#	exclusive	inclusive	rows x	rows	loops	node
1.	5.854	436.239	↓ 1.2	5253	1	→ Hash Join (cost=23459.78..27442.53 rows=4207 width=171) (actual time=405.837..436.239 rows=5253 loops=1) Hash Cond: (ek.keyword_id = k.id)
2.	2.370	413.813	↓ 1.2	5253	1	→ Nested Loop (cost=22741.77..26635.12 rows=4207 width=137) (actual time=389.238..413.813 rows=5253 loops=1)
3.	1.062	405.838	↓ 1.4	1121	1	→ Hash Left Join (cost=22741.77..25103.29 rows=787 width=133) (actual time=389.225..405.838 rows=1121 loops=1) Hash Cond: (e.id = e.id)
4.	15.760	15.760	↓ 1.4	1121	1	→ Seq Scan on events e (cost=0.00..2281.75 rows=787 width=121) (actual time=0.189..15.760 rows=1121 loops=1) Filter: display
5.	0.333	389.016	↓ 1.3	1039	1	→ Hash (cost=22731.93..22731.93 rows=787 width=12) (actual time=389.016..389.016 rows=1039 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 49kB
6.	28.560	388.683	↓ 1.3	1039	1	→ HashAggregate (cost=22716.19..22724.06 rows=787 width=8) (actual time=388.378..388.683 rows=1039 loops=1)
7.	38.353	360.123	↓ 1.8	45584	1	→ Nested Loop (cost=0.00..22590.50 rows=25138 width=8) (actual time=0.204..360.123 rows=45584 loops=1)
8.	28.475	134.843	↓ 2.0	62309	1	→ Nested Loop (cost=0.00..11756.31 rows=30777 width=12) (actual time=0.196..134.843 rows=62309 loops=1)
9.	7.456	34.563	↓ 1.6	14361	1	→ Nested Loop (cost=0.00..4926.35 rows=8832 width=10) (actual time=0.187..34.563 rows=14361 loops=1)
10.	15.897	15.897	↓ 1.4	1121	1	→ Seq Scan on events e (cost=0.00..2281.75 rows=787 width=4) (actual time=0.172..15.897 rows=1121 loops=1) Filter: display
11.	11.210	11.210	↑ 1.7	13	1121	→ Index Scan using markets_event_id_index on markets m (cost=0.00..3.09 rows=22 width=10) (actual time=0.004..0.010 rows=13 loops=1121) Index Cond: (event_id = e.id)
12.	71.805	71.805	↑ 3.2	4	14361	→ Index Scan using outcomes_market_id_index on outcomes o (cost=0.00..0.61 rows=13 width=10) (actual time=0.003..0.005 rows=4 loops=14361) Index Cond: (market_id = m.id)
13.	186.927	186.927	↑ 1.0	1	62309	→ 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=62309) Index Cond: (outcome_id = o.id)
14.	5.605	5.605	↑ 1.0	5	1121	→ Index Scan using events_keywords_event_id_idx on events_keywords ek (cost=0.00..1.88 rows=5 width=8) (actual time=0.004..0.005 rows=5 loops=1121) Index Cond: (event_id = e.id)
15.	10.549	16.572	↑ 1.0	20939	1	→ Hash (cost=443.56..443.56 rows=21956 width=42) (actual time=16.572..16.572 rows=20939 loops=1) Buckets: 4096 Batches: 1 Memory Usage: 1577kB
16.	6.023	6.023	↑ 1.0	20939	1	→ Seq Scan on keywords k (cost=0.00..443.56 rows=21956 width=42) (actual time=0.009..6.023 rows=20939 loops=1)

 Hash Join  (cost=23459.78..27442.53 rows=4207 width=171) (actual time=405.837..436.239 rows=5253 loops=1)
   Hash Cond: (ek.keyword_id = k.id)
   ->  Nested Loop  (cost=22741.77..26635.12 rows=4207 width=137) (actual time=389.238..413.813 rows=5253 loops=1)
         ->  Hash Left Join  (cost=22741.77..25103.29 rows=787 width=133) (actual time=389.225..405.838 rows=1121 loops=1)
               Hash Cond: (e.id = e.id)
               ->  Seq Scan on events e  (cost=0.00..2281.75 rows=787 width=121) (actual time=0.189..15.760 rows=1121 loops=1)
                     Filter: display
               ->  Hash  (cost=22731.93..22731.93 rows=787 width=12) (actual time=389.016..389.016 rows=1039 loops=1)
                     Buckets: 1024  Batches: 1  Memory Usage: 49kB
                     ->  HashAggregate  (cost=22716.19..22724.06 rows=787 width=8) (actual time=388.378..388.683 rows=1039 loops=1)
                           ->  Nested Loop  (cost=0.00..22590.50 rows=25138 width=8) (actual time=0.204..360.123 rows=45584 loops=1)
                                 ->  Nested Loop  (cost=0.00..11756.31 rows=30777 width=12) (actual time=0.196..134.843 rows=62309 loops=1)
                                       ->  Nested Loop  (cost=0.00..4926.35 rows=8832 width=10) (actual time=0.187..34.563 rows=14361 loops=1)
                                             ->  Seq Scan on events e  (cost=0.00..2281.75 rows=787 width=4) (actual time=0.172..15.897 rows=1121 loops=1)
                                                   Filter: display
                                             ->  Index Scan using markets_event_id_index on markets m  (cost=0.00..3.09 rows=22 width=10) (actual time=0.004..0.010 rows=13 loops=1121)
                                                   Index Cond: (event_id = e.id)
                                       ->  Index Scan using outcomes_market_id_index on outcomes o  (cost=0.00..0.61 rows=13 width=10) (actual time=0.003..0.005 rows=4 loops=14361)
                                             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=62309)
                                       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=0.004..0.005 rows=5 loops=1121)
               Index Cond: (event_id = e.id)
   ->  Hash  (cost=443.56..443.56 rows=21956 width=42) (actual time=16.572..16.572 rows=20939 loops=1)
         Buckets: 4096  Batches: 1  Memory Usage: 1577kB
         ->  Seq Scan on keywords k  (cost=0.00..443.56 rows=21956 width=42) (actual time=0.009..6.023 rows=20939 loops=1)
 Total runtime: 436.868 ms

Per node type stats

node type	count	sum of times	% of query
Hash	2	10.882 ms	2.5 %
Hash Join	1	5.854 ms	1.3 %
Hash Left Join	1	1.062 ms	0.2 %
HashAggregate	1	28.560 ms	6.5 %
Index Scan	4	275.547 ms	63.2 %
Nested Loop	4	76.654 ms	17.6 %
Seq Scan	3	37.680 ms	8.6 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
events	2	31.657 ms	7.3 %
Seq Scan	2	31.657 ms	100.0 %
events_keywords	1	5.605 ms	1.3 %
Index Scan	1	5.605 ms	100.0 %
keywords	1	6.023 ms	1.4 %
Seq Scan	1	6.023 ms	100.0 %
markets	1	11.210 ms	2.6 %
Index Scan	1	11.210 ms	100.0 %
outcomes	1	71.805 ms	16.5 %
Index Scan	1	71.805 ms	100.0 %
prices	1	186.927 ms	42.8 %
Index Scan	1	186.927 ms	100.0 %

explain.depesz.com

A tool for finding a real cause for slow queries.

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Per node type stats

Per table stats