How to perform a geographical search with spatial data in MySQL?
To perform geographic search, you need to use MySQL's spatial data types and functions. 1. Use the POINT type to store latitude and longitude and create SPATIAL INDEX of SRID 4326; 2. Use the ST_Distance_Sphere function to find the location within the specified radius, in meters; 3. To improve performance, first use MBRContains combined with bounding box filtering and then calculate the exact distance; 4. When searching for points in polygon areas, use the ST_Within function to determine whether the points are within the range; be sure to set the SRID correctly and upgrade to MySQL 8.0 to obtain better spatial support, and ultimately, various geographic queries can be efficiently implemented.
MySQL supports spatial data types and functions that allow you to store and query geographic data, such as points, lines, and polygons. Performing a geographic search—like finding locations within a certain distance or area—can be done using spatial functions. Here's how to set up and perform such searches effectively.
1. Store Geographical Data Using Spatial Data Types
Use the POINT data type to store latitude and longitude coordinates. For example:
CREATE TABLE locations (
id INT AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(100),
coord POINT SRID 4326, -- WGS84 (standard for GPS)
SPATIAL INDEX(coord)
);-
SRID 4327specifies the coordinate system (WGS84 for Earth coordinates). - A
SPATIAL INDEXon thecoordcolumn improves performance for spatial queries.
Insert sample data:
INSERT INTO locations (name, coordinate) VALUES ('Central Park', POINT(-73.9654, 40.7829)), ('Empire State', POINT(-73.9857, 40.7484));
2. Performance Distance-Based Searches
To find locations within a certain radius (eg, 10 kilometers), use ST_Distance_Sphere() , which calculates distance in meters on a sphere:
SELECT name,
ST_Distance_Sphere(coord, POINT(-73.9867, 40.7580)) AS distance
FROM locations
WHERE ST_Distance_Sphere(coord, POINT(-73.9867, 40.7580)) <= 10000;This finds all locations within 10 km (10,000 meters) of a reference point (eg, Times Square).
Note:
ST_Distance_Sphere()returns distance in meters, so compare accordingly.
3. Use Bounding Box for Faster Filtering
For better performance, especially on large datasets, first filter using a bounding box before applying precision distance checks:
SELECT name,
ST_Distance_Sphere(coord, POINT(-73.9867, 40.7580)) AS distance
FROM locations
WHERE MBRContains(
ST_GeomFromText('POLYGON((-74.0367 40.7080, -74.0367 40.8080,
-73.9367 40.8080, -73.9367 40.7080,
-74.0367 40.7080))', 4326),
coord
)
HAVING distance <= 10000;-
MBRContains()checks if a point is in a minimum bounding rectangle. - This uses the spatial index efficiently to reduce the number of rows before calculating exact distances.
4. Search Within a Polygon (eg, a City Boundary)
If you have a geographic boundary (like a city or zone), use ST_Within() :
SET @city_boundary = 'POLYGON((-74 40.7, -74 40.8, -73.9 40.8, -73.9 40.7, -74 40.7))'; SELECT name FROM locations WHERE ST_Within(coord, ST_GeomFromText(@city_boundary, 4326));
This returns all points that lie inside the defined polygon.
A few practical tips:
- Always assign the correct
SRID(usually 4326 for GPS data). - Use
ST_SRID()to check or set SRID explicitly if needed. - Spatial indexes only work with certain functions like
MBRContains,ST_Within, andST_Distance_Spherein newer MySQL versions (8.0 ). - In MySQL 8.0, spatial support is significantly improved—upgrade if possible.
Basically, store your data with POINT , index it, and use spatial functions like ST_Distance_Sphere or ST_Within depending on your search type. Not complicated once set up right, but easy to misconfigure if SRID or indexing is ignored.
The above is the detailed content of How to perform a geographical search with spatial data in MySQL?. For more information, please follow other related articles on the PHP Chinese website!
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