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From "David Smiley (JIRA)" <>
Subject [jira] Commented: (SOLR-2155) Geospatial search using geohash prefixes
Date Wed, 13 Oct 2010 13:20:32 GMT


David Smiley commented on SOLR-2155:

Yes, absolutely Rob.  I went with geohashes because it was a straight-forward implementation
to prove out the concept. It appears my patch is the first of its kind for Lucene/Solr.  For
doing a more efficient Morton representation, I have already looked at the work going on at
javageomodel:  which was built for use with Google
BigTable.  The code there is largely pure java, keep in mind.  It's the same concept but it
uses a dictionary of size 16 (representable by 4 bits) which results in cleaner algorithms
than geohashes' 5-bit dictionary which has some even/odd rules to it which are awkward.  But
yes, it would be more efficient to store the actual intended bits, not characters.

One area that I know nothing about is how scoring/sorting actually works within Lucene.  For
the work here I wasn't in need of that but many people clearly want that.  In your opinion
Rob, is there any opportunity for geo sorting/relevancy code to take advantage of any efficiencies
done here or are they completely unrelated?

(I meant to track you down at LuceneRevolution to say hi but I missed the opportunity.)

> Geospatial search using geohash prefixes
> ----------------------------------------
>                 Key: SOLR-2155
>                 URL:
>             Project: Solr
>          Issue Type: Improvement
>            Reporter: David Smiley
>         Attachments: GeoHashPrefixFilter.patch
> There currently isn't a solution in Solr for doing geospatial filtering on documents
that have a variable number of points.  This scenario occurs when there is location extraction
(i.e. via a "gazateer") occurring on free text.  None, one, or many geospatial locations might
be extracted from any given document and users want to limit their search results to those
occurring in a user-specified area.
> I've implemented this by furthering the GeoHash based work in Lucene/Solr with a geohash
prefix based filter.  A geohash refers to a lat-lon box on the earth.  Each successive character
added further subdivides the box into a 4x8 (or 8x4 depending on the even/odd length of the
geohash) grid.  The first step in this scheme is figuring out which geohash grid squares cover
the user's search query.  I've added various extra methods to GeoHashUtils (and added tests)
to assist in this purpose.  The next step is an actual Lucene Filter, GeoHashPrefixFilter,
that uses these geohash prefixes in to skip to relevant grid squares in the
index.  Once a matching geohash grid is found, the points therein are compared against the
user's query to see if it matches.  I created an abstraction GeoShape extended by subclasses
named PointDistance... and CartesianBox.... to support different queried shapes so that the
filter need not care about these details.
> This work was presented at LuceneRevolution in Boston on October 8th.

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