#	exclusive	inclusive	rows x	rows	loops	node
1.	9.955	9,110.966	↑ 1.0	1	1	→ Gather (cost=161,937.89..180,456.19 rows=1 width=17) (actual time=9,066.694..9,110.966 rows=1 loops=1) Workers Planned: 2 Workers Launched: 2
2.	3.576	9,101.011	↓ 0.0	0	3 / 3	→ Parallel Hash Join (cost=160,937.89..179,456.09 rows=1 width=17) (actual time=9,087.709..9,101.011 rows=0 loops=3) Hash Cond: (m.id = c.mid)
3.	64.562	64.562	↑ 1.3	1,400	3 / 3	→ Parallel Seq Scan on movie m (cost=0.00..18,511.35 rows=1,824 width=21) (actual time=0.390..64.562 rows=1,400 loops=3) Filter: (year > 2010) Rows Removed by Filter: 511,070
4.	1.214	9,032.873	↓ 89.5	179	3 / 3	→ Parallel Hash (cost=160,937.86..160,937.86 rows=2 width=4) (actual time=9,032.872..9,032.873 rows=179 loops=3) Buckets: 1,024 Batches: 1 Memory Usage: 104kB
5.	4,441.690	9,031.659	↓ 89.5	179	3 / 3	→ Parallel Hash Join (cost=23,592.48..160,937.86 rows=2 width=4) (actual time=2,194.410..9,031.659 rows=179 loops=3) Hash Cond: (c.pid = a.id)
6.	4,505.336	4,505.336	↑ 1.2	3,815,282	3 / 3	→ Parallel Seq Scan on casts c (cost=0.00..119,466.08 rows=4,767,808 width=8) (actual time=0.047..4,505.336 rows=3,815,282 loops=3)
7.	0.229	84.633	↓ 0.0	0	3 / 3	→ Parallel Hash (cost=23,592.46..23,592.46 rows=1 width=4) (actual time=84.631..84.633 rows=0 loops=3) Buckets: 1,024 Batches: 1 Memory Usage: 40kB
8.	84.404	84.404	↓ 0.0	0	3 / 3	→ Parallel Seq Scan on actor a (cost=0.00..23,592.46 rows=1 width=4) (actual time=62.403..84.404 rows=0 loops=3) Filter: (((fname)::text = 'Tom'::text) AND ((lname)::text = 'Hanks'::text)) Rows Removed by Filter: 621,678

                                                                      QUERY PLAN
------------------------------------------------------------------------------------------------------------------------------------------------------
 Gather  (cost=161937.89..180456.19 rows=1 width=17) (actual time=9066.694..9110.966 rows=1 loops=1)
   Workers Planned: 2
   Workers Launched: 2
   ->  Parallel Hash Join  (cost=160937.89..179456.09 rows=1 width=17) (actual time=9087.709..9101.011 rows=0 loops=3)
         Hash Cond: (m.id = c.mid)
         ->  Parallel Seq Scan on movie m  (cost=0.00..18511.35 rows=1824 width=21) (actual time=0.390..64.562 rows=1400 loops=3)
               Filter: (year > 2010)
               Rows Removed by Filter: 511070
         ->  Parallel Hash  (cost=160937.86..160937.86 rows=2 width=4) (actual time=9032.872..9032.873 rows=179 loops=3)
               Buckets: 1024  Batches: 1  Memory Usage: 104kB
               ->  Parallel Hash Join  (cost=23592.48..160937.86 rows=2 width=4) (actual time=2194.410..9031.659 rows=179 loops=3)
                     Hash Cond: (c.pid = a.id)
                     ->  Parallel Seq Scan on casts c  (cost=0.00..119466.08 rows=4767808 width=8) (actual time=0.047..4505.336 rows=3815282 loops=3)
                     ->  Parallel Hash  (cost=23592.46..23592.46 rows=1 width=4) (actual time=84.631..84.633 rows=0 loops=3)
                           Buckets: 1024  Batches: 1  Memory Usage: 40kB
                           ->  Parallel Seq Scan on actor a  (cost=0.00..23592.46 rows=1 width=4) (actual time=62.403..84.404 rows=0 loops=3)
                                 Filter: (((fname)::text = 'Tom'::text) AND ((lname)::text = 'Hanks'::text))
                                 Rows Removed by Filter: 621678

Per node type stats

node type	count	sum of times	% of query
Gather	1	9.955 ms	0.1 %
Parallel Hash	2	1.443 ms	0.0 %
Parallel Hash Join	2	4,445.266 ms	48.8 %
Parallel Seq Scan	3	4,654.302 ms	51.1 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
actor	1	84.404 ms	0.9 %
Parallel Seq Scan	1	84.404 ms	100.0 %
casts	1	4,505.336 ms	49.4 %
Parallel Seq Scan	1	4,505.336 ms	100.0 %
movie	1	64.562 ms	0.7 %
Parallel Seq Scan	1	64.562 ms	100.0 %

explain.depesz.com

PostgreSQL's explain analyze made readable

Result: m2V

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Per node type stats

Per table stats