#	exclusive	inclusive	rows x	rows	loops	node
1.	30,562.305	152,660.614	↓ 7.0	14,490,065	1	→ Subquery Scan on nd (cost=2,507,795.01..8,485,134.39 rows=2,064,355 width=58) (actual time=12,806.757..152,660.614 rows=14,490,065 loops=1) Filter: (((('2'::double precision * sqrt((power((nd.lat2 - nd.lat1), '2'::double precision) + power((nd.lng2 - nd.lng1), '2'::double precision)))) * sqrt((power((nd.lat2 - nd.lat3), '2'::double precision) + power((nd.lng2 - nd.lng3), '2'::double precision)))) > '1e-11'::double precision) AND (('1.00001'::double precision < abs(((((((power((nd.lat2 - nd.lat1), '2'::double precision) + power((nd.lng2 - nd.lng1), '2'::double precision)) + power((nd.lat2 - nd.lat3), '2'::double precision)) + power((nd.lng2 - nd.lng3), '2'::double precision)) - power((nd.lat1 - nd.lat3), '2'::double precision)) - power((nd.lng1 - nd.lng3), '2'::double precision)) / (('2'::double precision * sqrt((power((nd.lat2 - nd.lat1), '2'::double precision) + power((nd.lng2 - nd.lng1), '2'::double precision)))) * sqrt((power((nd.lat2 - nd.lat3), '2'::double precision) + power((nd.lng2 - nd.lng3), '2'::double precision))))))) OR (abs(((((((power((nd.lat2 - nd.lat1), '2'::double precision) + power((nd.lng2 - nd.lng1), '2'::double precision)) + power((nd.lat2 - nd.lat3), '2'::double precision)) + power((nd.lng2 - nd.lng3), '2'::double precision)) - power((nd.lat1 - nd.lat3), '2'::double precision)) - power((nd.lng1 - nd.lng3), '2'::double precision)) / (('2'::double precision * sqrt((power((nd.lat2 - nd.lat1), '2'::double precision) + power((nd.lng2 - nd.lng1), '2'::double precision)))) * sqrt((power((nd.lat2 - nd.lat3), '2'::double precision) + power((nd.lng2 - nd.lng3), '2'::double precision)))))) < '1'::double precision))) Rows Removed by Filter: 160012
2.	103,643.809	122,098.309	↓ 1.3	14,650,077	1	→ WindowAgg (cost=2,507,795.01..5,879,918.60 rows=11,147,516 width=130) (actual time=12,806.164..122,098.309 rows=14,650,077 loops=1)
3.	13,926.876	18,454.500	↓ 1.3	14,650,077	1	→ Sort (cost=2,507,795.01..2,535,663.80 rows=11,147,516 width=50) (actual time=12,806.124..18,454.500 rows=14,650,077 loops=1) Sort Key: point_v.tracker_code, point_v.navigation_time Sort Method: external merge Disk: 817192kB
4.	4,527.624	4,527.624	↓ 1.3	14,650,077	1	→ Seq Scan on point_v (cost=0.00..821,945.56 rows=11,147,516 width=50) (actual time=0.023..4,527.624 rows=14,650,077 loops=1) Filter: (((nsat > 3) OR (nsat IS NULL)) AND ((pdop < 8) OR (pdop IS NULL)) AND (speed > 5) AND (speed < 150)) Rows Removed by Filter: 11918935

Planning time	:	0.740 ms

"Subquery Scan on nd  (cost=2507795.01..8485134.39 rows=2064355 width=58) (actual time=12806.757..152660.614 rows=14490065 loops=1)"
"  Filter: (((('2'::double precision * sqrt((power((nd.lat2 - nd.lat1), '2'::double precision) + power((nd.lng2 - nd.lng1), '2'::double precision)))) * sqrt((power((nd.lat2 - nd.lat3), '2'::double precision) + power((nd.lng2 - nd.lng3), '2'::double precision)))) > '1e-11'::double precision) AND (('1.00001'::double precision < abs(((((((power((nd.lat2 - nd.lat1), '2'::double precision) + power((nd.lng2 - nd.lng1), '2'::double precision)) + power((nd.lat2 - nd.lat3), '2'::double precision)) + power((nd.lng2 - nd.lng3), '2'::double precision)) - power((nd.lat1 - nd.lat3), '2'::double precision)) - power((nd.lng1 - nd.lng3), '2'::double precision)) / (('2'::double precision * sqrt((power((nd.lat2 - nd.lat1), '2'::double precision) + power((nd.lng2 - nd.lng1), '2'::double precision)))) * sqrt((power((nd.lat2 - nd.lat3), '2'::double precision) + power((nd.lng2 - nd.lng3), '2'::double precision))))))) OR (abs(((((((power((nd.lat2 - nd.lat1), '2'::double precision) + power((nd.lng2 - nd.lng1), '2'::double precision)) + power((nd.lat2 - nd.lat3), '2'::double precision)) + power((nd.lng2 - nd.lng3), '2'::double precision)) - power((nd.lat1 - nd.lat3), '2'::double precision)) - power((nd.lng1 - nd.lng3), '2'::double precision)) / (('2'::double precision * sqrt((power((nd.lat2 - nd.lat1), '2'::double precision) + power((nd.lng2 - nd.lng1), '2'::double precision)))) * sqrt((power((nd.lat2 - nd.lat3), '2'::double precision) + power((nd.lng2 - nd.lng3), '2'::double precision)))))) < '1'::double precision)))"
"  Rows Removed by Filter: 160012"
"  ->  WindowAgg  (cost=2507795.01..5879918.60 rows=11147516 width=130) (actual time=12806.164..122098.309 rows=14650077 loops=1)"
"        ->  Sort  (cost=2507795.01..2535663.80 rows=11147516 width=50) (actual time=12806.124..18454.500 rows=14650077 loops=1)"
"              Sort Key: point_v.tracker_code, point_v.navigation_time"
"              Sort Method: external merge  Disk: 817192kB"
"              ->  Seq Scan on point_v  (cost=0.00..821945.56 rows=11147516 width=50) (actual time=0.023..4527.624 rows=14650077 loops=1)"
"                    Filter: (((nsat > 3) OR (nsat IS NULL)) AND ((pdop < 8) OR (pdop IS NULL)) AND (speed > 5) AND (speed < 150))"
"                    Rows Removed by Filter: 11918935"
"Planning time: 0.740 ms"
"Execution time: 154012.124 ms"

Per node type stats

node type	count	sum of times	% of query
Seq Scan	1	4,527.624 ms	3.0 %
Sort	1	13,926.876 ms	9.1 %
Subquery Scan	1	30,562.305 ms	20.0 %
WindowAgg	1	103,643.809 ms	67.9 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
point_v	1	4,527.624 ms	3.0 %
Seq Scan	1	4,527.624 ms	100.0 %

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PostgreSQL's explain analyze made readable

Result: RMOU

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Per node type stats

Per table stats