Nicholas Knize created LUCENE-8496:
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Summary: Explore selective dimension indexing in BKDReader/Writer
Key: LUCENE-8496
URL: https://issues.apache.org/jira/browse/LUCENE-8496
Project: Lucene - Core
Issue Type: New Feature
Reporter: Nicholas Knize
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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