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https://issues.apache.org/jira/browse/LUCENE-3233?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Robert Muir updated LUCENE-3233:
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Attachment: LUCENE-3233.patch
here's a rough start to building a datastructure that I think makes good
tradeoffs between RAM and processing.
No matter what, the processing on the filter-side will be hairy because of the
'interleaving' with the tokenstream.
This one is just an FST<CharsRef,Int[]>(BYTE4) where Int is an ord to a
BytesRefHash, containing the output Bytes for each term.
This way, at input time we can walk the FST with codePointAt()
On both sides, the Chars/Bytes are actually phrases, using \u0000 as a word
separator.
> HuperDuperSynonymsFilter™
> -------------------------
>
> Key: LUCENE-3233
> URL: https://issues.apache.org/jira/browse/LUCENE-3233
> Project: Lucene - Java
> Issue Type: Improvement
> Reporter: Robert Muir
> Attachments: LUCENE-3233.patch
>
>
> The current synonymsfilter uses a lot of ram and cpu, especially at build
> time.
> I think yesterday I heard about "huge synonyms files" three times.
> So, I think we should use an FST-based structure, sharing the inputs and
> outputs.
> And we should be more efficient with the tokenStream api, e.g. using
> save/restoreState instead of cloneAttributes()
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