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https://issues.apache.org/jira/browse/LUCENE-10654?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17579030#comment-17579030
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ASF subversion and git services commented on LUCENE-10654:
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Commit 543910d9008e714016db8a799058860b8ece5565 in lucene's branch
refs/heads/main from Nick Knize
[ https://gitbox.apache.org/repos/asf?p=lucene.git;h=543910d9008 ]
LUCENE-10654: Fix ShapeDocValue Bounding Box failure (#1066)
The base spatial test case may create invalid self crossing polygons. These
polygons are cleaned by the tessellator which may result in an inconsistent
bounding box between the tessellated shape and the original, invalid, geometry.
This commit fixes the shape doc value test case to compute the bounding box from
the cleaned geometry instead of relying on the, potentially invalid, original
geometry.
Signed-off-by: Nicholas Walter Knize <nkn...@apache.org>
> New companion doc value format for LatLonShape and XYShape field types
> ----------------------------------------------------------------------
>
> Key: LUCENE-10654
> URL: https://issues.apache.org/jira/browse/LUCENE-10654
> Project: Lucene - Core
> Issue Type: New Feature
> Reporter: Nick Knize
> Priority: Major
> Fix For: 9.4
>
> Time Spent: 7h 40m
> Remaining Estimate: 0h
>
> {{XYDocValuesField}} provides doc value support for {{XYPoint}}.
> {{LatLonDocValuesField}} provides docvalue support for {{LatLonPoint}}.
> However, neither {{LatLonShape}} nor {{XYShape}} currently have a docvalue
> format.
> This lack of doc value support for shapes means facets, aggregations, and
> IndexOrDocValues queries are currently not possible for Shape field types.
> This gap needs be closed in lucene.
> To support IndexOrDocValues queries along with various geometry aggregations
> and facets, the ability to compute the spatial relation with the doc value is
> needed. This is straightforward with {{XYPoint}} and {{LatLonPoint}} since
> the doc value encoding is nothing more than a simple 2D integer encoding of
> the x,y and lat,lon dimensional components. Accomplishing the same with a
> naive integer encoded binary representation for N-vertex shapes would be
> costly.
> {{ComponentTree}} already provides an efficient in memory structure for
> quickly computing spatial relations over Shape types based on a binary tree
> of tessellated triangles provided by the {{Tessellator}}. Furthermore, this
> tessellation is already computed at index time. If we create an on-disk
> representation of {{ComponentTree}} 's binary tree of tessellated triangles
> and use this as the doc value {{binaryValue}} format we will be able to
> efficiently compute spatial relations with this binary representation and
> achieve the same facet/aggregation result over shapes as we can with points
> today (e.g., grid facets, centroid, area, etc).
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