Error: FUNCTION ST_Distance_Sphere does not exist in MariaDB - Finding Distance Between Latitude-Longitude Points

• MariaDB: This is a relational database management system, similar to MySQL but with some differences. It's often used for storing and managing data in applications.
• ST_Distance_Sphere: This is a function specifically available in MySQL (version 5.7.6 onwards). It calculates the spherical distance (great-circle distance) between two points on the Earth's surface, given their latitude and longitude coordinates.

The Error Message

When you try to use ST_Distance_Sphere in a MariaDB query, you'll encounter this error because MariaDB doesn't have this built-in function.

Alternative for MariaDB

Since ST_Distance_Sphere isn't available, you can achieve the same functionality using the Haversine formula. This formula calculates the distance between two points on a sphere using their latitude and longitude. Here's the Python code for the Haversine formula:

from math import radians, sin, cos, acos

def haversine_distance(lat1, lon1, lat2, lon2):
  """
  Calculates the distance between two points on a sphere using the Haversine formula.

  Args:
      lat1 (float): Latitude of the first point in degrees.
      lon1 (float): Longitude of the first point in degrees.
      lat2 (float): Latitude of the second point in degrees.
      lon2 (float): Longitude of the second point in degrees.

  Returns:
      float: Distance between the two points in kilometers (default).
  """
  # Convert degrees to radians
  r = 6371  # Earth's radius in kilometers
  lat1, lon1, lat2, lon2 = map(radians, [lat1, lon1, lat2, lon2])

  # Haversine formula
  dlon = lon2 - lon1
  dlat = lat2 - lat1
  a = sin(dlat / 2) * sin(dlat / 2) + cos(radians(lat1)) * cos(radians(lat2)) * sin(dlon / 2) * sin(dlon / 2)
  c = 2 * acos(min(1, a))
  return r * c

# Example usage
latitude1 = 37.7749  # New York City
longitude1 = -122.4194  # San Francisco
latitude2 = 51.505  # London
longitude2 = -0.09

distance_km = haversine_distance(latitude1, longitude1, latitude2, longitude2)
print(f"Distance between New York City and London: {distance_km:.2f} kilometers")

This code defines a function haversine_distance that takes latitude and longitude coordinates of two points and returns the distance between them in kilometers. You can adjust the code to return the distance in other units (miles, etc.) by modifying the Earth's radius value (r).

In summary:

• ST_Distance_Sphere is a convenient function in MySQL for geospatial calculations.
• MariaDB doesn't have this function, but you can use the Haversine formula to achieve the same result.

import math
import mysql.connector

# Connect to your MariaDB database (replace with your credentials)
mydb = mysql.connector.connect(
    host="localhost",
    user="your_username",
    password="your_password",
    database="your_database"
)

mycursor = mydb.cursor()

# Sample query to retrieve latitude and longitude of two points (replace with your actual query)
sql = "SELECT lat, lon FROM your_table WHERE id IN (1, 2)"
mycursor.execute(sql)
rows = mycursor.fetchall()

# Function to calculate Haversine distance
def haversine_distance(lat1, lon1, lat2, lon2):
  """
  Calculates the distance between two points on a sphere using the Haversine formula.

  Args:
      lat1 (float): Latitude of the first point in degrees.
      lon1 (float): Longitude of the first point in degrees.
      lat2 (float): Latitude of the second point in degrees.
      lon2 (float): Longitude of the second point in degrees.

  Returns:
      float: Distance between the two points in kilometers (default).
  """
  r = 6371  # Earth's radius in kilometers
  lat1, lon1, lat2, lon2 = map(radians, [lat1, lon1, lat2, lon2])

  dlon = lon2 - lon1
  dlat = lat2 - lat1
  a = sin(dlat / 2) * sin(dlat / 2) + cos(radians(lat1)) * cos(radians(lat2)) * sin(dlon / 2) * sin(dlon / 2)
  c = 2 * acos(min(1, a))
  return r * c

# Calculate distance for each pair of points retrieved
for row in rows:
  point1_lat, point1_lon = row
  for point2_lat, point2_lon in rows:
    if point1_lat != point2_lat or point1_lon != point2_lon:  # Avoid calculating distance for the same point
      distance_km = haversine_distance(point1_lat, point1_lon, point2_lat, point2_lon)
      print(f"Distance between points ({point1_lat},{point1_lon}) and ({point2_lat},{point2_lon}): {distance_km:.2f} kilometers")

mydb.close()

Using native MySQL with the ST_Distance_Sphere function (assuming you have MySQL 5.7.6 or later):

-- Sample query using ST_Distance_Sphere
SELECT id1, id2, ST_Distance_Sphere(POINT(lon1, lat1), POINT(lon2, lat2)) AS distance_km
FROM your_table AS t1
JOIN your_table AS t2 ON t1.id != t2.id;

This query directly calculates the distance between all pairs of points in the your_table using ST_Distance_Sphere and returns the distance in kilometers as distance_km.

1. Using a User-Defined Function (UDF):

   • You can create a custom function in MariaDB that implements the Haversine formula logic. This can be more efficient than executing the formula in your application code, especially for complex queries involving many distance calculations.
   • Here's a basic example (replace HAVERSINE_RADIUS with the Earth's radius in your desired unit):

   DELIMITER //
   CREATE FUNCTION haversine_distance(lat1 DOUBLE, lon1 DOUBLE, lat2 DOUBLE, lon2 DOUBLE)
   RETURNS DOUBLE
   BEGIN
     DECLARE dlon DOUBLE;
     DECLARE dlat DOUBLE;
     DECLARE a DOUBLE;
     DECLARE c DOUBLE;
     SET dlon = RADIANS(lon2 - lon1);
     SET dlat = RADIANS(lat2 - lat1);
     SET a = SIN(dlat / 2) * SIN(dlat / 2) + COS(RADIANS(lat1)) * COS(RADIANS(lat2)) * SIN(dlon / 2) * SIN(dlon / 2);
     SET c = 2 * ASIN(SQRT(a));
     RETURN HAVERSINE_RADIUS * c;
   END //
   DELIMITER ;
   

   • Then you can use this function in your queries like any other built-in function:

   SELECT id1, id2, haversine_distance(lon1, lat1, lon2, lat2) AS distance_km
   FROM your_table AS t1
   JOIN your_table AS t2 ON t1.id != t2.id;
   

2. Using a Spatial Extension:

   • MariaDB doesn't have a built-in spatial extension like MySQL's Spatial Relations (SR) functions. However, there are third-party extensions like "MariaDB GIS" that add spatial functionalities, including distance calculations.
   • Installing and using such extensions might involve additional configuration steps and may not be suitable for all environments.

The choice of method depends on your specific needs and setup:

• The Haversine formula in your application code is simple to implement but might be less performant for large datasets.
• A UDF can provide better performance but requires creating and managing the function.
• A spatial extension offers a more comprehensive set of spatial functionalities but involves additional setup and may not be available in all environments.