#	exclusive	inclusive	rows x	rows	loops	node
1.	1,482.716	11,244.811	↓ 46.2	5,218,810	1	→ Hash Join (cost=608,029.86..656,649.41 rows=112,936 width=513) (actual time=7,866.519..11,244.811 rows=5,218,810 loops=1) Hash Cond: (i1_.id_jdd = i2_.id_jdd)
2.	1,895.050	9,748.090	↓ 17.1	400,645	1	→ Hash Join (cost=607,317.69..654,573.42 rows=23,442 width=513) (actual time=7,852.494..9,748.090 rows=400,645 loops=1) Hash Cond: (g.cd_ref = i0_.cd_nom)
3.	0.902	1.110	↑ 1.1	2,563	1	→ Bitmap Heap Scan on vm_requeteur_groupes g (cost=54.51..2,622.39 rows=2,850 width=4) (actual time=0.220..1.110 rows=2,563 loops=1) Recheck Cond: (gid = 12)
4.	0.208	0.208	↑ 1.1	2,563	1	→ Bitmap Index Scan on vm_requeteur_groupes_gid_idx (cost=0.00..53.80 rows=2,850 width=0) (actual time=0.208..0.208 rows=2,563 loops=1) Index Cond: (gid = 12)
5.	542.123	7,851.930	↓ 1.1	436,721	1	→ Hash (cost=575,259.35..575,259.35 rows=405,586 width=517) (actual time=7,851.930..7,851.930 rows=436,721 loops=1) Buckets: 1024 Batches: 8192 (originally 256) Memory Usage: 3483kB
6.	3,723.169	7,309.807	↓ 1.1	436,721	1	→ Hash Join (cost=204,525.88..575,259.35 rows=405,586 width=517) (actual time=1,312.044..7,309.807 rows=436,721 loops=1) Hash Cond: (i0_.id_releve = i1_.rid)
7.	2,289.108	2,289.108	↑ 1.0	4,124,641	1	→ Seq Scan on vm_requeteur_observations i0_ (cost=0.00..187,835.41 rows=4,124,641 width=105) (actual time=0.092..2,289.108 rows=4,124,641 loops=1)
8.	351.700	1,297.530	↑ 1.0	395,935	1	→ Hash (cost=178,309.69..178,309.69 rows=395,935 width=412) (actual time=1,297.530..1,297.530 rows=395,935 loops=1) Buckets: 1024 Batches: 256 Memory Usage: 595kB
9.	945.830	945.830	↑ 1.0	395,935	1	→ Seq Scan on vm_requeteur_releves i1_ (cost=0.00..178,309.69 rows=395,935 width=412) (actual time=0.022..945.830 rows=395,935 loops=1) Filter: ((departement)::text = '33'::text) Rows Removed by Filter: 1688760
10.	2.954	14.005	↓ 1.6	10,386	1	→ Hash (cost=630.51..630.51 rows=6,533 width=4) (actual time=14.005..14.005 rows=10,386 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 366kB
11.	3.272	11.051	↓ 1.6	10,386	1	→ Hash Join (cost=400.50..630.51 rows=6,533 width=4) (actual time=5.252..11.051 rows=10,386 loops=1) Hash Cond: (i2_.id_ca = i3_.id_ca)
12.	1.634	4.777	↑ 1.0	3,279	1	→ Hash Right Join (cost=257.51..405.55 rows=3,328 width=8) (actual time=2.239..4.777 rows=3,279 loops=1) Hash Cond: (i5_.id_jdd = i2_.id_jdd)
13.	0.933	0.933	↑ 1.0	3,279	1	→ Seq Scan on jdd_contact_donnees i5_ (cost=0.00..102.28 rows=3,328 width=4) (actual time=0.008..0.933 rows=3,279 loops=1)
14.	0.715	2.210	↑ 1.1	1,226	1	→ Hash (cost=240.56..240.56 rows=1,356 width=8) (actual time=2.210..2.210 rows=1,226 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 48kB
15.	1.495	1.495	↑ 1.1	1,226	1	→ Seq Scan on jdd i2_ (cost=0.00..240.56 rows=1,356 width=8) (actual time=0.005..1.495 rows=1,226 loops=1)
16.	0.553	3.002	↓ 1.2	1,044	1	→ Hash (cost=131.73..131.73 rows=901 width=4) (actual time=3.002..3.002 rows=1,044 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 37kB
17.	1.229	2.449	↓ 1.2	1,044	1	→ Hash Right Join (cost=83.33..131.73 rows=901 width=4) (actual time=0.655..2.449 rows=1,044 loops=1) Hash Cond: (i4_.id_ca = i3_.id_ca)
18.	0.590	0.590	↓ 1.1	964	1	→ Seq Scan on ca_contact i4_ (cost=0.00..36.01 rows=901 width=4) (actual time=0.009..0.590 rows=964 loops=1)
19.	0.248	0.630	↑ 1.1	409	1	→ Hash (cost=77.59..77.59 rows=459 width=4) (actual time=0.630..0.630 rows=409 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 15kB
20.	0.382	0.382	↑ 1.1	409	1	→ Seq Scan on ca i3_ (cost=0.00..77.59 rows=459 width=4) (actual time=0.010..0.382 rows=409 loops=1)

Total runtime	:	11,914.724 ms

Hash Join  (cost=608029.86..656649.41 rows=112936 width=513) (actual time=7866.519..11244.811 rows=5218810 loops=1)
  Hash Cond: (i1_.id_jdd = i2_.id_jdd)
  ->  Hash Join  (cost=607317.69..654573.42 rows=23442 width=513) (actual time=7852.494..9748.090 rows=400645 loops=1)
        Hash Cond: (g.cd_ref = i0_.cd_nom)
        ->  Bitmap Heap Scan on vm_requeteur_groupes g  (cost=54.51..2622.39 rows=2850 width=4) (actual time=0.220..1.110 rows=2563 loops=1)
              Recheck Cond: (gid = 12)
              ->  Bitmap Index Scan on vm_requeteur_groupes_gid_idx  (cost=0.00..53.80 rows=2850 width=0) (actual time=0.208..0.208 rows=2563 loops=1)
                    Index Cond: (gid = 12)
        ->  Hash  (cost=575259.35..575259.35 rows=405586 width=517) (actual time=7851.930..7851.930 rows=436721 loops=1)
              Buckets: 1024  Batches: 8192 (originally 256)  Memory Usage: 3483kB
              ->  Hash Join  (cost=204525.88..575259.35 rows=405586 width=517) (actual time=1312.044..7309.807 rows=436721 loops=1)
                    Hash Cond: (i0_.id_releve = i1_.rid)
                    ->  Seq Scan on vm_requeteur_observations i0_  (cost=0.00..187835.41 rows=4124641 width=105) (actual time=0.092..2289.108 rows=4124641 loops=1)
                    ->  Hash  (cost=178309.69..178309.69 rows=395935 width=412) (actual time=1297.530..1297.530 rows=395935 loops=1)
                          Buckets: 1024  Batches: 256  Memory Usage: 595kB
                          ->  Seq Scan on vm_requeteur_releves i1_  (cost=0.00..178309.69 rows=395935 width=412) (actual time=0.022..945.830 rows=395935 loops=1)
                                Filter: ((departement)::text = '33'::text)
                                Rows Removed by Filter: 1688760
  ->  Hash  (cost=630.51..630.51 rows=6533 width=4) (actual time=14.005..14.005 rows=10386 loops=1)
        Buckets: 1024  Batches: 1  Memory Usage: 366kB
        ->  Hash Join  (cost=400.50..630.51 rows=6533 width=4) (actual time=5.252..11.051 rows=10386 loops=1)
              Hash Cond: (i2_.id_ca = i3_.id_ca)
              ->  Hash Right Join  (cost=257.51..405.55 rows=3328 width=8) (actual time=2.239..4.777 rows=3279 loops=1)
                    Hash Cond: (i5_.id_jdd = i2_.id_jdd)
                    ->  Seq Scan on jdd_contact_donnees i5_  (cost=0.00..102.28 rows=3328 width=4) (actual time=0.008..0.933 rows=3279 loops=1)
                    ->  Hash  (cost=240.56..240.56 rows=1356 width=8) (actual time=2.210..2.210 rows=1226 loops=1)
                          Buckets: 1024  Batches: 1  Memory Usage: 48kB
                          ->  Seq Scan on jdd i2_  (cost=0.00..240.56 rows=1356 width=8) (actual time=0.005..1.495 rows=1226 loops=1)
              ->  Hash  (cost=131.73..131.73 rows=901 width=4) (actual time=3.002..3.002 rows=1044 loops=1)
                    Buckets: 1024  Batches: 1  Memory Usage: 37kB
                    ->  Hash Right Join  (cost=83.33..131.73 rows=901 width=4) (actual time=0.655..2.449 rows=1044 loops=1)
                          Hash Cond: (i4_.id_ca = i3_.id_ca)
                          ->  Seq Scan on ca_contact i4_  (cost=0.00..36.01 rows=901 width=4) (actual time=0.009..0.590 rows=964 loops=1)
                          ->  Hash  (cost=77.59..77.59 rows=459 width=4) (actual time=0.630..0.630 rows=409 loops=1)
                                Buckets: 1024  Batches: 1  Memory Usage: 15kB
                                ->  Seq Scan on ca i3_  (cost=0.00..77.59 rows=459 width=4) (actual time=0.010..0.382 rows=409 loops=1)
Total runtime: 11914.724 ms

Per node type stats

node type	count	sum of times	% of query
Bitmap Heap Scan	1	0.902 ms	0.0 %
Bitmap Index Scan	1	0.208 ms	0.0 %
Hash	6	898.293 ms	8.0 %
Hash Join	4	7,104.207 ms	63.2 %
Hash Right Join	2	2.863 ms	0.0 %
Seq Scan	6	3,238.338 ms	28.8 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
ca	1	0.382 ms	0.0 %
Seq Scan	1	0.382 ms	100.0 %
ca_contact	1	0.590 ms	0.0 %
Seq Scan	1	0.590 ms	100.0 %
jdd	1	1.495 ms	0.0 %
Seq Scan	1	1.495 ms	100.0 %
jdd_contact_donnees	1	0.933 ms	0.0 %
Seq Scan	1	0.933 ms	100.0 %
vm_requeteur_groupes	1	0.902 ms	0.0 %
Bitmap Heap Scan	1	0.902 ms	100.0 %
vm_requeteur_observations	1	2,289.108 ms	20.4 %
Seq Scan	1	2,289.108 ms	100.0 %
vm_requeteur_releves	1	945.830 ms	8.4 %
Seq Scan	1	945.830 ms	100.0 %

explain.depesz.com

PostgreSQL's explain analyze made readable

Result: VUKX : Optimization for: Optimization for: plan #CgMh; plan #z7W4

Color mode:

Visible columns:

Optimization path:

Per node type stats

Per table stats