#	exclusive	inclusive	rows x	rows	loops	node
1.	0.013	449.571	↓ 0.0	0	1	→ Hash Join (cost=12854.09..15162.43 rows=40228 width=16) (actual time=449.571..449.571 rows=0 loops=1) Hash Cond: (artist.id = t.artist_id)
2.	0.013	0.013	↑ 80456.0	1	1	→ Seq Scan on artist (cost=0.00..1994.56 rows=80456 width=20) (actual time=0.013..0.013 rows=1 loops=1)
3.	0.001	449.545	↓ 0.0	0	1	→ Hash (cost=12839.01..12839.01 rows=1207 width=4) (actual time=449.545..449.545 rows=0 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 0kB
4.	0.028	449.544	↓ 0.0	0	1	→ HashAggregate (cost=12814.87..12826.94 rows=1207 width=4) (actual time=449.544..449.544 rows=0 loops=1)
5.	57.678	449.516	↓ 0.0	0	1	→ Hash Anti Join (cost=9522.09..12811.85 rows=1207 width=4) (actual time=449.516..449.516 rows=0 loops=1) Hash Cond: (t.artist_id = att.artist_id)
6.	26.711	252.126	↑ 16.6	371	1	→ Hash Join (cost=5799.03..8537.96 rows=6154 width=4) (actual time=197.017..252.126 rows=371 loops=1) Hash Cond: (mf.track_id = t.id)
7.	32.179	32.179	↑ 1.0	53093	1	→ Seq Scan on musicfile mf (cost=0.00..2411.93 rows=53093 width=4) (actual time=0.052..32.179 rows=53093 loops=1)
8.	2.286	193.236	↑ 3.7	4541	1	→ Hash (cost=5589.36..5589.36 rows=16773 width=8) (actual time=193.236..193.236 rows=4541 loops=1) Buckets: 2048 Batches: 1 Memory Usage: 178kB
9.	78.364	190.950	↑ 3.7	4541	1	→ Hash Anti Join (cost=363.01..5589.36 rows=16773 width=8) (actual time=41.597..190.950 rows=4541 loops=1) Hash Cond: (t.artist_id = webservice_history.artist_id)
10.	75.574	75.574	↓ 1.0	145690	1	→ Seq Scan on track t (cost=0.00..3891.02 rows=144702 width=8) (actual time=0.027..75.574 rows=145690 loops=1)
11.	2.699	37.012	↓ 1.0	2956	1	→ Hash (cost=326.21..326.21 rows=2944 width=4) (actual time=37.012..37.012 rows=2956 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 104kB
12.	34.313	34.313	↓ 1.0	2956	1	→ Seq Scan on webservice_history (cost=0.00..326.21 rows=2944 width=4) (actual time=16.478..34.313 rows=2956 loops=1) Filter: (calltype_id = 2)
13.	83.001	139.712	↓ 1.0	113460	1	→ Hash (cost=1868.25..1868.25 rows=113025 width=4) (actual time=139.712..139.712 rows=113460 loops=1) Buckets: 4096 Batches: 8 Memory Usage: 521kB
14.	56.711	56.711	↓ 1.0	113460	1	→ Seq Scan on artisttoptrack att (cost=0.00..1868.25 rows=113025 width=4) (actual time=0.044..56.711 rows=113460 loops=1)

                                                                              QUERY PLAN                                                                              
----------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Hash Join  (cost=12854.09..15162.43 rows=40228 width=16) (actual time=449.571..449.571 rows=0 loops=1)
   Hash Cond: (artist.id = t.artist_id)
   ->  Seq Scan on artist  (cost=0.00..1994.56 rows=80456 width=20) (actual time=0.013..0.013 rows=1 loops=1)
   ->  Hash  (cost=12839.01..12839.01 rows=1207 width=4) (actual time=449.545..449.545 rows=0 loops=1)
         Buckets: 1024  Batches: 1  Memory Usage: 0kB
         ->  HashAggregate  (cost=12814.87..12826.94 rows=1207 width=4) (actual time=449.544..449.544 rows=0 loops=1)
               ->  Hash Anti Join  (cost=9522.09..12811.85 rows=1207 width=4) (actual time=449.516..449.516 rows=0 loops=1)
                     Hash Cond: (t.artist_id = att.artist_id)
                     ->  Hash Join  (cost=5799.03..8537.96 rows=6154 width=4) (actual time=197.017..252.126 rows=371 loops=1)
                           Hash Cond: (mf.track_id = t.id)
                           ->  Seq Scan on musicfile mf  (cost=0.00..2411.93 rows=53093 width=4) (actual time=0.052..32.179 rows=53093 loops=1)
                           ->  Hash  (cost=5589.36..5589.36 rows=16773 width=8) (actual time=193.236..193.236 rows=4541 loops=1)
                                 Buckets: 2048  Batches: 1  Memory Usage: 178kB
                                 ->  Hash Anti Join  (cost=363.01..5589.36 rows=16773 width=8) (actual time=41.597..190.950 rows=4541 loops=1)
                                       Hash Cond: (t.artist_id = webservice_history.artist_id)
                                       ->  Seq Scan on track t  (cost=0.00..3891.02 rows=144702 width=8) (actual time=0.027..75.574 rows=145690 loops=1)
                                       ->  Hash  (cost=326.21..326.21 rows=2944 width=4) (actual time=37.012..37.012 rows=2956 loops=1)
                                             Buckets: 1024  Batches: 1  Memory Usage: 104kB
                                             ->  Seq Scan on webservice_history  (cost=0.00..326.21 rows=2944 width=4) (actual time=16.478..34.313 rows=2956 loops=1)
                                                   Filter: (calltype_id = 2)
                     ->  Hash  (cost=1868.25..1868.25 rows=113025 width=4) (actual time=139.712..139.712 rows=113460 loops=1)
                           Buckets: 4096  Batches: 8  Memory Usage: 521kB
                           ->  Seq Scan on artisttoptrack att  (cost=0.00..1868.25 rows=113025 width=4) (actual time=0.044..56.711 rows=113460 loops=1)
 Total runtime: 450.323 ms
(24 rows)

Per node type stats

node type	count	sum of times	% of query
Hash	4	87.987 ms	19.6 %
Hash Anti Join	2	136.042 ms	30.3 %
Hash Join	2	26.724 ms	5.9 %
HashAggregate	1	0.028 ms	0.0 %
Seq Scan	5	198.790 ms	44.2 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
artist	1	0.013 ms	0.0 %
Seq Scan	1	0.013 ms	100.0 %
artisttoptrack	1	56.711 ms	12.6 %
Seq Scan	1	56.711 ms	100.0 %
musicfile	1	32.179 ms	7.2 %
Seq Scan	1	32.179 ms	100.0 %
track	1	75.574 ms	16.8 %
Seq Scan	1	75.574 ms	100.0 %
webservice_history	1	34.313 ms	7.6 %
Seq Scan	1	34.313 ms	100.0 %

explain.depesz.com

A tool for finding a real cause for slow queries.

Result: Ns6

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Per node type stats

Per table stats