ing a lot about it by debugging and fighting through it.
> Thank you, and also thank you, Stefan for your responses and for your
> help. Stefan, I will review your demo as well.
>
> Thank you,
>
> Tony
>
>
> -Original Message-
> From: Greg Miller
> Sent:
Hi Tony-
There are indeed a few different ways faceting can be implemented, which
can be confusing. Can you share a little more about what you're looking to
do with faceting? It sounds like maybe you want to facet on a docvalues
field you already have in your index? If that's the use-case, you mig
Hey Michael-
You've gotten a lot of great information here already. I'll point you to
one more implementation as well: StringValueFacetCounts. This
implementation lets you do faceting over arbitrary "string-like" doc value
fields (SORTED and SORTED_SET). So if you already have a field of this type
[forwarding to dev@ and java-users@]
For anyone interested, please see the following note from Gavin on ASF
Travel Assistance for Berlin Buzzwords.
Cheers,
-Greg
-- Forwarded message -
From: Gavin McDonald
Date: Fri, Mar 24, 2023 at 2:57 AM
Subject: TAC supporting Berlin Buzzwor
lps
> with the
> use-case we were discussing. I left a comment with some other ideas that
> I'd
> like to explore.
>
> Thank you for coding this up,
> Stefan
>
> On Sun, 5 Mar 2023 at 19:33, Greg Miller wrote:
> >
> > Hi Stefan-
> >
> > I cobb
defining the expression and making a
> single
> faceting call. Has anyone worked on something similar?
>
> Best,
> Stefan
>
> On Thu, 23 Feb 2023 at 16:53, Greg Miller wrote:
> >
> > Thanks for the detailed benchmarking Stefan! I think you've demonstrated
>
3317 |
>
> With 10 aggregations, we're saving a second or more. That is significant
> for my
> use-case.
>
> I'd like to know if the test and results seem reasonable. If so, maybe
> we can think
> about providing this functionality.
>
> Thanks,
>
facet field using data from a `popularity`
> DocValue.
> > >
> > > In the demo, we compute `sum(_score * sqrt(popularity))`, but what if
> we
> > > want several other different aggregations with respect to the same
> facet
> > > field? Maybe we want `max(popular
c924028063/lucene/demo/src/java/org/apache/lucene/demo/facet/ExpressionAggregationFacetsExample.java#L91
>
> On Mon, 13 Feb 2023 at 22:46, Greg Miller wrote:
> >
> > Hi Stefan-
> >
> > That helps, thanks. I'm a bit confused about where you're concerned
“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 wrote:
> >
> > Hi Stefan-
> >
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,
oes let you avoid building a global ordinal map and doing
map lookups within the tight loop.
Cheers,
-Greg
On Fri, Jul 1, 2022 at 2:35 AM Harald Braumann wrote:
>
> Hi!
>
> On 01.07.22 00:46, Greg Miller wrote:
> > Have you considered taxonomy faceting for your use-case?
Hi Harry-
Have you considered taxonomy faceting for your use-case? Because the
taxonomy structure is maintained in a separate index, it's
(relatively) trivial to iterate all direct child ordinals of a given
dimension. The cost of mapping to a global ordinal space is done when
the index is merged.
I wonder if the idea is that fastMatchQuery provides additional
filtering to only documents that might match one of the ranges being
faceted on. As a (somewhat contrived) example, what if you were
searching over items in an ecommerce catalog that all contain an
indexed numeric "price" attribute, an
+1 to align this to the needs of keepScores. Good find!
On Mon, Mar 21, 2022 at 10:00 AM Adrien Grand wrote:
>
> +1 to adjusting the ScoreMode based on keepScores.
>
> On Mon, Mar 21, 2022 at 5:47 PM Mike Drob wrote:
> >
> > Hey all,
> >
> > I was looking into some performance issues and was a l
My understanding is that, 1) there isn't any specific relationship
between the iterations, and 2) the final output is a summary over all
iterations. The idea is that randomness might affect results on any
particular iteration, but by running multiple times (20 I think?) and
then aggregating the sta
e implemented something similar, or have any thoughts or
> ideas about that?
>
> --
> Regards,
> Alex
>
>
> On Thu, Apr 29, 2021 at 6:08 AM Greg Miller wrote:
>
> > Hi Alex-
> >
> > Amazon's product search engine is built on top of Lucene, which is a
&
Hi Alex-
Amazon's product search engine is built on top of Lucene, which is a
fairly large-scale application (w.r.t. both index size, traffic and
use-case complexity). We have found taxonomy-based faceting to work
well for us generally, and haven't needed to do much to optimize
beyond what's alrea
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