There are few techniques currently available. Geomesa which uses GeoHash also can be proved useful.( https://github.com/locationtech/geomesa)
Other potential candidate is https://github.com/Esri/gis-tools-for-hadoop especially https://github.com/Esri/geometry-api-java for inner customization. If you want to ask questions like nearby me then these are the basic steps. 1) Index your geometry data which uses R-Tree. 2) Write your joiner logic that takes advantage of the index tree to get you faster access. Thanks Manas On Wed, Mar 11, 2015 at 5:55 AM, Andrew Musselman < andrew.mussel...@gmail.com> wrote: > Ted Dunning and Ellen Friedman's "Time Series Databases" has a section on > this with some approaches to geo-encoding: > > https://www.mapr.com/time-series-databases-new-ways-store-and-access-data > http://info.mapr.com/rs/mapr/images/Time_Series_Databases.pdf > > On Tue, Mar 10, 2015 at 3:53 PM, John Meehan <jnmee...@gmail.com> wrote: > >> There are some techniques you can use If you geohash >> <http://en.wikipedia.org/wiki/Geohash> the lat-lngs. They will >> naturally be sorted by proximity (with some edge cases so watch out). If >> you go the join route, either by trimming the lat-lngs or geohashing them, >> you’re essentially grouping nearby locations into buckets — but you have to >> consider the borders of the buckets since the nearest location may actually >> be in an adjacent bucket. Here’s a paper that discusses an implementation: >> http://www.gdeepak.com/thesisme/Finding%20Nearest%20Location%20with%20open%20box%20query.pdf >> >> On Mar 9, 2015, at 11:42 PM, Akhil Das <ak...@sigmoidanalytics.com> >> wrote: >> >> Are you using SparkSQL for the join? In that case I'm not quiet sure you >> have a lot of options to join on the nearest co-ordinate. If you are using >> the normal Spark code (by creating key-pair on lat,lon) you can apply >> certain logic like trimming the lat,lon etc. If you want more specific >> computing then you are better off using haversine formula. >> <http://www.movable-type.co.uk/scripts/latlong.html> >> >> >> >
