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https://issues.apache.org/jira/browse/LUCENE-5333?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13818844#comment-13818844
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Shai Erera commented on LUCENE-5333:
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Actually, if we move FacetResultsHandler to FacetRequest and create the new
AllDimensionsFR, it doesn't need to setDepth() at all, only override
createFacetResultsHandler. And we can add a flattenResults() method to
AllDimsFR which takes a FacetResult and returns a List<FacetResult>, to
simplify app's life. Just an idea.
> 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
> Attachments: LUCENE-5333.patch, LUCENE-5333.patch, LUCENE-5333.patch
>
>
> 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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