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https://issues.apache.org/jira/browse/LUCENE-5333?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13817196#comment-13817196
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Michael McCandless commented on LUCENE-5333:
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Hmm if we wrap another FacetsAccumulator, is it the user's job to first create
that accumulator (with no facet requests)? But then how do we then create
another one, with all the facet requests we derived from ROOT? I guess we
could just switch on the N types we have? But then maybe we should just add
static methods to each to make this "All" accumulator for each?
> Support sparse faceting for heterogeneous indices
> -------------------------------------------------
>
> Key: LUCENE-5333
> URL: https://issues.apache.org/jira/browse/LUCENE-5333
> Project: Lucene - Core
> Issue Type: New Feature
> Components: modules/facet
> Reporter: Michael McCandless
>
> In some search apps, e.g. a large e-commerce site, the index can have
> a mix of wildly different product categories and facet dimensions, and
> the number of dimensions could be huge.
> E.g. maybe the index has shirts, computer memory, hard drives, etc.,
> and each of these many categories has different attributes.
> In such an index, when someone searches for "so dimm", which should
> match a bunch of laptop memory modules, you can't (easily) know up
> front which facet dimensions will be important.
> But, I think this is very easy for the facet module, since ords are
> stored "row stride" (each doc lists all facet labels it has), we could
> simply count all facets that the hits actually saw, and then in the
> end see which ones "got traction" and return facet results for these
> top dims.
> I'm not sure what the API would look like, but conceptually this
> should work very well, because of how the facet module works.
> You shouldn't have to state up front exactly which facet dimensions
> to count...
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