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From "Shai Erera (JIRA)" <>
Subject [jira] [Commented] (LUCENE-5333) Support sparse faceting for heterogeneous indices
Date Mon, 11 Nov 2013 10:36:21 GMT


Shai Erera commented on LUCENE-5333:

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:
>             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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