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https://issues.apache.org/jira/browse/LUCENE-7254?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15298215#comment-15298215
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Adrien Grand commented on LUCENE-7254:
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[~rcmuir] I ran the geo benchmark again on my machine and I now get the
following QPS thanks to the recent improvements to DocIdSetBuilder:
|| Benchmark || MatchingPoints || DocIdSetBuilder ||
| box | 71.1 | 72.0 |
| distance | 37.0 | 36.9 |
| poly 5 | 51.9 | 51.4 |
The results now look very close (the difference might just be noise), so should
we switch back to DocIdSetBuilder for geo queries?
> DocIDSetBuilder is no good for points
> -------------------------------------
>
> Key: LUCENE-7254
> URL: https://issues.apache.org/jira/browse/LUCENE-7254
> Project: Lucene - Core
> Issue Type: Bug
> Reporter: Robert Muir
> Attachments: LUCENE-7254.patch, LUCENE-7254.patch
>
>
> For the postings lists, I think this approach works well in dense cases (e.g.
> whole DISI's are added, things are coming in order, etc).
> However in the points case, it holds back range performance significantly.
> There are a couple of problems here:
> * expensive cardinality computation (this is a 2% hit) when its totally
> unnecessary. we can use index statistics to help here.
> * lots of conditional stuff in add(). This includes growing checks / bitset
> switching checks and so on (which happens even if you are smart and call
> grow, but this stuff all adds up).
> I dont think we should try to create a magical shared API that is both
> efficient for postings lists of unstructured stuff and at the same time point
> collection for structured fields, instead we should just do things
> differently for points and iterate from there.
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