#	exclusive	inclusive	rows x	rows	loops	node
1.	0.042	10,897.512	↓ 0.0	0	1	→ HashAggregate (cost=9,477.28..9,518.43 rows=4,115 width=447) (actual time=10,897.511..10,897.512 rows=0 loops=1) Group Key: "NonProfitOrganization".id
2.	10,504.051	10,897.470	↓ 0.0	0	1	→ Hash Right Join (cost=2,973.29..9,466.99 rows=4,115 width=447) (actual time=10,897.469..10,897.470 rows=0 loops=1) Hash Cond: (locations."npoId" = "NonProfitOrganization".id) Filter: ((npo_make_tsvector("NonProfitOrganization".*) @@ plainto_tsquery('group'::text)) OR ((locations."zipCode")::text = 'test'::text) OR (("locations->city".name)::text = 'test'::text) OR (("locations->city->state".name)::text = 'test'::text) OR (("locations->city->state".code)::text = 'test'::text)) Rows Removed by Filter: 121692
3.	86.509	300.936	↑ 1.0	121,690	1	→ Hash Left Join (cost=914.30..7,084.66 rows=122,182 width=32) (actual time=18.683..300.936 rows=121,690 loops=1) Hash Cond: ("locations->city"."stateId" = "locations->city->state".id)
4.	146.025	214.374	↑ 1.0	121,690	1	→ Hash Left Join (cost=911.98..6,738.57 rows=122,182 width=23) (actual time=18.612..214.374 rows=121,690 loops=1) Hash Cond: (locations."cityId" = "locations->city".id)
5.	49.966	49.966	↑ 1.0	121,690	1	→ Seq Scan on "npoLocations" locations (cost=0.00..5,505.82 rows=122,182 width=14) (actual time=0.012..49.966 rows=121,690 loops=1)
6.	10.730	18.383	↑ 1.0	29,910	1	→ Hash (cost=538.10..538.10 rows=29,910 width=17) (actual time=18.383..18.383 rows=29,910 loops=1) Buckets: 32768 Batches: 1 Memory Usage: 1703kB
7.	7.653	7.653	↑ 1.0	29,910	1	→ Seq Scan on cities "locations->city" (cost=0.00..538.10 rows=29,910 width=17) (actual time=0.014..7.653 rows=29,910 loops=1)
8.	0.027	0.053	↑ 1.0	59	1	→ Hash (cost=1.59..1.59 rows=59 width=17) (actual time=0.053..0.053 rows=59 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 11kB
9.	0.026	0.026	↑ 1.0	59	1	→ Seq Scan on states "locations->city->state" (cost=0.00..1.59 rows=59 width=17) (actual time=0.013..0.026 rows=59 loops=1)
10.	36.161	92.483	↑ 1.0	24,340	1	→ Hash (cost=1,751.77..1,751.77 rows=24,577 width=918) (actual time=92.483..92.483 rows=24,340 loops=1) Buckets: 32768 Batches: 1 Memory Usage: 21872kB
11.	56.322	56.322	↑ 1.0	24,340	1	→ Seq Scan on "nonProfitOrganizations" "NonProfitOrganization" (cost=0.00..1,751.77 rows=24,577 width=918) (actual time=0.018..56.322 rows=24,340 loops=1) Filter: (NOT "isSuspended")

HashAggregate  (cost=9477.28..9518.43 rows=4115 width=447) (actual time=10897.511..10897.512 rows=0 loops=1)
  Group Key: "NonProfitOrganization".id
  ->  Hash Right Join  (cost=2973.29..9466.99 rows=4115 width=447) (actual time=10897.469..10897.470 rows=0 loops=1)
        Hash Cond: (locations."npoId" = "NonProfitOrganization".id)
        Filter: ((npo_make_tsvector("NonProfitOrganization".*) @@ plainto_tsquery('group'::text)) OR ((locations."zipCode")::text = 'test'::text) OR (("locations->city".name)::text = 'test'::text) OR (("locations->city->state".name)::text = 'test'::text) OR (("locations->city->state".code)::text = 'test'::text))
        Rows Removed by Filter: 121692
        ->  Hash Left Join  (cost=914.30..7084.66 rows=122182 width=32) (actual time=18.683..300.936 rows=121690 loops=1)
              Hash Cond: ("locations->city"."stateId" = "locations->city->state".id)
              ->  Hash Left Join  (cost=911.98..6738.57 rows=122182 width=23) (actual time=18.612..214.374 rows=121690 loops=1)
                    Hash Cond: (locations."cityId" = "locations->city".id)
                    ->  Seq Scan on "npoLocations" locations  (cost=0.00..5505.82 rows=122182 width=14) (actual time=0.012..49.966 rows=121690 loops=1)
                    ->  Hash  (cost=538.10..538.10 rows=29910 width=17) (actual time=18.383..18.383 rows=29910 loops=1)
                          Buckets: 32768  Batches: 1  Memory Usage: 1703kB
                          ->  Seq Scan on cities "locations->city"  (cost=0.00..538.10 rows=29910 width=17) (actual time=0.014..7.653 rows=29910 loops=1)
              ->  Hash  (cost=1.59..1.59 rows=59 width=17) (actual time=0.053..0.053 rows=59 loops=1)
                    Buckets: 1024  Batches: 1  Memory Usage: 11kB
                    ->  Seq Scan on states "locations->city->state"  (cost=0.00..1.59 rows=59 width=17) (actual time=0.013..0.026 rows=59 loops=1)
        ->  Hash  (cost=1751.77..1751.77 rows=24577 width=918) (actual time=92.483..92.483 rows=24340 loops=1)
              Buckets: 32768  Batches: 1  Memory Usage: 21872kB
              ->  Seq Scan on "nonProfitOrganizations" "NonProfitOrganization"  (cost=0.00..1751.77 rows=24577 width=918) (actual time=0.018..56.322 rows=24340 loops=1)
                    Filter: (NOT "isSuspended")
Planning Time: 2.385 ms
Execution Time: 10897.737 ms

Per node type stats

node type	count	sum of times	% of query
Hash	3	46.918 ms	0.4 %
Hash Left Join	2	232.534 ms	2.1 %
Hash Right Join	1	10,504.051 ms	96.4 %
HashAggregate	1	0.042 ms	0.0 %
Seq Scan	4	113.967 ms	1.0 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
"nonProfitOrganizations"	1	56.322 ms	0.5 %
Seq Scan	1	56.322 ms	100.0 %
"npoLocations"	1	49.966 ms	0.5 %
Seq Scan	1	49.966 ms	100.0 %
cities	1	7.653 ms	0.1 %
Seq Scan	1	7.653 ms	100.0 %
states	1	0.026 ms	0.0 %
Seq Scan	1	0.026 ms	100.0 %

explain.depesz.com

PostgreSQL's explain analyze made readable

Result: gk21

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Per node type stats

Per table stats