#	exclusive	inclusive	rows x	rows	loops	node
1.	0.001	1887657.013	↓ 0.0	0	1	→ Limit (cost=0.00..1388733.68 rows=1000 width=138) (actual time=1887657.013..1887657.013 rows=0 loops=1)
2.	46807.216	1887657.012	↓ 0.0	0	1	→ Nested Loop (cost=0.00..31471007691.03 rows=22661658 width=138) (actual time=1887657.012..1887657.012 rows=0 loops=1) Join Filter: (u."RoleId" = r."Id")
3.	0.000	1840849.796	↑ 1.0	343063334	1	→ Nested Loop (cost=0.00..31465859566.41 rows=343208229 width=122) (actual time=1.018..1840849.796 rows=343063334 loops=1)
4.	70187.874	805593.748	↑ 1.0	346511117	1	→ Nested Loop (cost=0.00..17722559954.00 rows=346710000 width=42) (actual time=0.586..805593.748 rows=346511117 loops=1)
5.	35405.874	35405.874	↑ 1.0	350000000	1	→ Seq Scan on "Payments" p (cost=0.00..5724570.00 rows=350000000 width=18) (actual time=0.019..35405.874 rows=350000000 loops=1)
6.	700000.000	700000.000	↑ 1.0	1	350000000	→ Index Scan using "PaymentOrders_pkey" on "PaymentOrders" po (cost=0.00..50.61 rows=1 width=24) (actual time=0.002..0.002 rows=1 loops=350000000) Index Cond: ("Id" = p."PaymentOrderId")
7.	1039533.351	1039533.351	↑ 1.0	1	346511117	→ Index Scan using "Users_pkey" on "Users" u (cost=0.00..39.63 rows=1 width=80) (actual time=0.002..0.003 rows=1 loops=346511117) Index Cond: ("Id" = po."UserId")
8.	0.000	0.000	↓ 0.0	0	343063334	→ Materialize (cost=0.00..1.19 rows=1 width=16) (actual time=0.000..0.000 rows=0 loops=343063334)
9.	0.016	0.016	↓ 0.0	0	1	→ Seq Scan on "Roles" r (cost=0.00..1.19 rows=1 width=16) (actual time=0.016..0.016 rows=0 loops=1) Filter: (("Name")::text = 'Moses2333'::text) Rows Removed by Filter: 15

Limit  (cost=0.00..1388733.68 rows=1000 width=138) (actual time=1887657.013..1887657.013 rows=0 loops=1)
  ->  Nested Loop  (cost=0.00..31471007691.03 rows=22661658 width=138) (actual time=1887657.012..1887657.012 rows=0 loops=1)
        Join Filter: (u."RoleId" = r."Id")
        ->  Nested Loop  (cost=0.00..31465859566.41 rows=343208229 width=122) (actual time=1.018..1840849.796 rows=343063334 loops=1)
              ->  Nested Loop  (cost=0.00..17722559954.00 rows=346710000 width=42) (actual time=0.586..805593.748 rows=346511117 loops=1)
                    ->  Seq Scan on "Payments" p  (cost=0.00..5724570.00 rows=350000000 width=18) (actual time=0.019..35405.874 rows=350000000 loops=1)
                    ->  Index Scan using "PaymentOrders_pkey" on "PaymentOrders" po  (cost=0.00..50.61 rows=1 width=24) (actual time=0.002..0.002 rows=1 loops=350000000)
                          Index Cond: ("Id" = p."PaymentOrderId")
              ->  Index Scan using "Users_pkey" on "Users" u  (cost=0.00..39.63 rows=1 width=80) (actual time=0.002..0.003 rows=1 loops=346511117)
                    Index Cond: ("Id" = po."UserId")
        ->  Materialize  (cost=0.00..1.19 rows=1 width=16) (actual time=0.000..0.000 rows=0 loops=343063334)
              ->  Seq Scan on "Roles" r  (cost=0.00..1.19 rows=1 width=16) (actual time=0.016..0.016 rows=0 loops=1)
                    Filter: (("Name")::text = 'Moses2333'::text)
                    Rows Removed by Filter: 15
Total runtime: 1887657.090 ms

Per node type stats

node type	count	sum of times	% of query
Index Scan	2	1739533.351 ms	92.2 %
Limit	1	0.001 ms	0.0 %
Materialize	1	0.000 ms	0.0 %
Nested Loop	3	116995.090 ms	6.2 %
Seq Scan	2	35405.890 ms	1.9 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
"PaymentOrders"	1	700000.000 ms	37.1 %
Index Scan	1	700000.000 ms	100.0 %
"Payments"	1	35405.874 ms	1.9 %
Seq Scan	1	35405.874 ms	100.0 %
"Roles"	1	0.016 ms	0.0 %
Seq Scan	1	0.016 ms	100.0 %
"Users"	1	1039533.351 ms	55.1 %
Index Scan	1	1039533.351 ms	100.0 %

explain.depesz.com

A tool for finding a real cause for slow queries.

Result: 7e7 : Postgresql slow query explain analyze

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Per node type stats

Per table stats