I did some analysis with access-control lists and found that our
customers have significant overlap in the documents they have access to,
so we would be able to realize very nice compression in the number of
terms in access control queries by indexing overlapping subsets.
However this is a fai
For queries with many terms, where each term matches few documents
(actually a single document for "ID filters" in my tests), I saw
speedups between 4x and 8x
http://heliosearch.org/solr-terms-query/ (the 3rd chart)
-Yonik
http://heliosearch.org - native code faceting, facet functions,
sub-facets
I suggested TermsFilter, not TermFilter :) Note the sneaky extra s
Mike McCandless
http://blog.mikemccandless.com
On Wed, Oct 29, 2014 at 8:20 AM, Pawel Rog wrote:
> Hi,
> I already tried to transform Queries to filter (TermQuery -> TermFilter)
> but didn't see much speed up. I wrote tha
Hi,
I already tried to transform Queries to filter (TermQuery -> TermFilter)
but didn't see much speed up. I wrote that wrapped this filter into
ConstantScoreQuery and in other test I used FilteredQuery with
MatchAllDocsQuery and BooleanFilter. Both cases seems to work quite similar
in terms of pe
I'm curious to know more about your use case, because I have an idea for
something that addresses this, but haven't found the opportunity to
develop it yet - maybe somebody else wants to :). The basic idea is to
reduce the number of terms needed to be looked up by collapsing
commonly-occurring
Are the clauses simple TermQuery? If so, try TermsFilter: it sorts
the terms which should give some [small] speedup when visiting them in
the terms dict, and it reuses a single TermsEnum across all terms.
Mike McCandless
http://blog.mikemccandless.com
On Tue, Oct 28, 2014 at 9:40 PM, Pawel Ro
