I currently have just under a million locations in a mysql database all with longitude and latitude information.
I am trying to find the distance between one point and many other points via a query. It's not as fast as I want it to be especially with 100+ hits a second.
Is there a faster query or possibly a faster system other than mysql for this? I'm using this query:
SELECT
name,
( 3959 * acos( cos( radians(42.290763) ) * cos( radians( locations.lat ) )
* cos( radians(locations.lng) - radians(-71.35368)) + sin(radians(42.290763))
* sin( radians(locations.lat)))) AS distance
FROM locations
WHERE active = 1
HAVING distance < 10
ORDER BY distance;
Note: The provided distance is in Miles. If you need Kilometers, use 6371
instead of 3959
.
Create your points using Point
values of Geometry
data types in MyISAM
table. As of Mysql 5.7.5, InnoDB
tables now also support SPATIAL
indices.
Create a SPATIAL
index on these points
Use MBRContains()
to find the values:
SELECT *
FROM table
WHERE MBRContains(LineFromText(CONCAT(
'('
, @lon + 10 / ( 111.1 / cos(RADIANS(@lon)))
, ' '
, @lat + 10 / 111.1
, ','
, @lon - 10 / ( 111.1 / cos(RADIANS(@lat)))
, ' '
, @lat - 10 / 111.1
, ')' )
,mypoint)
, or, in MySQL 5.1
and above:
SELECT *
FROM table
WHERE MBRContains
(
LineString
(
Point (
@lon + 10 / ( 111.1 / COS(RADIANS(@lat))),
@lat + 10 / 111.1
),
Point (
@lon - 10 / ( 111.1 / COS(RADIANS(@lat))),
@lat - 10 / 111.1
)
),
mypoint
)
This will select all points approximately within the box (@lat +/- 10 km, @lon +/- 10km)
.
This actually is not a box, but a spherical rectangle: latitude and longitude bound segment of the sphere. This may differ from a plain rectangle on the Franz Joseph Land, but quite close to it on most inhabited places.
Apply additional filtering to select everything inside the circle (not the square)
Possibly apply additional fine filtering to account for the big circle distance (for large distances)