#	exclusive	inclusive	rows x	rows	loops	node
1.	70.245	11726.554	↓ 2.5	319	1	→ HashAggregate (cost=33192.68..33195.20 rows=126 width=32) (actual time=11725.796..11726.554 rows=319 loops=1)
2.	271.649	11656.309	↓ 133.3	16795	1	→ Nested Loop Left Join (cost=1.07..33191.10 rows=126 width=32) (actual time=1281.582..11656.309 rows=16795 loops=1)
3.	220.945	11267.095	↓ 133.3	16795	1	→ Nested Loop (cost=1.07..33154.19 rows=126 width=20) (actual time=1281.519..11267.095 rows=16795 loops=1)
4.	1946.904	10911.790	↓ 133.3	16795	1	→ Nested Loop (cost=1.07..33118.81 rows=126 width=20) (actual time=1281.484..10911.790 rows=16795 loops=1) Join Filter: ((s.annee)::double precision = ((round((random() * 50::double precision)) + 1950::double precision)))
5.	0.020	0.020	↑ 1.0	1	1	→ Result (cost=0.00..0.02 rows=1 width=0) (actual time=0.017..0.020 rows=1 loops=1)
6.	3765.569	8964.866	↓ 34.1	860874	1	→ Hash Join (cost=1.07..32739.58 rows=25280 width=16) (actual time=6.718..8964.866 rows=860874 loops=1) Hash Cond: (s.contenant_id = c.id)
7.	3291.492	5199.266	↑ 2.0	860874	1	→ Append (cost=0.00..26165.61 rows=1685361 width=16) (actual time=6.594..5199.266 rows=860874 loops=1)
8.	6.594	6.594	↑ 287142.0	3	1	→ Seq Scan on stock s (cost=0.00..13271.26 rows=861426 width=16) (actual time=6.588..6.594 rows=3 loops=1)
9.	382.134	382.134	↓ 1.0	169085	1	→ Seq Scan on stock_1950 s (cost=0.00..2531.78 rows=161778 width=16) (actual time=0.011..382.134 rows=169085 loops=1)
10.	361.539	361.539	↓ 1.0	168524	1	→ Seq Scan on stock_1960 s (cost=0.00..2523.47 rows=161247 width=16) (actual time=0.012..361.539 rows=168524 loops=1)
11.	373.675	373.675	↓ 1.0	168487	1	→ Seq Scan on stock_1970 s (cost=0.00..2523.47 rows=161247 width=16) (actual time=0.014..373.675 rows=168487 loops=1)
12.	374.972	374.972	↓ 1.0	168789	1	→ Seq Scan on stock_1980 s (cost=0.00..2529.01 rows=161601 width=16) (actual time=0.010..374.972 rows=168789 loops=1)
13.	367.025	367.025	↓ 1.0	168497	1	→ Seq Scan on stock_1990 s (cost=0.00..2523.47 rows=161247 width=16) (actual time=0.010..367.025 rows=168497 loops=1)
14.	41.835	41.835	↓ 1.0	17489	1	→ Seq Scan on stock_2000 s (cost=0.00..263.15 rows=16815 width=16) (actual time=0.010..41.835 rows=17489 loops=1)
15.	0.018	0.031	↑ 1.0	3	1	→ Hash (cost=1.03..1.03 rows=3 width=8) (actual time=0.031..0.031 rows=3 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 1kB
16.	0.013	0.013	↑ 1.0	3	1	→ Seq Scan on contenant c (cost=0.00..1.03 rows=3 width=8) (actual time=0.006..0.013 rows=3 loops=1)
17.	134.360	134.360	↑ 1.0	1	16795	→ Index Scan using vin_pkey on vin v (cost=0.00..0.27 rows=1 width=8) (actual time=0.006..0.008 rows=1 loops=16795) Index Cond: (id = s.vin_id)
18.	117.565	117.565	↑ 1.0	1	16795	→ Index Scan using appellation_pkey on appellation a (cost=0.00..0.27 rows=1 width=20) (actual time=0.004..0.007 rows=1 loops=16795) Index Cond: (v.appellation_id = id)

                                                                        QUERY PLAN                                                                        
----------------------------------------------------------------------------------------------------------------------------------------------------------
 HashAggregate  (cost=33192.68..33195.20 rows=126 width=32) (actual time=11725.796..11726.554 rows=319 loops=1)
   ->  Nested Loop Left Join  (cost=1.07..33191.10 rows=126 width=32) (actual time=1281.582..11656.309 rows=16795 loops=1)
         ->  Nested Loop  (cost=1.07..33154.19 rows=126 width=20) (actual time=1281.519..11267.095 rows=16795 loops=1)
               ->  Nested Loop  (cost=1.07..33118.81 rows=126 width=20) (actual time=1281.484..10911.790 rows=16795 loops=1)
                     Join Filter: ((s.annee)::double precision = ((round((random() * 50::double precision)) + 1950::double precision)))
                     ->  Result  (cost=0.00..0.02 rows=1 width=0) (actual time=0.017..0.020 rows=1 loops=1)
                     ->  Hash Join  (cost=1.07..32739.58 rows=25280 width=16) (actual time=6.718..8964.866 rows=860874 loops=1)
                           Hash Cond: (s.contenant_id = c.id)
                           ->  Append  (cost=0.00..26165.61 rows=1685361 width=16) (actual time=6.594..5199.266 rows=860874 loops=1)
                                 ->  Seq Scan on stock s  (cost=0.00..13271.26 rows=861426 width=16) (actual time=6.588..6.594 rows=3 loops=1)
                                 ->  Seq Scan on stock_1950 s  (cost=0.00..2531.78 rows=161778 width=16) (actual time=0.011..382.134 rows=169085 loops=1)
                                 ->  Seq Scan on stock_1960 s  (cost=0.00..2523.47 rows=161247 width=16) (actual time=0.012..361.539 rows=168524 loops=1)
                                 ->  Seq Scan on stock_1970 s  (cost=0.00..2523.47 rows=161247 width=16) (actual time=0.014..373.675 rows=168487 loops=1)
                                 ->  Seq Scan on stock_1980 s  (cost=0.00..2529.01 rows=161601 width=16) (actual time=0.010..374.972 rows=168789 loops=1)
                                 ->  Seq Scan on stock_1990 s  (cost=0.00..2523.47 rows=161247 width=16) (actual time=0.010..367.025 rows=168497 loops=1)
                                 ->  Seq Scan on stock_2000 s  (cost=0.00..263.15 rows=16815 width=16) (actual time=0.010..41.835 rows=17489 loops=1)
                           ->  Hash  (cost=1.03..1.03 rows=3 width=8) (actual time=0.031..0.031 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=0.006..0.013 rows=3 loops=1)
               ->  Index Scan using vin_pkey on vin v  (cost=0.00..0.27 rows=1 width=8) (actual time=0.006..0.008 rows=1 loops=16795)
                     Index Cond: (id = s.vin_id)
         ->  Index Scan using appellation_pkey on appellation a  (cost=0.00..0.27 rows=1 width=20) (actual time=0.004..0.007 rows=1 loops=16795)
               Index Cond: (v.appellation_id = id)
 Total runtime: 11727.420 ms
(24 lignes)

Per node type stats

node type	count	sum of times	% of query
Append	1	3291.492 ms	28.1 %
Hash	1	0.018 ms	0.0 %
Hash Join	1	3765.569 ms	32.1 %
HashAggregate	1	70.245 ms	0.6 %
Index Scan	2	251.925 ms	2.1 %
Nested Loop	2	2167.849 ms	18.5 %
Nested Loop Left Join	1	271.649 ms	2.3 %
Result	1	0.020 ms	0.0 %
Seq Scan	8	1907.787 ms	16.3 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
appellation	1	117.565 ms	1.0 %
Index Scan	1	117.565 ms	100.0 %
contenant	1	0.013 ms	0.0 %
Seq Scan	1	0.013 ms	100.0 %
stock	1	6.594 ms	0.1 %
Seq Scan	1	6.594 ms	100.0 %
stock_1950	1	382.134 ms	3.3 %
Seq Scan	1	382.134 ms	100.0 %
stock_1960	1	361.539 ms	3.1 %
Seq Scan	1	361.539 ms	100.0 %
stock_1970	1	373.675 ms	3.2 %
Seq Scan	1	373.675 ms	100.0 %
stock_1980	1	374.972 ms	3.2 %
Seq Scan	1	374.972 ms	100.0 %
stock_1990	1	367.025 ms	3.1 %
Seq Scan	1	367.025 ms	100.0 %
stock_2000	1	41.835 ms	0.4 %
Seq Scan	1	41.835 ms	100.0 %
vin	1	134.360 ms	1.1 %
Index Scan	1	134.360 ms	100.0 %

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Per node type stats

Per table stats