Querying a DB for locations in an area - php

Question

I'm interested in making a site which will store several locations and needs to be able to find them based on a user's query. Similar to how sites like Yelp, Zomato, Zillow, etc. function. My preferred tech stack is PHP/MySQL.
That said, I have a few related questions. Given a database of locations with their associate latitude/longitude coordinates...
How are they able to query their database of locations and return the ones within X distance of a specific city or ZIP code?
Furthermore, how can they query their database for locations that, instead of being within proximity, are within very specific city or state limits? Where do they get their boundary data from and how do you determine if a coordinate falls within that boundary in an efficient manner?
Lastly, I notice that some of the sites have city-specific links on their site. I would have expected city data to be pulled from remote mapping APIs, but they often associate images and other content with those cities. Do these sites store the names of all cities in their own database? Where do they get their list?

Answer 1

This will help with your first point.
I use this query to search properties in my database by distance from a starting point. The starting point is the longitude and latitude, $coordX and $coordY. I get these from doing a geocode lookup on the Google Maps API:
SELECT properties.*,
(
( ACOS(SIN(".$coordX." * PI() / 180) *
SIN(coordX * PI() / 180) + COS(".$coordX." * PI() / 180) *
COS(coordX * PI() / 180) * COS((".$coordY." - coordY) *
PI() / 180)) * 180 / PI()) * 60 * 1.1515
)
AS distance
FROM properties
order by distance
In my table I store the coordinates of the coordinates of individual properties in the coordX and coordY columns.

Answer 2

Here's MySQL function that will take two latitude/longitude pairs, and give you the distance in degrees between the two points.
It uses the Haversine formula to calculate the distance. Since the Earth is not a perfect sphere, there is some error near the
poles and the equator.
To convert to miles, multiply by 3961.
To convert to kilometers, multiply by 6373.
To convert to meters, multiply by 6373000.
To convert to feet, multiply by (3961 * 5280) 20914080.
DELIMITER $$
CREATE FUNCTION haversine(
lat1 FLOAT, lon1 FLOAT,
lat2 FLOAT, lon2 FLOAT
) RETURNS float
NO SQL
DETERMINISTIC
COMMENT 'Returns the distance in degrees on the Earth between two known points of latitude and longitude. To get miles, multiply by 3961, and km by 6373'
BEGIN
RETURN DEGREES(ACOS(
COS(RADIANS(lat1)) *
COS(RADIANS(lat2)) *
COS(RADIANS(lon2) - RADIANS(lon1)) +
SIN(RADIANS(lat1)) * SIN(RADIANS(lat2))
));
END;
DELIMITER ;
Add columns to your address table for latitude and longitude with a type of FLOAT(10,6).
Write a php script to do the lookup of the lat/long when the record is saved.
Then you can do a select against the table to get a list of addresses with distances. You can even sort
the results by distance, or limit the result to a certain radius from the reference location.
SELECT
`street`,
`city`,
`state`,
`zip`,
(haversine($ref_location_lat,$ref_location_long,`lat`,`long) * 3961) as `distance`
FROM `address_table`
WHERE (haversine($ref_location_lat,$ref_location_long,`lat`,`long) * 3961) < 300 // Example for limiting returned records to a raduis of 300 miles.
ORDER BY haversine($ref_location_lat,$ref_location_long,`lat`,`long) DESC; // Don't need actual distance for sorting, just relative distance.