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From "Nicholas Knize (JIRA)" <>
Subject [jira] [Updated] (LUCENE-8496) Explore selective dimension indexing in BKDReader/Writer
Date Thu, 18 Oct 2018 16:44:00 GMT


Nicholas Knize updated LUCENE-8496:
    Affects Version/s: master (8.0)

> Explore selective dimension indexing in BKDReader/Writer
> --------------------------------------------------------
>                 Key: LUCENE-8496
>                 URL:
>             Project: Lucene - Core
>          Issue Type: New Feature
>    Affects Versions: 7.6, master (8.0)
>            Reporter: Nicholas Knize
>            Priority: Major
>         Attachments: LUCENE-8496.patch, LUCENE-8496.patch, LUCENE-8496.patch, LUCENE-8496.patch,
LUCENE-8496.patch, LatLonShape_SelectiveEncoding.patch
>          Time Spent: 2h 20m
>  Remaining Estimate: 0h
> This issue explores adding a new feature to BKDReader/Writer that enables users to select
a fewer number of dimensions to be used for creating the BKD index than the total number of
dimensions specified for field encoding. This is useful for encoding dimensional data that
is used for interpreting the encoded field data but unnecessary (or not efficient) for creating
the index structure. One such example is {{LatLonShape}} encoding. The first 4 dimensions
may be used to to efficiently search/index the triangle using its precomputed bounding box
as a 4D point, and the remaining dimensions can be used to encode the vertices of the tessellated
triangle. This causes BKD to act much like an R-Tree for shape data where search is distilled
into a 4D point (instead of a more expensive 6D point) and the triangle is encoded using a
portion of the remaining (non-indexed) dimensions. Fields that use the full data range for
indexing are not impacted and behave as they normally would.

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