#	exclusive	inclusive	rows x	rows	loops	node
1.	5.321	405.255	↓ 1.2	5210	1	→ Hash Join (cost=23386.15..27357.28 rows=4202 width=163) (actual time=375.680..405.255 rows=5210 loops=1) Hash Cond: (ek.keyword_id = k.id)
2.	2.215	382.699	↓ 1.2	5210	1	→ Nested Loop (cost=22674.55..26566.89 rows=4202 width=129) (actual time=358.431..382.699 rows=5210 loops=1)
3.	0.958	374.904	↓ 1.4	1116	1	→ Hash Left Join (cost=22674.55..25036.08 rows=787 width=125) (actual time=358.420..374.904 rows=1116 loops=1) Hash Cond: (e.id = e.id)
4.	15.732	15.732	↓ 1.4	1116	1	→ Seq Scan on events e (cost=0.00..2281.75 rows=787 width=121) (actual time=0.188..15.732 rows=1116 loops=1) Filter: display
5.	0.302	358.214	↓ 1.3	1028	1	→ Hash (cost=22664.72..22664.72 rows=787 width=4) (actual time=358.214..358.214 rows=1028 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 37kB
6.	16.489	357.912	↓ 1.3	1028	1	→ HashAggregate (cost=22648.98..22656.85 rows=787 width=4) (actual time=357.628..357.912 rows=1028 loops=1)
7.	34.257	341.423	↓ 1.8	44843	1	→ Nested Loop (cost=0.00..22586.18 rows=25120 width=4) (actual time=0.198..341.423 rows=44843 loops=1)
8.	19.860	122.849	↓ 2.0	61439	1	→ Nested Loop (cost=0.00..11754.45 rows=30776 width=8) (actual time=0.189..122.849 rows=61439 loops=1)
9.	4.466	32.089	↓ 1.6	14180	1	→ Nested Loop (cost=0.00..4926.33 rows=8830 width=8) (actual time=0.180..32.089 rows=14180 loops=1)
10.	16.463	16.463	↓ 1.4	1116	1	→ Seq Scan on events e (cost=0.00..2281.75 rows=787 width=4) (actual time=0.166..16.463 rows=1116 loops=1) Filter: display
11.	11.160	11.160	↑ 1.7	13	1116	→ Index Scan using markets_event_id_index on markets m (cost=0.00..3.09 rows=22 width=8) (actual time=0.004..0.010 rows=13 loops=1116) Index Cond: (event_id = e.id)
12.	70.900	70.900	↑ 3.2	4	14180	→ Index Scan using outcomes_market_id_index on outcomes o (cost=0.00..0.61 rows=13 width=8) (actual time=0.003..0.005 rows=4 loops=14180) Index Cond: (market_id = m.id)
13.	184.317	184.317	↑ 1.0	1	61439	→ Index Scan using prices_outcome_id_key on prices p (cost=0.00..0.34 rows=1 width=4) (actual time=0.003..0.003 rows=1 loops=61439) Index Cond: (outcome_id = o.id)
14.	5.580	5.580	↑ 1.0	5	1116	→ Index Scan using events_keywords_event_id_idx on events_keywords ek (cost=0.00..1.88 rows=5 width=8) (actual time=0.003..0.005 rows=5 loops=1116) Index Cond: (event_id = e.id)
15.	10.869	17.235	↑ 1.0	20934	1	→ Hash (cost=439.60..439.60 rows=21760 width=42) (actual time=17.235..17.235 rows=20934 loops=1) Buckets: 4096 Batches: 1 Memory Usage: 1577kB
16.	6.366	6.366	↑ 1.0	20934	1	→ Seq Scan on keywords k (cost=0.00..439.60 rows=21760 width=42) (actual time=0.008..6.366 rows=20934 loops=1)

 Hash Join  (cost=23386.15..27357.28 rows=4202 width=163) (actual time=375.680..405.255 rows=5210 loops=1)
   Hash Cond: (ek.keyword_id = k.id)
   ->  Nested Loop  (cost=22674.55..26566.89 rows=4202 width=129) (actual time=358.431..382.699 rows=5210 loops=1)
         ->  Hash Left Join  (cost=22674.55..25036.08 rows=787 width=125) (actual time=358.420..374.904 rows=1116 loops=1)
               Hash Cond: (e.id = e.id)
               ->  Seq Scan on events e  (cost=0.00..2281.75 rows=787 width=121) (actual time=0.188..15.732 rows=1116 loops=1)
                     Filter: display
               ->  Hash  (cost=22664.72..22664.72 rows=787 width=4) (actual time=358.214..358.214 rows=1028 loops=1)
                     Buckets: 1024  Batches: 1  Memory Usage: 37kB
                     ->  HashAggregate  (cost=22648.98..22656.85 rows=787 width=4) (actual time=357.628..357.912 rows=1028 loops=1)
                           ->  Nested Loop  (cost=0.00..22586.18 rows=25120 width=4) (actual time=0.198..341.423 rows=44843 loops=1)
                                 ->  Nested Loop  (cost=0.00..11754.45 rows=30776 width=8) (actual time=0.189..122.849 rows=61439 loops=1)
                                       ->  Nested Loop  (cost=0.00..4926.33 rows=8830 width=8) (actual time=0.180..32.089 rows=14180 loops=1)
                                             ->  Seq Scan on events e  (cost=0.00..2281.75 rows=787 width=4) (actual time=0.166..16.463 rows=1116 loops=1)
                                                   Filter: display
                                             ->  Index Scan using markets_event_id_index on markets m  (cost=0.00..3.09 rows=22 width=8) (actual time=0.004..0.010 rows=13 loops=1116)
                                                   Index Cond: (event_id = e.id)
                                       ->  Index Scan using outcomes_market_id_index on outcomes o  (cost=0.00..0.61 rows=13 width=8) (actual time=0.003..0.005 rows=4 loops=14180)
                                             Index Cond: (market_id = m.id)
                                 ->  Index Scan using prices_outcome_id_key on prices p  (cost=0.00..0.34 rows=1 width=4) (actual time=0.003..0.003 rows=1 loops=61439)
                                       Index Cond: (outcome_id = o.id)
         ->  Index Scan using events_keywords_event_id_idx on events_keywords ek  (cost=0.00..1.88 rows=5 width=8) (actual time=0.003..0.005 rows=5 loops=1116)
               Index Cond: (event_id = e.id)
   ->  Hash  (cost=439.60..439.60 rows=21760 width=42) (actual time=17.235..17.235 rows=20934 loops=1)
         Buckets: 4096  Batches: 1  Memory Usage: 1577kB
         ->  Seq Scan on keywords k  (cost=0.00..439.60 rows=21760 width=42) (actual time=0.008..6.366 rows=20934 loops=1)
 Total runtime: 405.865 ms

Per node type stats

node type	count	sum of times	% of query
Hash	2	11.171 ms	2.8 %
Hash Join	1	5.321 ms	1.3 %
Hash Left Join	1	0.958 ms	0.2 %
HashAggregate	1	16.489 ms	4.1 %
Index Scan	4	271.957 ms	67.1 %
Nested Loop	4	60.798 ms	15.0 %
Seq Scan	3	38.561 ms	9.5 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
events	2	32.195 ms	7.9 %
Seq Scan	2	32.195 ms	100.0 %
events_keywords	1	5.580 ms	1.4 %
Index Scan	1	5.580 ms	100.0 %
keywords	1	6.366 ms	1.6 %
Seq Scan	1	6.366 ms	100.0 %
markets	1	11.160 ms	2.8 %
Index Scan	1	11.160 ms	100.0 %
outcomes	1	70.900 ms	17.5 %
Index Scan	1	70.900 ms	100.0 %
prices	1	184.317 ms	45.5 %
Index Scan	1	184.317 ms	100.0 %

explain.depesz.com

A tool for finding a real cause for slow queries.

Result: Uecc

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Per node type stats

Per table stats