I run a geolocation-based social network. Members can see other members based on how close they are.
Right now my MySQL query looks like:
$lat_min = $geo['user_lat'] - 5;
$lat_max = $geo['user_lat'] + 5;
$long_min = $geo['user_long'] - 5;
$long_max = $geo['user_long'] + 5;
$members_query = "SELECT " . $fields . " FROM members WHERE (user_lat BETWEEN " . $lat_min . " AND " . $lat_max . " AND user_long BETWEEN " . $long_min . " AND " . $long_max . ") OR (gc_lat BETWEEN " . $lat_min . " AND " . $lat_max . " AND gc_long BETWEEN " . $long_min . " AND " . $long_max . ")";
user_lat and user_long are coordinates based on geolocation if they have it turned on in their browser. gc_lat and gc_long and coordinates based on their IP address. These rows are all indexed in the database. I am pulling all members within 10 degrees.
The problem is this query takes about 2 seconds to perform for our 250,000+ members, and we want the site to scale.
ATTEMPT 2: I have tried assigning quadrants to each member e.g. "36x-99" ... I am rounding off the latitude and longitude to the nearest multiple of 3 to label the quadrant, and then I only pull quadrants within 12 degrees of the quadrant the member is in.
$members_query = "SELECT " . $fields . " FROM members WHERE quadrant IN ('36x-99', '33x-99', '30x-99', ...);
This gave me no noticeable difference in query speed.
Anyone have any ideas of what I should do? I need to find a solution that will allow the site to scale better.