How would you perform a radius search to find nearby addresses?

How would you perform a radius search to find nearby addresses?

• A. Use a general search by textual matching and then filter results by distance manually.
• B. Use a geospatial index (e.g., PostGIS) with latitude/longitude; perform distance calculations within a defined radius; optimize with bounding-box filters.
• C. Compute distance by approximate coordinates for all records without an index.
• D. Limit the search to postal codes only and ignore coordinates.

Answer: (B)

Radius searches rely on geospatial indexing and distance-based predicates, not just text matching. To find nearby addresses efficiently, you’d store each address as a geographic point with its latitude and longitude (typically using a geometry or geography column with a common SRID like 4326). A spatial index (such as a GIST index in PostGIS) is built on that column so the database can quickly narrow down candidates near a given location.

When you perform the query, you apply a distance check within the defined radius. Using a function like a distance-based predicate lets the index be used to limit the search to points that are geographically close, and then you compute the exact distance to ensure they truly fall inside the radius. Bounding-box filters are often employed as a first pass to quickly discard records outside a surrounding square, which speeds things up before the precise distance calculation.

This approach is far more scalable and accurate than methods that rely on textual text matching and later filtering by distance, or on computing distances for every single record without any spatial index. Limiting the search to postal codes and ignoring coordinates also misses the precise geometry needed for a true radius query, since multiple addresses can share a postal code and locations within the radius can span many codes.