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Anyone knows how the geospatial indexing works, i mean the algorithm to calculate nearest points?
In SQL we may do things like this:SELECT id, (x-a)*(x-a)+(y-b)*(y-b) as distance FROM table1 ORDER by distance ASC
Sure this is not efficient enough compared with mongodb's geospatial indexing, but how does mongodb calculate and sort?
Many thanks in advance.
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MongoDB's geospatial indexing allows you to efficiently execute spatial queries on a collection that contains geospatial shapes and points.
MongoDB provides the following geospatial index types to support the geospatial queries.
With the spatio-temporal library, you can use functions to index points within a region, on a region containing points, and points within a radius to enable fast queries on this data during location analysis.
A 2dsphere index supports queries that calculate geometries on an earth-like sphere. 2dsphere index supports all MongoDB geospatial queries: queries for inclusion, intersection and proximity. For more information on geospatial queries, see Geospatial Queries.
Heart of mongodb geospatial is Geohashes. Geohash is a
Hierarchical spatial data structure which subdivides space into buckets of grid shape.
I couldn't find the appropriate links for the geohash implementations in mongo, but this thread might give some insights.
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from the 10gen site:
The current implementation encodes geographic hash codes atop standard MongoDB B-trees. Results of $near queries are exact. One limitation with this encoding, while fast, is that prefix lookups don't give exact results, especially around bit flip areas. MongoDB solves this by doing a grid-neighbor search after the initial prefix scan to pick up any straggler points. This generally ensures that performance remains very high while providing correct results.
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