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https://issues.apache.org/jira/browse/LUCENE-4620?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13549568#comment-13549568
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Michael McCandless commented on LUCENE-4620:
--------------------------------------------
Looks like there were some svn mv's, so the patch doesn't directly apply ...
Can you regenerate the patch using 'svn diff --show-copies-as-adds' (assuming
you're using svn 1.7+)?
Either that or use dev-tools/scripts/diffSources.py ... thanks.
> Explore IntEncoder/Decoder bulk API
> -----------------------------------
>
> Key: LUCENE-4620
> URL: https://issues.apache.org/jira/browse/LUCENE-4620
> Project: Lucene - Core
> Issue Type: Improvement
> Components: modules/facet
> Reporter: Shai Erera
> Attachments: LUCENE-4620.patch
>
>
> Today, IntEncoder/Decoder offer a streaming API, where you can encode(int)
> and decode(int). Originally, we believed that this layer can be useful for
> other scenarios, but in practice it's used only for writing/reading the
> category ordinals from payload/DV.
> Therefore, Mike and I would like to explore a bulk API, something like
> encode(IntsRef, BytesRef) and decode(BytesRef, IntsRef). Perhaps the Encoder
> can still be streaming (as we don't know in advance how many ints will be
> written), dunno. Will figure this out as we go.
> One thing to check is whether the bulk API can work w/ e.g. facet
> associations, which can write arbitrary byte[], and so may decoding to an
> IntsRef won't make sense. This too we'll figure out as we go. I don't rule
> out that associations will use a different bulk API.
> At the end of the day, the requirement is for someone to be able to configure
> how ordinals are written (i.e. different encoding schemes: VInt, PackedInts
> etc.) and later read, with as little overhead as possible.
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