Hi Greg,

I’m assuming we have one match-set which was not constrained by any
of the categories we want to aggregate over, so it may have books by
Mark Twain, books by American authors, and sci-fi books.

Maybe we can imagine we obtained it by searching for a keyword, say
“Washington”, which is present in Mark Twain’s writing, and those of other
American authors, and in sci-fi novels too.

Does that make the example clearer?


Stefan


On Sat, 11 Feb 2023 at 00:16, Greg Miller <gsmil...@gmail.com> wrote:
>
> Hi Stefan-
>
> Can you clarify your example a little bit? It sounds like you want to facet
> over three different match sets (one constrained by "Mark Twain" as the
> author, one constrained by "American authors" and one constrained by the
> "sci-fi" genre). Is that correct?
>
> Cheers,
> -Greg
>
> On Fri, Feb 10, 2023 at 11:33 AM Stefan Vodita <stefan.vod...@gmail.com>
> wrote:
>
> > Hi all,
> >
> > Let’s say I have an index of books, similar to the example in the facet
> > demo [1]
> > with a hierarchical facet field encapsulating `Genre / Author’s
> > nationality /
> > Author’s name`.
> >
> > I might like to find the latest publish date of a book written by Mark
> > Twain, the
> > sum of the prices of books written by American authors, and the number of
> > sci-fi novels.
> >
> > As far as I understand, this would require faceting 3 times over the
> > match-set,
> > one iteration for each aggregation of a different type (max(date),
> > sum(price),
> > count). That seems inefficient if we could instead compute all
> > aggregations in
> > one pass.
> >
> > Is there a way to do that?
> >
> >
> > Stefan
> >
> > [1]
> > https://javadoc.io/doc/org.apache.lucene/lucene-demo/latest/org/apache/lucene/demo/facet/package-summary.html
> >
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