Indeed I forgot about the query filter.
Here's my new query:
{
"query": {
"filtered": {
"filter": {
"query": {
"match": {
"_all": {
"query": "abc def",
"operator": "and"
}
}
}
}
}
}
}
Now all the documents have a score of 1, but the performance is still
really bad. Any further suggestions?
On Wednesday, September 3, 2014 6:26:51 PM UTC+2, vineeth mohan wrote:
>
> 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] <javascript:>
> > 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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>>>> .
>>>> For more options, visit https://groups.google.com/d/optout.
>>>>
>>>
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>
>
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