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https://issues.apache.org/jira/browse/LUCENE-8091?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16287631#comment-16287631
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Adrien Grand commented on LUCENE-8091:
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This implementation requires values to be both indexed with points and readable
with doc values. The thing that makes it hard with more than 1 dimension is
that we do not have a canonical way to represent vectors in doc values, this
requires a custom encoding with a binary doc value field. So it would be doable
but either the API would be a bit hard to use or we would have to make
assumptions as to how the float[] is encoded in a binary field.
> Better nearest-neighbor queries
> -------------------------------
>
> Key: LUCENE-8091
> URL: https://issues.apache.org/jira/browse/LUCENE-8091
> Project: Lucene - Core
> Issue Type: Improvement
> Reporter: Adrien Grand
> Priority: Minor
> Attachments: LUCENE-8091.patch
>
>
> LatLonPoint.nearest is very efficient at identifying the top-k documents
> sorted by distance from a given point, by working directly on the BKD tree.
> This doesn't support filtering though, so if you need to filter by another
> property, you need to switch to querying on the filter and sorting by a
> LatLonPointSortField. Unfortunately this requires visiting all documents that
> match the filter.
> We could leverage the new {{setMinCompetitiveScore}} API introduced in
> LUCENE-4100 in order to allow for retrieval of nearest neighbors with
> arbitrary filters, by recomputing a bounding-box when a new minimum
> competitive score is set.
> In the future we could also leverage this to speed up queries that are
> boosted by distance. For instance if the final score is a weighted sum of the
> score on a text field and a distance-based score, and the minimum competitive
> score gets higher than the maximum score that may be produced on the text
> field at some point, then we could dynamically prune hits based on the
> distance.
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