You can use IndexSearcher#explain to see how scores are computed.
On Wed, Jun 26, 2019 at 12:48 AM wrote:
>
> Hi,-
>
> i really want to know why the scoring works this way: search String is
> either MAINO or MAINS: MAIN appears as the 276th entry in the results.
>
> NEW HAMPSHIRE in results: ci
Hi,-
i really want to know why the scoring works this way: search String is
either MAINO or MAINS: MAIN appears as the 276th entry in the results.
NEW HAMPSHIRE in results: city="NASHUA" municipality="HILLSBOROUGH"
region="NEW HAMPSHIRE" country="UNITED STATES" in the 0 th result
NEW HAMPSHI
Yeah, that code looks right to me.
The factory we use for keeping backwards compatibility is entirely
ours. I think CustomAnalyzer is a similar-looking API to what we have
but we made ours much earlier and it supports analysis stuff all the
way back to Lucene 3 which we migrated all the way to whe
Corrected a typo below in the new code.
Best regards
On 6/25/19 5:01 PM, baris.ka...@oracle.com wrote:
Hi,-
do You mean there is a backward compatibility factory in Lucene for
these kinds of cases?
i think it can be fixed like this, In other words is the following
first line redundant t
Hi,-
do You mean there is a backward compatibility factory in Lucene for
these kinds of cases?
i think it can be fixed like this, In other words is the following
first line redundant then?
TokenStream filter = new StandardFilter(tokenizer); -> redundant
(tokenizer is actually a StandardT
i tested this on Lucene 7.7.2 and got the same answer MAINS cannot find
MAIN but all other consonant combos at the end can be found.
i am now confident that this is a bug with Lucene.
Best regards
PS. Lucene 8.1 has drastic changes such as StandardFilter is removed in
one of the packages and
Optimize is rarely useful. It can give some performance gains, but is quite an
expensive operation. Pre Solr 7.5, optimizing had some behaviors that weren’t
obvious, see:
https://lucidworks.com/2017/10/13/segment-merging-deleted-documents-optimize-may-bad/
Post 7.5, the behavior has changed.
I
Hello folks,
I got some Lucene indexes in my project, mostly of them are created once and
updated, not so frequently, about once a week or monthly. The indexes sizes are
about 20GB and as more inserts are done the indexes grow, so I'd like to know
what the best index optimization strategy or e
