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Posted to dev@lucene.apache.org by "Michael McCandless (JIRA)" <ji...@apache.org> on 2017/05/26 13:18:04 UTC

[jira] [Updated] (LUCENE-7854) Indexing custom term frequencies

     [ https://issues.apache.org/jira/browse/LUCENE-7854?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Michael McCandless updated LUCENE-7854:
---------------------------------------
    Attachment: LUCENE-7854.patch

Initial patch; I think it's close.

> Indexing custom term frequencies
> --------------------------------
>
>                 Key: LUCENE-7854
>                 URL: https://issues.apache.org/jira/browse/LUCENE-7854
>             Project: Lucene - Core
>          Issue Type: Improvement
>            Reporter: Michael McCandless
>            Assignee: Michael McCandless
>             Fix For: master (7.0)
>
>         Attachments: LUCENE-7854.patch
>
>
> When you index a field with {{IndexOptions.DOCS_AND_FREQS}}, Lucene will store just the docID and term frequency (how many times that term occurred in that document) for all documents that have a given term.
> We compute that term frequency by counting how many times a given token appeared in the field during analysis.
> But it can be useful, in expert use cases, to customize what Lucene stores as the term frequency, e.g. to hold custom scoring signals that are a function of term and document (this is my use case).  Users have also asked for this before, e.g. see https://stackoverflow.com/questions/26605090/lucene-overwrite-term-frequency-at-index-time.
> One way to do this today is to stuff your custom data into a {{byte[]}} payload.  But that's quite inefficient, forcing you to index positions, and pay the overhead of retrieving payloads at search time.
> Another approach is "token stuffing": just enumerate the same token N times where N is the custom number you want to store, but that's also inefficient when N gets high.
> I think we can make this simple to do in Lucene.  I have a working version, using my own custom indexing chain, but the required changes are quite simple so I think we can add it to Lucene's default indexing chain?
> I created a new token attribute, {{TermDocFrequencyAttribute}}, and tweaked the indexing chain to use that attribute's value as the term frequency if it's present, and if the index options are {{DOCS_AND_FREQS}} for that field.



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