I left a comment on the issue.
Mike McCandless
http://blog.mikemccandless.com
On Sun, Sep 20, 2020 at 1:08 PM Alex K wrote:
> Hi all, I'm still a bit stuck on this particular issue.I posted an issue on
> the Elastiknn repo outlining some measurements and thoughts on potential
> solutions: htt
Hi all, I'm still a bit stuck on this particular issue.I posted an issue on
the Elastiknn repo outlining some measurements and thoughts on potential
solutions: https://github.com/alexklibisz/elastiknn/issues/160
To restate the question: Is there a known optimal way to find and count
docs matching
Thanks Ali. I don't think that will work in this case, since the data I'm
counting is managed by lucene, but that looks like an interesting project.
-Alex
On Fri, Jul 24, 2020, 00:15 Ali Akhtar wrote:
> I'm new to lucene so I'm not sure what the best way of speeding this up in
> Lucene is, but I
I'm new to lucene so I'm not sure what the best way of speeding this up in
Lucene is, but I've previously used https://github.com/npgall/cqengine for
similar stuff. It provided really good performance, especially if you're
just counting things.
On Fri, Jul 24, 2020 at 6:55 AM Alex K wrote:
> Hi
Hi all,
I am working on a query that takes a set of terms, finds all documents
containing at least one of those terms, computes a subset of candidate docs
with the most matching terms, and applies a user-provided scoring function
to each of the candidate docs
Simple example of the query:
- query
