1)

11. 6.707 121.261 ↓ 9.3 2,507 1

GroupAggregate (cost=726.92..733.65 rows=269 width=12) (actual time=114.034..121.261 rows=2,507 loops=1)

12. 5.155 114.554 ↓ 27.2 7,306 1

Sort (cost=726.92..727.60 rows=269 width=12) (actual time=113.997..114.554 rows=7,306 loops=1)

  • Sort Key: pgps.id_point_gps
  • Sort Method: quicksort Memory: 535kB
13. 86.845 109.399 ↓ 27.2 7,306 1

Nested Loop (cost=9.27..716.07 rows=269 width=12) (actual time=0.119..109.399 rows=7,306 loops=1)

  • Join Filter: _st_within(pgps.geom, pg.geom)
14. 0.139 1.538 ↓ 4.3 568 1

Nested Loop (cost=9.27..188.31 rows=132 width=242,308) (actual time=0.057..1.538 rows=568 loops=1)

15. 0.011 0.011 ↓ 4.0 4 1

Seq Scan on polygone_type pty (cost=0.00..1.10 rows=1 width=8) (actual time=0.007..0.011 rows=4 loops=1)

  • Filter: ((categorie_polygone_type)::text = 'montagnarde'::text)
16. 1.244 1.388 ↓ 1.1 142 4

Bitmap Heap Scan on polygones pg (cost=9.27..185.56 rows=132 width=242,308) (actual time=0.048..0.347 rows=142 loops=4)

  • Recheck Cond: (id_polygone_type = pty.id_polygone_type)
17. 0.144 0.144 ↓ 1.1 142 4

Bitmap Index Scan on polygones_id_polygone_type (cost=0.00..9.24 rows=132 width=0) (actual time=0.036..0.036 rows=142 loops=4)

  • Index Cond: (id_polygone_type = pty.id_polygone_type)
18. 21.016 21.016 ↓ 19.0 19 568

Index Scan using points_gps_geom on points_gps pgps (cost=0.00..3.74 rows=1 width=104) (actual time=0.016..0.037 rows=19 loops=568)

  • Index Cond: (geom && pg.geom)
19. 0.014 0.014 ↑ 1.0 1 2

Index Scan using point_type_id_point_type_pkey on point_type (cost=0.00..1.19 rows=1 width=7,888) (actual time=0.007..0.007 rows=1 loops=2)

  • Index Cond: (id_point_type = points.id_point_type)
20. 0.006 0.028 ↑ 1.0 1 2

Bitmap Heap Scan on points_gps (cost=4.30..8.31 rows=1 width=353) (actual time=0.014..0.014 rows=1 loops=2)

  • Recheck Cond: (id_point_gps = points.id_point_gps)
21. 0.022 0.022 ↑ 1.0 1 2

Bitmap Index Scan on points_gps_id_point_gps_pkey (cost=0.00..4.30 rows=1 width=0) (actual time=0.011..0.011 rows=1 loops=2)

  • Index Cond: (id_point_gps = points.id_point_gps)
22. 0.010 0.010 ↑ 1.0 1 2

Index Scan using type_precision_gps_id_type_precision_gps_pkey on type_precision_gps (cost=0.00..0.27 rows=1 width=524) (actual time=0.004..0.005 rows=1 loops=2)

  • Index Cond: (id_type_precision_gps = points_gps.id_type_precision_gps)
23. 0.354 0.354 ↓ 2.0 2 2

Index Scan using polygones_geom on polygones (cost=0.00..0.58 rows=1 width=242,431) (actual time=0.123..0.177 rows=2 loops=2)

  • Index Cond: (points_gps.geom && geom)
  • Filter: (id_polygone_type = 1)
Total runtime : 127.004 ms