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Thanks for the pointer! This looks interesting. The edge conditions seem like they might pose a problem. I'll have to check out how often it would occur. Maybe

Thanks for the pointer! This looks interesting. The edge conditions seem like they might pose a problem. I'll have to check out how often it would occur. Maybe the geospatial indexes are a better bet. It looks like MongoDB supports them also. Good excuse to try that out.

thibaut_barrere 16y ago
I've been using either MySQL with Sphinx or MongoDB with the built-in geonear successfully. If you're already using MongoDB, it's really dead-easy to setup (see the docs).
nl 16y ago
If you are prepared to introduce new technology specifically to solve this problem, then you should take a look at LocalLucene, too: http://www.gissearch.com/locallucene http://www.gissearch.com/locallucene
bravo_sierra 16y ago
The edge cases happen all the time. Using a B-Tree on a Geohash (like MongoDB does) is a bit more efficient that just indexing min/max values, but not by much. MySQL, PostgreSQL and even SQLite have R-Tree indices that perform 10x better.