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https://issues.apache.org/jira/browse/LUCENE-7854?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16027782#comment-16027782
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Uwe Schindler commented on LUCENE-7854:
---------------------------------------

Looks fine to me. Only the reflectWith output is different between the packed 
attribute. I think it should be normalized. For the other stuff, [~rcmuir] is 
the better reviewer. :-)

Now we only need a TokenFilter that allows to parse "special tokens" like the 
payload one does (e.g. "token^3"). But that's a separate issue.

> 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, LUCENE-7854.patch, LUCENE-7854.patch, 
> 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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