[jira] [Updated] (LUCENE-7239) Speed up LatLonPoint's polygon queries when there are many vertices

["Robert Muir (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/LUCENE-7239?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Robert Muir updated LUCENE-7239:
--------------------------------
    Attachment: LUCENE-7239.patch

Here is a patch for the sandbox. Ultimately, I think we should just yank the slower polygon support out of Polygon.java, make it a pure holder class. Feels wrong to do stuff like this when e.g. spatial3d does not care.

But for now lets improve it here.

Synthetic polygons from luceneUtil
||vertices||old QPS||new QPS|
|5|24.4|38.4|
|50|21.7|29.7|
|500|14.4|27.5|
|5000|3.3|18.8|
Real polygons (33 london districts: http://data.london.gov.uk/2011-boundary-files)
||vertices||old QPS||new QPS|
|avg 5.6k|8.6|73.0|

Since relations are much faster, startup cost is reduced substantially: e.g. for those real polygons it drops from 85ms to 3ms. We keep our grid for now (its still a decent speedup and now has a cheap cost). Less complex polygons get a nice speedup too since we are less trappy and the two-phase iteration doesn't buy us stuff anymore (similar to distance case).


> Speed up LatLonPoint's polygon queries when there are many vertices
> -------------------------------------------------------------------
>
>                 Key: LUCENE-7239
>                 URL: https://issues.apache.org/jira/browse/LUCENE-7239
>             Project: Lucene - Core
>          Issue Type: Improvement
>            Reporter: Robert Muir
>         Attachments: LUCENE-7239.patch
>
>
> This is inspired by the "reliability and numerical stability" recommendations at the end of http://www-ma2.upc.es/geoc/Schirra-pointPolygon.pdf.
> Basically our polys need to answer two questions that are slow today:
> contains(point)
> crosses(rectangle)
> Both of these ops only care about a subset of edges: the ones overlapping a y interval range. We can organize these edges in an interval tree to be practical and speed things up a lot. Worst case is still O(n) but those solutions are more complex to do.



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