Fastest Way to Find Distance Between Two Lat/Long Points

Question

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 a

Answer 1

SELECT * FROM (SELECT *,(((acos(sin((43.6980168*pi()/180)) * 
sin((latitude*pi()/180))+cos((43.6980168*pi()/180)) * 
cos((latitude*pi()/180)) * cos(((7.266903899999988- longitude)* 
pi()/180))))*180/pi())*60*1.1515 ) as distance 
FROM wp_users WHERE 1 GROUP BY ID limit 0,10) as X 
ORDER BY ID DESC

This is the distance calculation query between to points in MySQL, I have used it in a long database, it it working perfect! Note: do the changes (database name, table name, column etc) as per your requirements.

Answer 2

I needed to solve similar problem (filtering rows by distance from single point) and by combining original question with answers and comments, I came up with solution which perfectly works for me on both MySQL 5.6 and 5.7.

SELECT 
    *,
    (6371 * ACOS(COS(RADIANS(56.946285)) * COS(RADIANS(Y(coordinates))) 
    * COS(RADIANS(X(coordinates)) - RADIANS(24.105078)) + SIN(RADIANS(56.946285))
    * SIN(RADIANS(Y(coordinates))))) AS distance
FROM places
WHERE MBRContains
    (
    LineString
        (
        Point (
            24.105078 + 15 / (111.320 * COS(RADIANS(56.946285))),
            56.946285 + 15 / 111.133
        ),
        Point (
            24.105078 - 15 / (111.320 * COS(RADIANS(56.946285))),
            56.946285 - 15 / 111.133
        )
    ),
    coordinates
    )
HAVING distance < 15
ORDER By distance

coordinates is field with type POINT and has SPATIAL index
6371 is for calculating distance in kilometres
56.946285 is latitude for central point
24.105078 is longitude for central point
15 is maximum distance in kilometers

In my tests, MySQL uses SPATIAL index on coordinates field to quickly select all rows which are within rectangle and then calculates actual distance for all filtered places to exclude places from rectangles corners and leave only places inside circle.

This is visualisation of my result:

Gray stars visualise all points on map, yellow stars are ones returned by MySQL query. Gray stars inside corners of rectangle (but outside circle) were selected by MBRContains() and then deselected by HAVING clause.

Answer 3

set @latitude=53.754842;
set @longitude=-2.708077;
set @radius=20;

set @lng_min = @longitude - @radius/abs(cos(radians(@latitude))*69);
set @lng_max = @longitude + @radius/abs(cos(radians(@latitude))*69);
set @lat_min = @latitude - (@radius/69);
set @lat_max = @latitude + (@radius/69);

SELECT * FROM postcode
WHERE (longitude BETWEEN @lng_min AND @lng_max)
AND (latitude BETWEEN @lat_min and @lat_max);

source

Answer 4

The following MySQL function was posted on this blog post. I haven't tested it much, but from what I gathered from the post, if your latitude and longitude fields are indexed, this may work well for you:

DELIMITER $$

DROP FUNCTION IF EXISTS `get_distance_in_miles_between_geo_locations` $$
CREATE FUNCTION get_distance_in_miles_between_geo_locations(
  geo1_latitude decimal(10,6), geo1_longitude decimal(10,6), 
  geo2_latitude decimal(10,6), geo2_longitude decimal(10,6)) 
returns decimal(10,3) DETERMINISTIC
BEGIN
  return ((ACOS(SIN(geo1_latitude * PI() / 180) * SIN(geo2_latitude * PI() / 180) 
    + COS(geo1_latitude * PI() / 180) * COS(geo2_latitude * PI() / 180) 
    * COS((geo1_longitude - geo2_longitude) * PI() / 180)) * 180 / PI()) 
    * 60 * 1.1515);
END $$

DELIMITER ;

Sample usage:

Assuming a table called places with fields latitude & longitude:

SELECT get_distance_in_miles_between_geo_locations(-34.017330, 22.809500,
latitude, longitude) AS distance_from_input FROM places;

Answer 5

if you are using MySQL 5.7.*, then you can use st_distance_sphere(POINT, POINT).

Select st_distance_sphere(POINT(-2.997065, 53.404146 ), POINT(58.615349, 23.56676 ))/1000  as distcance

Answer 6

   select
   (((acos(sin(('$latitude'*pi()/180)) * sin((`lat`*pi()/180))+cos(('$latitude'*pi()/180)) 
    * cos((`lat`*pi()/180)) * cos((('$longitude'- `lng`)*pi()/180))))*180/pi())*60*1.1515) 
    AS distance
    from table having distance<22;