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https://issues.apache.org/jira/browse/LUCENE-8496?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16615249#comment-16615249
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Nicholas Knize commented on LUCENE-8496:
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{quote}It is a pity that the patch is so large{quote}
Yeah. Refactoring {{pointDimensionCount}} touched a lot of files so the patch
is rather busy. I could change it to leave {{pointDimensionCount}} as is and
just add a new {{indexDimensionCount}}?
{quote}Out of curiosity, did your working copy already have LUCENE-7862 when
you ran the benchmark?{quote}
Yes. My benchmark numbers include the latest change to store min/max packed
values. The only difference is using {{LatLonShape}} without and with the
selective indexing approach.
{quote}...could you maybe set up a pull request or use Apache reviewboard{quote}
Sure thing! I went ahead and opened a PR
[here|https://github.com/apache/lucene-solr/pull/451]
> 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
> Priority: Major
> Attachments: LUCENE-8496.patch
>
> Time Spent: 10m
> 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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