I created a new index that includes both the old "autocomplete" multi-field 
and a new multi-field called "autocompletenew" that contains omit_norms : 
true

I did the same query on the two fields and the results are here
https://gist.github.com/ewltang/33ab829c404130c935ac

The scoring is consistent for both but I find the query on the original 
field seems to return results that make more sense to me. For example 
"PaulJones" is the first result and then followed by PaulJones with one 
numerical digit. The second result is more random with "PaulJones" being 
second. The rest of the results contain longer variations of PaulJones.  

I was expecting that the query on autocompletenew to return the results 
that the query on the original field returns. I also didn't expect the 
first query to return the results that I want since the multi-field doesn't 
have omit_norms: true.  Is this the expected behaviour? 



On Friday, March 28, 2014 12:18:02 AM UTC-4, Eric T wrote:
>
> Hi Ivan,
>
> No I don't apply any boost at index time. 
>
> I did not disable norms on the uname.autocomplete field, I will have to 
> get back to you on the result. I'm using 0.90.2.
>
> thanks
> Eric
>
>
> On Thu, Mar 27, 2014 at 8:55 PM, Ivan Brusic <[email protected]> wrote:
>
>> The difference is the fieldNorm. This field holds any boosts (both 
>> document and field level) and any length normalization. It is only 1 byte, 
>> so it is incredibly lossy. Did you apply an index time boost to either the 
>> field or document?
>>
>> Have you tried disabling norms on ngram fields? Which version of 
>> elasticsearch are you using? I noticed you used the old format 
>> "omit_norms":true
>> instead of  
>> "norms": { "enabled": false }
>>
>> -- 
>> Ivan
>>
>>
>> On Thu, Mar 27, 2014 at 1:28 PM, Eric T <[email protected]> wrote:
>>
>>> Hello,
>>>
>>> I'm running a test of my query and mapping shown here:
>>> https://gist.github.com/ewltang/9c00155525784b620ca9
>>>
>>> I'm searching for "pauljones" in the uname field. In the results the 
>>> fifth document containing "pauljones10297" has a score of 16.027834, while 
>>> the 6th document containing "PaulJones" has a score of 5.008698.
>>> Why is the score for the 5th document so much higher than the 6th? 
>>>
>>> Regards,
>>> Eric
>>>
>>>
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