Playing with Geometry/Spatial Data Types in MySQL

Playing with Geometry/Spatial Data Types in MySQLIn this tutorial, we are going to understand how to store and use spatial data types like coordinates and objects.

But, we will mainly focus on Points (2D Cartesian Coordinate) and Geographic Locations (Geodetic Coordinates)Uday HiwaraleBlockedUnblockFollowFollowingFeb 22(courtesy of pexels.

com)Imagine that you are trying to develop an application that helps people find restaurants, pubs, bars and other hangout places near them.

In nutshell, this will be a location discovery platform.

Looking from a backend perspective, we would be needing to store geographic data of these locations like Latitude and Longitude.

Then we would need to write functions that calculate the distance between the user and the location (to show how far the location is from him/her).

Using the same function, we can design an algorithm that finds closest places near to the user or within a given radius from him/her.

There are many tutorials and study material on the internet that helps you solve this problem by using simple data types like float for latitude and longitude and MySQL’s capability to create internal procedures/functions to calculate & search locations.

But in this tutorial, we are going to talk about MySQL’s built-in spatial data types.

This tutorial assumes that you have the latest MySQL/MariaDB version installed on your system and you are using InnoDB as your default database engine.

All the tests in this tutorial are performed using MySQL Server Version 8.


13 and InnoDB version 8.



To Check MySQL version, use command mysql –version and same for InnoDB can be achived by loging into the MySQL database and execute query SHOW VARIABLES LIKE "innodb_version";OGC or Open Geospatial Consortium is a non-profit organization consisting of many individuals, companies, and organizations that set the standard OpenGIS for open geospatial content and services.

MySQL is one of the databases that follow a subset of this standard.

You can read about OGC from opengeospatial.


Let’s start by understanding some theory about the coordinate system.

We are mainly focusing on a 2-dimensional coordinate system.

Initially, we will focus on an infinite flat cartesian coordinate system.

(courtesy of Wikipedia)On the left, you can see an infinite 2D flat unitless surface where a point is represented like P(x,y) where x is the distance of a point P from the origin(0,0) on the x-axis while y is the distance from the origin(0,0) on the y-axis.

Hence, if we know x, y of a point, we can locate it on the coordinate surface.

The distance of a point from the origin is calculated using Pythagoras theorem.

If we consider the point in green color, using Pythagoras theorem, we can calculate its distance from the origin to be the square root of the sum of the squares of the 2 and 3.

If you want to calculate the distance between two points, you can shift the origin to any one point and measure the distance from it.

If we had to find points inside a circle (whose center is at the origin), we have to calculate the distance of each point and check if it is less than or equal to equal to the radius of the circleI am assuming you understand basic math and geometry and I don’t need to explain 2D cartesian coordiante system in formulae.

For Spherical Surface, like Planet Earth, things are not as simple as a 2-dimensional surface.

We follow the geodetic reference system for mapping locations on the surface of the planet.

In a nutshell, the geodetic reference system is based on longitude and latitude value.

(Courtesy of Wikimedia Commons)Latitude of a location (point) on the globe (sphere) is the number of degrees it is from the equator (when measured along the axis of rotation of the Earth).

Longitude of a location on the globe is the number of degrees it is from the prime meridian (when measured along the equator).

Both Latitude and Longitude are measured from the center of the Earth.

You can read more about the Geographic Coordinate System on Wikipedia.

The maximum value of the Latitude is 90° while the minimum is -90°.

Similarly, the maximum value of longitude is 180° while the minimum is -180°.

As we know, Earth isn’t exactly a sphere but it is an ellipsoid.

But for the sake of simplicity, we are going to assume it is a simple sphere of constant uniform radius.

Later, towards the ending of this tutorial, we are going to talk about some of the issues with MySQL regarding this same exact problem.

Moving on, the 0° Latitude line goes through the equator of the planet dividing the globe into northern and southern hemispheres.

The 0° Longitude line AKA international prime meridian, however, goes through British Royal Observatory in Greenwich, England.

Finding the distance between two locations (points) on the globe (sphere) is not as easy as it was in the 2D coordinate system.

In this case, we need to use Haversine formula which is used to find the distance between two points on the sphere using latitude, longitude of the points and radius of the sphere.

We can use the same formula to find the shortest distance between two locations on the globe.


com has provided some simple code snippets in different languages to calculate the distance between two places on the Earth based on Haversine formula, you can check it out from here.

But the important fact to remember here is that Haversine formula is for a sphere and as we know, that’s not the case for the Earth.

Hence, this can lead to some error which might not be acceptable for precision measurements.

So far, we have seen two coordinate systems, flat and spherical.

There can be many coordinate systems based on the shape, location of the origin or how distance is measured from an origin.

Hence a point on a surface can have a different meaning based on in which coordinate system it lies.

Hence saying P(x,y) is just not enough.

Therefore, we need an extra identifier associated with point signature.

This is where SRID comes into the picture.

SRID or Coordinate Reference System Identifier is the unique integer associated with a coordinate system proposed by OGC.

MySQL databased comes with more than 5000 of such coordinate systems which you can check using below querySELECT `srs_name`, `srs_id`FROM INFORMATION_SCHEMA.

ST_SPATIAL_REFERENCE_SYSTEMSOGC has provided two formats for creating a spatial object like Point, Line, Polygon etc.

They are WKT (well-known text) and WKB (well-known binary).

WKT for a point is 2D cartesian coordinates is as simple as string “POINT(X, Y)” where X and Y are axial distances from the origin.

While in spherical coordinate system X and Y of POINT(X, Y) is latitude and longitude value respectively.

WKB is the binary representation of WKB, which will cover in upcoming topics in this tutorial.

Read more about WKT, WKB specifications for different geometries from here.

Cartesian Coordinate SystemAlright, enough with the theory.

Let’s now dive into the MySQL world and execute some queries to see things in real life.

Initially, we will focus on the 2D cartesian coordinate system.

SRID associated with the 2D cartesian coordinate system is 0.

This is default SRID associated with the POINT built-in function in MySQL.

MySQL provides many built-in functions like POINT, LINESTRING, POLYGON etc.

They are documented here.

Since, we are going to talk about POINT only, I though I should mention this.

Let’s create a point with x = 3 and y = 4 on a coordinate system with SRID 0 (flat 2D cartesian coordinate system).

We will use POINT constructor function since its default SRID is 0.

In the above query, we created a local variable point_p which is set to point (3,4) on the 2D coordinate plane (SRID 0).

As we can see from the result, MySQL successfully created the point and saved in BLOB format.

BLOB is the default storage format of MySQL for all the geometries (do not get confused with WKB format, that is different, as we will see).

Let’s calculate the distance between the origin (point 0,0) and above point.

In the above query, we created another point point_o which is set to the origin point (0,0).

Then we used MySQL’s built-in function ST_Distance to calculate the distance between two points.

As expected, we got result 5.

Hence, our theory is working just fine until now.

MySQL provides many built-in functions to test the relationship between two geometries (above, points).

They are documented here, but we will cover most of them in this tutorial.

ST_ prefix in these functions stands for Spatial Type.

You can find list of all Spatial Type functions from here.

In this tutorial, we are not going to use MySQL’s built-in constructor functions to create geometries (like points) as it is non-standard and restrict to SRID 0, but instead, we will be using MySQL’s built-in functions to create geometries from WKT specification, they are documented here.

ST_GeomFromText is a built-in function to create a geometry in given SRID from WKT specification.

ST_PointFromText can also be used to specifically state that we are creating POINT geometry but it’s just an alias.

The syntax of ST_GeomFromText is as belowST_GeomFromText(geom_wkt, [srid], [options])geom_wkt is WKT representation of a geometry, srid is optional and defaults to 0 while options (comma separated key=value) argument is also optional.

options is additional information provided to ST_GeomFromText function.

As of now, it supports only axis-order key with the value being either long-lat, lat-long or srid-defined(default).

This will come up later when SRID will be different than 0.

In the above query, we simply replaced the generation of POINT geometries from using MySQL’s constructor function to creating geometries from WKT specifications.

We can also verify that default SRID of ST_GeomFromText function is 0 using ST_SRID built-in function which expects a geometry and returns SRID associated with that geometry.

As we know, MySQL stores a geometry data type in BLOB format, but how can we make sure that the given point is correct if we can’t read it.

This can be solved using MySQL’s built-in conversion functions, they are documented here.

Using these functions, we can convert geometries into WKT, WKB and JSON formats (and vice-versa).

ST_AsText(g, [options]) function expects a geometry and optional options argument which is used to set axis-order (as described in ST_GeomFromText) and returns WKT format of a geometry.

ST_AsBinary expects the same arguments as ST_AsText and returns WKB format of a geometry.

ST_AsGeoJson(g) expects a geometry and returns coordinates in JSON.

In the above example, we have converted a geometric shape of the type POINT into readable WKT value, binary WKB value and JSON format.

If you have a GeoJSON of a geometry, you can convert it back a geometry object using ST_GeomFromGeoJSON(geo_json_string) built-in function.

You can also create geometry from WKB using ST_GeomFromWKB / ST_PointFromWKB function.

Arguments for ST_GeomFromWKB is the same as ST_GeomFromText except geometry must be in WKB format.

If you want to get X and Y coordinates of a POINT geometry, you can use ST_X(g) and ST_Y(g) built-in functions.

Let’s create a locations_flat database table and populate it with some sample geometry POINT values.

CREATE TABLE IF NOT EXISTS `locations_flat`( `id` INT NOT NULL PRIMARY KEY AUTO_INCREMENT, `name` VARCHAR(100), `position` POINT NOT NULL SRID 0);SHOW COLUMNS FROM `locations_flat`;You can use POINT, POLYGON, LINESTRING and other geometrical types (mentioned here) to explicitly state the data type.

MySQL also provides GEOMETRY data type if your column contains variable geometry types.

SRID is optional, if omitted, the column can contain geometries of multiple SRIDs.

But this is not recommended as this will not utilize the INDEX and query performance on large data set will be slower, as we will see later.

To insert some sample data, use below queryINSERT INTO `locations_flat`(`name`, `position`)VALUES ( 'point_1', ST_GeomFromText( 'POINT( 1 1 )', 0 ) ), ( 'point_2', ST_GeomFromText( 'POINT( 2 2 )', 0 ) ), ( 'point_3', ST_GeomFromText( 'POINT( 3 3 )', 0 ) );But since we need a large data set, set take help of JavaScript.

Inside your JavaScript console, execute below code which will print above insert statement but with 1000 entry points.

var fn = `ST_GeomFromText`;var values = new Array( 1000 ).


map( ( val, index ) => { var id = index + 1; return `('point_${ id }', ${fn}('POINT(${ id } ${ id + 1 })'))`;} ).


log(` INSERT INTO `locations_flat`(`name`, `position`) VALUES ${ values };`);Let’s see a few data points in our table with a quick SELECT query.

SELECT *, ST_ASTEXT(`position`) AS `pos_wkt`FROM `locations_flat`LIMIT 10;It is perfectly legal to pass a column name to ST_ built-in function as long as its input parameters are legal.

Also, all ST_ function names are case-insensitive.

Hence, you can also use ST_AsText as ST_ASTEXT or st_asText.

Let’s consider these points as places and our user is located at the origin(0,0).

If we want to search for places which are within 100 unit distance from him (let’s say the user is male), we need to calculate the distance of each place and compare if it is less than or equal to 100.

We have used distance function before, which is ST_Distance.

We are going to use this function in WHERE clause in our MySQL query.

SET @user_location = ST_GeomFromText( 'POINT(0 0)' );SELECT *, ST_AsText(`position`) AS `pos_wkt`, ST_Distance(`position`, @user_location) AS `distance`FROM `locations_flat`WHERE ST_Distance(`position`, @user_location) <= 100;From the above query, we created a sample origin geometry POINT at (0,0) and used a reference point to calculate the distance of each point.

WHERE clause filtered the results based on distance and we got around 70 results.

But we can also achieve this using ST_Buffer(g, d) built-in function (documented here) to create geometry (as stated in the documentation) that represents all points whose distance from the geometry value g is less than or equal to a distance of d.

In nutshell, it creates a circular surface area.

It should be noted that ST_Buffer can only create geometry for SRID 0 (plane surface).

Since, g in our case has SRID = 0, hence this works for us.

But a circular area on a spherical surface is rather complex, MySQL just gives up there.

Using this geometry, we can check whether a geometry (point) lies inside it or not.

This can be done using ST_Contains(g1, g2) function which returns 1 if the geometry g1 contains g2, else 0.

Otherwise, we can use ST_Within(g1, g2) function which returns 1 if g1 is within g2, which is quite opposite of ST_Contains function but works for us as well.

SET @user_location = ST_GeomFromText( 'POINT(0 0)' );SET @area_to_search = ST_Buffer( @user_location, 100 );SELECT *, ST_AsText(`position`) AS `pos_wkt`, ST_Distance(`position`, @user_location) AS `distance`FROM `locations_flat`WHERE ST_Within( `position`, @area_to_search ) = 1;Let’s talk about performance now.

We all know about MySQL Indexes.

If not then there is a lot of literature about it on the internet which you can read.

Basically, MySQL maintains an index of a table with rows being ordered according to column values in the B-Tree index.

Whenever we try to search something from the table, MySQL looks into the index and uses nodes created by B-Tree to shortened the search path.

An index of a table won’t be created unless we tell it (in some case, MySQL does that on its own, like Primary Key).

In the case of Spatial Data, MySQL uses SPATIAL INDEX which is for complex multi-dimensional data values and it maintains this index in R-Tree tree structure.

Understanding how it works is not very important at this moment.

Let’s first add SPATIAL INDEX on the table locations_flat.

You can do this in three ways.

You can add index while creation of the table.

CREATE TABLE IF NOT EXISTS `locations_flat`( `id` INT NOT NULL PRIMARY KEY AUTO_INCREMENT, `name` VARCHAR(100), `position` POINT NOT NULL SRID 0, SPATIAL INDEX(`position`));You can also alter the table and add SPATIAL INDEX.

ALTER TABLE `locations_flat` ADD SPATIAL INDEX(`position`);Or you can add index manually using CREATE SPATIAL INDEX statement.

CREATE SPATIAL INDEX position_index ON locations_flat(`position`);A spatial index can only be created on a column with geometry type.

It must be a NOT NULL column and should contain data of only one SRID.

Once, SPATIAL INDEX is created, you can verify indexes on the table using query SHOW INDEXES FROM `locations_flat`;Let’s see how our earlier location search example is doing without using SPATIAL INDEX (ignore index).

SET @user_location = ST_GeomFromText( 'POINT(0 0)' );SET @area_to_search = ST_Buffer( @user_location, 100 );EXPLAIN SELECT *, ST_AsText(`position`) AS `pos_wkt`, ST_Distance(`position`, @user_location) AS `distance`FROM `locations_flat`IGNORE INDEX(`position`)WHERE ST_Within( `position`, @area_to_search ) = 1;Seems like MySQL is using full-table scan and results show that 1000 rows are being searched for the match.

Also, possible_keys are empty which shows that no index was used to perform the search.

Let’s now use the index to find locations, we are going to use statement USE INDEX but that is optional as position column by-default uses the index.

SET @user_location = ST_GeomFromText( 'POINT(0 0)' );SET @area_to_search = ST_Buffer( @user_location, 100 );EXPLAIN SELECT *, ST_AsText(`position`) AS `pos_wkt`, ST_Distance(`position`, @user_location) AS `distance`FROM `locations_flat`USE INDEX(`position`)WHERE ST_Within( `position`, @area_to_search ) = 1;Aha!.We see no difference.

Don’t worry, this is a documented MySQL bug.

When we compare the return value of a spatial function in WHERE clause (like we did with ST_Within( `position`, @area_to_search ) = 1;), MySQL ignores the index.

Since ST_Within returns 1 or 0, it’s perfectly safe to ignore =1 in the statement and WHERE clause will only select value which returns 1.

Yess!.Now we can see that only 53 rows were scanned to return the result and possible_keys column shows that position index was used for the search.

In my experience, I found that in case of a search on small data set, MySQL ignores the index.

So, don’t worry if your EXPLAIN statement doesn’t seem ok.

Geographic Coordinate SystemWe talked a lot about 2D Cartesian Coordinate System, but I know, you must be thinking what’s the use of that.

Basically, it helped us understand how we can use MySQL’s powerful spatial features and use spatial indexes to improve our query performance.

Now, it’s time to come back to Earth and focus on Geographic data points.

Before we begin, let me tell you a bitter truth.

In MySQL, Earth has been approximated as a sphere with a mean radius equal to 6,370,986 meters.

This may create some errors while calculating distances but works in the approximated world.

Also, SRID for the geographic coordinate system is 4326, hence any POINT we are going to create must use 4326 SRID.

Let’s create a table locations_sphere with SPATIAL INDEX and populate it with some sample data points.

CREATE TABLE IF NOT EXISTS `locations_earth`( `id` INT NOT NULL PRIMARY KEY AUTO_INCREMENT, `name` VARCHAR(100), `position` POINT NOT NULL SRID 4326, SPATIAL INDEX(`position`));SHOW COLUMNS FROM `locations_earth`;Let’s populate the locations_earth table with sample geometry points with SRID 4326.

We are going to take help of JavaScript here.

var fn = `ST_GeomFromText`;var values = new Array( 1000 ).


map( ( val, index ) => { var id = index + 1; var lat = (90/1000) * id; // 0-90 deg latitude var long = (180/1000) * id; // 0-180 deg longitude return `('point_${ id }', ${fn}('POINT(${ lat.

toFixed(5) } ${ long.

toFixed(5) })', 4326))`;} ).


log(` INSERT INTO `locations_earth`(`name`, `position`) VALUES ${ values };`);In the above query generator, we made sure that each geometry point on the sphere should not exceed 90 degree latitude and 180 degrees longitude, though all our points are in the northern-eastern hemisphere.

Above code will produce a query like below.

INSERT INTO `locations_earth`(`name`, `position`) VALUES ('point_1', ST_GeomFromText('POINT(0.

09000 0.

18000)', 4326)), ('point_2', ST_GeomFromText('POINT(0.

18000 0.

36000)', 4326)), ('point_3', ST_GeomFromText('POINT(0.

27000 0.

54000)', 4326));As per the OpenGIS specification by OGC, WKT for POINT geometry is POINT(lat, long).

In our case, ST_GeomFromText function returns a geometry POINT with SRID 4326, hence our data points truly belong to spherical coordinates or geographic coordinate system.

Let’s calculate the distance between two points on the globe.

As we seen in the case of the 2D surface, we used ST_Distance function to calculate the distance between two points.

But in the case of a spherical coordinate system, we are going to use ST_Distance_Sphere function.

The signature of ST_Distance_Sphere function is as below.

ST_Distance_Sphere(g1, g2 [, radius])Here, g1 and g2 are geometries on the sphere, like POINTs in our case.

radius argument is optional and defaults to the radius of the earth.

This function returns the shortest distance on the sphere (earth) in meters.

For the test and accuracy test of this function, let’s pick two random locations on the google map.

Since I live in Delhi – India, I am going to pick Lotus Temple (28.

553298, 77.

259221) and India Gate (28.

612849, 77.


You can find (latitude, longitude) combination of a location on google map by right-clicking on a place and selecting what’s here?The distance between these two places is 7.

21km or 7210 meters.

SET @lotus_temple := ST_GeomFromText( 'POINT(28.

553298 77.

259221)', 4326, 'axis-order=lat-long' );SET @india_gate := ST_GeomFromText( 'POINT(28.

612849 77.

229883)', 4326 );SELECT ST_Latitude( @lotus_temple ) AS `lat_lotus_temple`, ST_Longitude( @lotus_temple ) AS `long_lotus_temple`, ST_Latitude( @india_gate ) AS `lat_india_gate`, ST_Longitude( @india_gate ) AS `long_india_gate`, ST_Distance_Sphere( @lotus_temple, @india_gate ) AS `distance`;From the above result, we can see that Google and we are not that far off.

Google measured distance 7210 meters while we measured it to be 7214 meters.

As we know, both of these values certainly can’t be used sensitive information but it’s pretty damn close.

As you can see in the above query, we have used options argument of ST_GeomFromText function to explicitly provide information about the axis order of POINT geometry in WKT.

Also, we can use ST_Latitude and ST_Longitude to get latitude and longitude value geometry types of 4326 SRID.

Now, let’s focus on the application side.

As in earlier examples of 2D flat surface, we calculated points inside a given radius using ST_Buffer circular area geometry.

But unfortunately, MySQL does not support creating circular area geometry in any other SRID besides 0.

Also, we can not transform any geometry from SRID 0 to other coordinate systems using the ST_Transform function.

Seems like our luck is running out.

But we can use a simple but expensive approach to calculate distances of each point on the sphere from the reference point and check if they are within a given radius, like we did earlier.

Let’s say that we are looking for places in 1000km (1000 * 1000m) radius from location(30, 50).

Here 30 is latitude and 50 is longitude.

Using same old SQL query, we get below result.

SET @user_location = ST_GeomFromText( 'POINT(30 50)', 4326 );SELECT *, ST_AsText(`position`) AS `pos_wkt`, ST_Distance_Sphere(`position`, @user_location) AS `distance`FROM `locations_earth`WHERE ST_Distance_Sphere(`position`, @user_location) <= (1000*1000);We have found around 87 results but let’s see how our query is doing.

So even with the SPATIAL INDEX on, the query is performing the full-table scan.

Since we are comparing value returned by ST_Distance_Sphere function inside the WHERE clause, MySQL is ignoring the index.

The only solution is to ignore comparison in WHERE clause but since we can not create a circular geometry in a spherical coordinate system, the closest thing we have is POLYGON geometry type.

To approximate a circle but not wasting too much memory, we can safely use 6 sided polygon.

Let’s see if this works by enclosing a 4 sided polygon around user location.

I know this is very inaccurate, but it will prove that we can do it.

Hurray.So this works.

So far I haven’t found a formula that can take proximity radius from a point on the globe and draw a polygon with n sides.

I guess this will be a TODO and as soon as I find some solution, I will make sure to update this tutorial.

But if you have any suggestions or know any resource material on the internet, please drop a comment.

By the way, Postgres database has far better support for spacial geographic data calculation using PostGIS extension.

Just to mention one, unlike MySQL, PostGIS provides a built-in function ST_DWithin to check if two geometries are within the specified distance of one another, which can be used in WHERE clause and increase performance by utilizing the index.


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