#	exclusive	inclusive	rows x	rows	loops	node
1.	57.656	3940.063	↑ 1.0	319	1	→ HashAggregate (cost=22745.56..22751.94 rows=319 width=32) (actual time=3939.293..3940.063 rows=319 loops=1)
2.	120.262	3882.407	↓ 3.9	16879	1	→ Hash Left Join (cost=180.66..22691.86 rows=4296 width=32) (actual time=287.259..3882.407 rows=16879 loops=1) Hash Cond: (v.appellation_id = a.id)
3.	68.765	3760.781	↓ 3.9	16879	1	→ Hash Join (cost=170.48..22579.66 rows=4296 width=20) (actual time=285.838..3760.781 rows=16879 loops=1) Hash Cond: (s.contenant_id = c.id)
4.	74.559	3691.987	↓ 3.9	16879	1	→ Hash Join (cost=169.42..22519.52 rows=4296 width=20) (actual time=285.783..3691.987 rows=16879 loops=1) Hash Cond: (s.vin_id = v.id)
5.	1845.824	3592.057	↓ 3.9	16879	1	→ Hash Join (cost=0.04..22264.15 rows=4304 width=20) (actual time=260.339..3592.057 rows=16879 loops=1) Hash Cond: ((s.annee)::double precision = ((round((random() * 50::double precision)) + 1950::double precision)))
6.	1746.201	1746.201	↑ 1.0	860871	1	→ Seq Scan on stock s (cost=0.00..17916.71 rows=860871 width=16) (actual time=52.281..1746.201 rows=860871 loops=1)
7.	0.014	0.032	↑ 1.0	1	1	→ Hash (cost=0.03..0.03 rows=1 width=8) (actual time=0.032..0.032 rows=1 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 1kB
8.	0.018	0.018	↑ 1.0	1	1	→ Result (cost=0.00..0.02 rows=1 width=0) (actual time=0.016..0.018 rows=1 loops=1)
9.	12.722	25.371	↑ 1.0	6061	1	→ Hash (cost=93.61..93.61 rows=6061 width=8) (actual time=25.371..25.371 rows=6061 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 190kB
10.	12.649	12.649	↑ 1.0	6061	1	→ Seq Scan on vin v (cost=0.00..93.61 rows=6061 width=8) (actual time=0.012..12.649 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.	0.696	1.364	↑ 1.0	319	1	→ Hash (cost=6.19..6.19 rows=319 width=20) (actual time=1.364..1.364 rows=319 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 15kB
14.	0.668	0.668	↑ 1.0	319	1	→ Seq Scan on appellation a (cost=0.00..6.19 rows=319 width=20) (actual time=0.011..0.668 rows=319 loops=1)

                                                                     QUERY PLAN                                                                    
--------------------------------------------------------------------------------------------------------------------------------------------------
 HashAggregate  (cost=22745.56..22751.94 rows=319 width=32) (actual time=3939.293..3940.063 rows=319 loops=1)
   ->  Hash Left Join  (cost=180.66..22691.86 rows=4296 width=32) (actual time=287.259..3882.407 rows=16879 loops=1)
         Hash Cond: (v.appellation_id = a.id)
         ->  Hash Join  (cost=170.48..22579.66 rows=4296 width=20) (actual time=285.838..3760.781 rows=16879 loops=1)
               Hash Cond: (s.contenant_id = c.id)
               ->  Hash Join  (cost=169.42..22519.52 rows=4296 width=20) (actual time=285.783..3691.987 rows=16879 loops=1)
                     Hash Cond: (s.vin_id = v.id)
                     ->  Hash Join  (cost=0.04..22264.15 rows=4304 width=20) (actual time=260.339..3592.057 rows=16879 loops=1)
                           Hash Cond: ((s.annee)::double precision = ((round((random() * 50::double precision)) + 1950::double precision)))
                           ->  Seq Scan on stock s  (cost=0.00..17916.71 rows=860871 width=16) (actual time=52.281..1746.201 rows=860871 loops=1)
                           ->  Hash  (cost=0.03..0.03 rows=1 width=8) (actual time=0.032..0.032 rows=1 loops=1)
                                 Buckets: 1024  Batches: 1  Memory Usage: 1kB
                                 ->  Result  (cost=0.00..0.02 rows=1 width=0) (actual time=0.016..0.018 rows=1 loops=1)
                     ->  Hash  (cost=93.61..93.61 rows=6061 width=8) (actual time=25.371..25.371 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=0.012..12.649 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=1.364..1.364 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=0.011..0.668 rows=319 loops=1)
 Total runtime: 3940.854 ms
(23 lignes)

Per node type stats

node type	count	sum of times	% of query
Hash	4	13.447 ms	0.3 %
Hash Join	3	1989.148 ms	50.5 %
Hash Left Join	1	120.262 ms	3.1 %
HashAggregate	1	57.656 ms	1.5 %
Result	1	0.018 ms	0.0 %
Seq Scan	4	1759.532 ms	44.7 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
appellation	1	0.668 ms	0.0 %
Seq Scan	1	0.668 ms	100.0 %
contenant	1	0.014 ms	0.0 %
Seq Scan	1	0.014 ms	100.0 %
stock	1	1746.201 ms	44.3 %
Seq Scan	1	1746.201 ms	100.0 %
vin	1	12.649 ms	0.3 %
Seq Scan	1	12.649 ms	100.0 %

explain.depesz.com

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Per table stats