#	exclusive	inclusive	rows x	rows	loops	node
1.	61.228	4009.842	↑ 1.0	319	1	→ HashAggregate (cost=18092.05..18098.42 rows=319 width=32) (actual time=4009.066..4009.842 rows=319 loops=1) Total runtime: 4010.805 ms
2.	123.088	3948.614	↓ 3.9	16833	1	→ Hash Left Join (cost=180.66..18038.25 rows=4304 width=32) (actual time=185.033..3948.614 rows=16833 loops=1) Hash Cond: (v.appellation_id = a.id)
3.	72.665	3824.137	↓ 3.9	16833	1	→ Hash Join (cost=170.48..17925.85 rows=4304 width=20) (actual time=183.579..3824.137 rows=16833 loops=1) Hash Cond: (s.contenant_id = c.id)
4.	79.521	3751.443	↓ 3.9	16833	1	→ Hash Join (cost=169.42..17865.60 rows=4304 width=20) (actual time=183.529..3751.443 rows=16833 loops=1) Hash Cond: (s.vin_id = v.id)
5.	1881.882	3646.208	↓ 3.9	16833	1	→ Hash Join (cost=0.04..17610.15 rows=4304 width=20) (actual time=157.734..3646.208 rows=16833 loops=1) Hash Cond: ((s.annee)::double precision = ((round((random() * 50::double precision)) + 1950::double precision)))
6.	1764.307	1764.307	↑ 1.0	860871	1	→ Seq Scan on stock s (cost=0.00..13262.71 rows=860871 width=16) (actual time=0.006..1764.307 rows=860871 loops=1)
7.	0.008	0.019	↑ 1.0	1	1	→ Hash (cost=0.03..0.03 rows=1 width=8) (actual time=0.019..0.019 rows=1 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 1kB
8.	0.011	0.011	↑ 1.0	1	1	→ Result (cost=0.00..0.02 rows=1 width=0) (actual time=0.009..0.011 rows=1 loops=1)
9.	12.921	25.714	↑ 1.0	6061	1	→ Hash (cost=93.61..93.61 rows=6061 width=8) (actual time=25.714..25.714 rows=6061 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 190kB
10.	12.793	12.793	↑ 1.0	6061	1	→ Seq Scan on vin v (cost=0.00..93.61 rows=6061 width=8) (actual time=0.015..12.793 rows=6061 loops=1)
11.	0.015	0.029	↑ 1.0	3	1	→ Hash (cost=1.03..1.03 rows=3 width=8) (actual time=0.029..0.029 rows=3 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 1kB
12.	0.014	0.014	↑ 1.0	3	1	→ Seq Scan on contenant c (cost=0.00..1.03 rows=3 width=8) (actual time=0.007..0.014 rows=3 loops=1)
13.	0.708	1.389	↑ 1.0	319	1	→ Hash (cost=6.19..6.19 rows=319 width=20) (actual time=1.389..1.389 rows=319 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 15kB
14.	0.681	0.681	↑ 1.0	319	1	→ Seq Scan on appellation a (cost=0.00..6.19 rows=319 width=20) (actual time=0.012..0.681 rows=319 loops=1)

HashAggregate  (cost=18092.05..18098.42 rows=319 width=32) (actual time=4009.066..4009.842 rows=319 loops=1)
   ->  Hash Left Join  (cost=180.66..18038.25 rows=4304 width=32) (actual time=185.033..3948.614 rows=16833 loops=1)
         Hash Cond: (v.appellation_id = a.id)
         ->  Hash Join  (cost=170.48..17925.85 rows=4304 width=20) (actual time=183.579..3824.137 rows=16833 loops=1)
               Hash Cond: (s.contenant_id = c.id)
               ->  Hash Join  (cost=169.42..17865.60 rows=4304 width=20) (actual time=183.529..3751.443 rows=16833 loops=1)
                     Hash Cond: (s.vin_id = v.id)
                     ->  Hash Join  (cost=0.04..17610.15 rows=4304 width=20) (actual time=157.734..3646.208 rows=16833 loops=1)
                           Hash Cond: ((s.annee)::double precision = ((round((random() * 50::double precision)) + 1950::double precision)))
                           ->  Seq Scan on stock s  (cost=0.00..13262.71 rows=860871 width=16) (actual time=0.006..1764.307 rows=860871 loops=1)
                           ->  Hash  (cost=0.03..0.03 rows=1 width=8) (actual time=0.019..0.019 rows=1 loops=1)
                                 Buckets: 1024  Batches: 1  Memory Usage: 1kB
                                 ->  Result  (cost=0.00..0.02 rows=1 width=0) (actual time=0.009..0.011 rows=1 loops=1)
                     ->  Hash  (cost=93.61..93.61 rows=6061 width=8) (actual time=25.714..25.714 rows=6061 loops=1)
                           Buckets: 1024  Batches: 1  Memory Usage: 190kB
                           ->  Seq Scan on vin v  (cost=0.00..93.61 rows=6061 width=8) (actual time=0.015..12.793 rows=6061 loops=1)
               ->  Hash  (cost=1.03..1.03 rows=3 width=8) (actual time=0.029..0.029 rows=3 loops=1)
                     Buckets: 1024  Batches: 1  Memory Usage: 1kB
                     ->  Seq Scan on contenant c  (cost=0.00..1.03 rows=3 width=8) (actual time=0.007..0.014 rows=3 loops=1)
         ->  Hash  (cost=6.19..6.19 rows=319 width=20) (actual time=1.389..1.389 rows=319 loops=1)
               Buckets: 1024  Batches: 1  Memory Usage: 15kB
               ->  Seq Scan on appellation a  (cost=0.00..6.19 rows=319 width=20) (actual time=0.012..0.681 rows=319 loops=1)
 Total runtime: 4010.805 ms

Per node type stats

node type	count	sum of times	% of query
Hash	4	13.652 ms	0.3 %
Hash Join	3	2034.068 ms	50.7 %
Hash Left Join	1	123.088 ms	3.1 %
HashAggregate	1	61.228 ms	1.5 %
Result	1	0.011 ms	0.0 %
Seq Scan	4	1777.795 ms	44.3 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
appellation	1	0.681 ms	0.0 %
Seq Scan	1	0.681 ms	100.0 %
contenant	1	0.014 ms	0.0 %
Seq Scan	1	0.014 ms	100.0 %
stock	1	1764.307 ms	44.0 %
Seq Scan	1	1764.307 ms	100.0 %
vin	1	12.793 ms	0.3 %
Seq Scan	1	12.793 ms	100.0 %

explain.depesz.com

A tool for finding a real cause for slow queries.

Result: U3M

Colorize:

Columns visibility:

Per node type stats

Per table stats