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https://issues.apache.org/jira/browse/LUCENE-6196?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14289272#comment-14289272
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David Smiley commented on LUCENE-6196:
--------------------------------------

I can tell that you've been focused on distance boosting/ranking applications 
-- and in that context I see where you're coming from.  But it shouldn't at all 
be a for-lorn conclusion that the application is going to score/rank the 
results by distance.  The query might be for analytics to compare a count with 
multiple other filters (e.g. time) or it might be a spatial-rich data set like 
"tracks" generating from GPS and other sensors matching thousands of points and 
once you get into the thousands, I think let alone millions, there would be 
benefit to avoiding thousands of DocValiues lookups (random-IO) versus reading 
postings for a couple terms or so known to be within the shape.

Any way; thanks again for releasing geo3d here.

> Include geo3d package, along with Lucene integration to make it useful
> ----------------------------------------------------------------------
>
>                 Key: LUCENE-6196
>                 URL: https://issues.apache.org/jira/browse/LUCENE-6196
>             Project: Lucene - Core
>          Issue Type: New Feature
>          Components: modules/spatial
>            Reporter: Karl Wright
>            Assignee: David Smiley
>         Attachments: ShapeImpl.java, geo3d.zip
>
>
> I would like to explore contributing a geo3d package to Lucene.  This can be 
> used in conjunction with Lucene search, both for generating geohashes (via 
> spatial4j) for complex geographic shapes, as well as limiting results 
> resulting from those queries to those results within the exact shape in 
> highly performant ways.
> The package uses 3d planar geometry to do its magic, which basically limits 
> computation necessary to determine membership (once a shape has been 
> initialized, of course) to only multiplications and additions, which makes it 
> feasible to construct a performant BoostSource-based filter for geographic 
> shapes.  The math is somewhat more involved when generating geohashes, but is 
> still more than fast enough to do a good job.



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