would also like to know... On Friday, November 14, 2014 9:29:54 AM UTC-7, Todd Nine wrote: > > Hey All, > I have a question about the internal implementation of geo hashes and > distance filters. Here is my current understanding, I'm struggling to > figure out how to apply these to our queries internally in ES. > > > Using bool queries are very efficient. Internally they > perform bitmap union, intersection, and subtraction for very fast candidate > aggregation per term. > > Geo distance filters are then run on the results of the candidates from > the bitmap logic. Each document must be evaluated individually in memory. > Obviously for large documents sets from the bitmap evaluation, this is > inefficient. > > > > What happens when someone only gives our application a geo distance query? > To make this more efficient, I would like to use geo hashing. ES seems to > have geo hashing built in, but it's documented as filter. For instance, I > envision the following workflow internally in ES. > > > 1) User searches for all matches within 2k of their current location > 2) Use a geohash to create a hash that will encapsulate all points within > 2k of their current location > 3) Use the bool query with this geo hash to narrow the candidate result set > 4) Apply the distance filter to these candidates to get more accurate > results. > > > > However, when reading the documentation on searching geo hashing, it's > still a filter. Internally, does it use geohasing and the fast bitmaps > since it's a string match, then filter, or is it all filters and the hash > is evaluated in memory for all documents? > > > http://www.elasticsearch.org/guide/en/elasticsearch/reference/1.4/query-dsl-geohash-cell-filter.html > > > > Thanks, > Todd > > > >
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