One-degree of longitude equals 288,200 feet (54.6 miles), one minute equals 4,800 feet (0.91 mile), and one second equals 80 feet.
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(@lat)))
, ' '
, @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)
Not a MySql specific answer, but it'll improve the performance of your sql statement.
What you're effectively doing is calculating the distance to every point in the table, to see if it's within 10 units of a given point.
What you can do before you run this sql, is create four points that draw a box 20 units on a side, with your point in the center i.e.. (x1,y1 ) . . . (x4, y4), where (x1,y1) is (givenlong + 10 units, givenLat + 10units) . . . (givenLong - 10units, givenLat -10 units). Actually, you only need two points, top left and bottom right call them (X1, Y1) and (X2, Y2)
Now your SQL statement use these points to exclude rows that definitely are more than 10u from your given point, it can use indexes on the latitudes & longitudes, so will be orders of magnitude faster than what you currently have.
e.g.
select . . .
where locations.lat between X1 and X2
and locations.Long between y1 and y2;
The box approach can return false positives (you can pick up points in the corners of the box that are > 10u from the given point), so you still need to calculate the distance of each point. However this again will be much faster because you have drastically limited the number of points to test to the points within the box.
I call this technique "Thinking inside the box" :)
EDIT: Can this be put into one SQL statement?
I have no idea what mySql or Php is capable of, sorry. I don't know where the best place is to build the four points, or how they could be passed to a mySql query in Php. However, once you have the four points, there's nothing stopping you combining your own SQL statement with mine.
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
and locations.lat between X1 and X2
and locations.Long between y1 and y2
having distance < 10 ORDER BY distance;
I know with MS SQL I can build a SQL statement that declares four floats (X1, Y1, X2, Y2) and calculates them before the "main" select statement, like I said, I've no idea if this can be done with MySql. However I'd still be inclined to build the four points in C# and pass them as parameters to the SQL query.
Sorry I can't be more help, if anyone can answer the MySQL & Php specific portions of this, feel free to edit this answer to do so.
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
index6371
is for calculating distance in kilometres56.946285
is latitude for central point24.105078
is longitude for central point15
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.
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 ;
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;
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
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.
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
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