Some months ago, have been asked about how to generate a search result ordered by distance, without using spatial DB predicated.
For a situation such as this, the steps are the following:
Store the latitude and longitude in numeric fields in the table, something like this:
create table poi(id int auto_increment primary key, name varchar(64), lat float, lon float);
Create the indexes (this is important, other)
create index idxpoilat on poi(lat); create index idxpoilon on poi(lon);
Given the point (ptlat, ptlon) and distance do the radius query with bounding box filtering.
About the queries, if we want, for example, to search for services around point 47.3569, 8.5432 up to distance = 10km, the query is the following:
select name, lat, lon, SQRT(POW(lat-47.3569,2)+ POW(lon-8.5432 , 2)) * 111.32 as distance from poi where lat < (47.3569 + 0.08983) and lat > (47.3569 - 0.08983) and lon < (8.5432 + 0.08983) and lon > (8.5432 - 0.08983) having distance < 10 order by distance asc;
- conversion from degrees to KM is degree 40075.16/360 = 111.32, so for 10 km, we will search for radius in degrees: 10.0/111.32 = 0.0898. This variable will be computed when building the query.
- filtering by lat and long makes use of the B-trees of the Mysql non-geographic index
For a more precise solution, the possible improvements are:
Use a storage with spatial indexing such as R-trees. PostgreSQL/Posgis, later versions of MySQL with extensions can do the trick. MongoDB also as built-in geographic indexes
store the coordinates in projected system (eg, Google Mercator, or a more localized one), it makes the precision better