Hi ,
Analyzer are used either way. Just that score is not computed for filters.
Also there are some permanence optimizations using caching in filters -
http://www.elasticsearch.org/guide/en/elasticsearch/guide/current/filter-caching.html
Try that too.
Thanks
Vineeth
On Wed, Sep 3, 2014 at 9:48 PM, André Hänsel <[email protected]> wrote:
> I thought I need a query (instead of a filter) to use the analyzer. How
> can I do this? Sorry, I'm rather new to Elasticsearch.
>
> Also, is that the best way to go for this kind of query?
>
>
> On Wednesday, September 3, 2014 6:13:15 PM UTC+2, vineeth mohan wrote:
>
>> Hello ,
>>
>> If you use filters rather than query , the scoring should be out of
>> picture.
>>
>> Thanks
>> Vineeth
>>
>>
>> On Wed, Sep 3, 2014 at 9:34 PM, André Hänsel <[email protected]> wrote:
>>
>>> I have an index with about a million entries with a rather dynamic
>>> structure. The queries I want to perform are of the kind: "give me exactly
>>> the entries that contain '*abc*' and '*def*' in any two fields". The
>>> results can be returned in an arbitrary order.
>>>
>>> Since I still need the analyzer for accent and case folding and the
>>> like, the query I end up with is:
>>> {
>>> "query": {
>>> "match": {
>>> "_all": {
>>> "query": "abc def",
>>> "operator": "and"
>>> }
>>> }
>>> }
>>> }
>>>
>>> I have the exact same dataset in Sphinx with min_infix_length = 3 (the
>>> Sphinx equivalent of "min_gram: 3") and on my development machine no query
>>> takes longer than 100 ms (in Sphinx).
>>>
>>> I haven't even activated the ngrams in Elasticsearch yet and it already
>>> takes more than 500 ms to search for a new set of terms.
>>>
>>> Now I wonder if this rather bad performance is related to the scoring
>>> that is performed and what I can do to make it (much) better. Can I maybe
>>> turn off the scoring (since I don't care about the order at all) and get
>>> better performance by that?
>>>
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