your query runs in parallel on multiple shards and score you seeing is 
computed independently on every shard
the default similarity is tf/idf based, which means it is using terms 
frequency across all documents (so your score on the shard will depend on 
data on this shard)
for score to be this same, every shard will have to have more or less this 
same documents

you can change search_type to compute score when combining results from 
shards (slower):
http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/search-request-search-type.html

also check this out (to learn more about similarity algorithms used by 
elasticsearch):
http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/index-modules-similarity.html

because you are searching for user names, it is possible that you could 
wrap your query in constant (or function) score query and settle for less 
granular scoring:
http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/query-dsl-function-score-query.html


Cheers,
Karol Gwaj


On Monday, February 17, 2014 11:00:47 AM UTC, Vallabh Bothre wrote:
>
> Dear Friends,
>
> I am using phonetic analysis in elasticsearch to search best results.
>
> When i search keyword lets say "McDonald" elastic search returns many 
> listings with "McDonald's" but some of these have differrent scores.
>
> I am manipulating results based on score and due to this difference its 
> affecting my functionality.
>
> All returned listings with "McDonald" have same case and are exact.
>
> For Ex: 
> *Name                 score*
> McDonald's         *5.8059134*
> McDonald's         5.8059134
> McDonald's         5.8059134
> McDonald's         *5.7834973*
> McDonald's         5.7834973
> McDonald's         *5.4078074*
>
>
> As shown in example above there are 3 different scores which are 
> highlighted.
>
> Any help is very much appreciated.
>
> Regards,
> Vallabh
>

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