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https://issues.apache.org/jira/browse/LUCENE-9335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17345793#comment-17345793
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Zach Chen commented on LUCENE-9335:
-----------------------------------
I made some changes to the BulkScorer implementations to return false for BMM
eligibility immediately when non term query was identified, and they improved
the benchmark results for Fuzzy1 & Fuzzy2 a bit
([https://github.com/apache/lucene/pull/113/commits/f4115f78be0833b65694ad6a0f9f4f32565091e7).]
However, it appears that Fuzzy1 & Fuzzy2 benchmark results would vary more in
general across runs / queries used compared to other tasks.
> Add a bulk scorer for disjunctions that does dynamic pruning
> ------------------------------------------------------------
>
> Key: LUCENE-9335
> URL: https://issues.apache.org/jira/browse/LUCENE-9335
> Project: Lucene - Core
> Issue Type: Improvement
> Reporter: Adrien Grand
> Priority: Minor
> Attachments: wikimedium.10M.nostopwords.tasks,
> wikimedium.10M.nostopwords.tasks.5OrMeds
>
> Time Spent: 6h 50m
> Remaining Estimate: 0h
>
> Lucene often gets benchmarked against other engines, e.g. against Tantivy and
> PISA at [https://tantivy-search.github.io/bench/] or against research
> prototypes in Table 1 of
> [https://cs.uwaterloo.ca/~jimmylin/publications/Grand_etal_ECIR2020_preprint.pdf].
> Given that top-level disjunctions of term queries are commonly used for
> benchmarking, it would be nice to optimize this case a bit more, I suspect
> that we could make fewer per-document decisions by implementing a BulkScorer
> instead of a Scorer.
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