Hello Darren ,

I am glad that my solution worked for you.

The approach there is to use multi fields.
One field , keep the raw data by declaring the analyzer as not_analyzed.
Example is sited in this link -
http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/mapping-core-types.html#_multi_fields_3

Thanks
          Vineeth

On Tue, Sep 9, 2014 at 9:27 PM, Darren Trzynka <[email protected]>
wrote:

> Vineeth,
> I just saw your response today and I came to the same conclusion yesterday
> after you gave me a nice working example!  I took it a step further doing
> the same grouping by the field that you did and it came out nicely.
> Something is sinking in anyways with me..-)
>
> Besides some possible language support issues, the biggest thing I see for
> challenges could be if stemming is involved (you search for federal and
> hits are returned on federal, federalizing, etc... so if you just look for
> federal in the term count, it wouldn't find all the matches) and then
> dealing with case sensitivity when looking at the term frequencies (the
> user typed in "Federal cases" which matches by default on federal and
> cases) it seems you would need to lower case the lookup for the term
> frequencies.  What do you think about these cases?
>
> Thanks!
> Darren
>
> On Mon, Sep 8, 2014 at 11:28 AM, vineeth mohan <[email protected]>
> wrote:
>
>> Hello Darren ,
>>
>> Following query does what you have asked for ( replace FIELD with the
>> field you are looking for) -
>>
>> {
>>   "fields": [
>>     "text"
>>   ],
>>   "query": {
>>     "term": {
>>       "text": "god"
>>     }
>>   },
>>   "script_fields": {
>>     "tf": {
>>       "script": "_index['FIELD']['cat'].tf()"
>>     }
>>   }
>> }
>>
>> For the second one , use -
>>
>> {
>>   "query": {
>>     "term": {
>>       "FIELD": "CAT"
>>     }
>>   },
>>   "aggs": {
>>     "groupName": {
>>       "terms": {
>>         "field": "GROUP_FIELD"
>>       },
>>       "aggs": {
>>         "catStats": {
>>           "sum": {
>>             "script": "_index['FIELD']['CAT'].tf()"
>>           }
>>         }
>>       }
>>     }
>>   }
>> }
>>
>> Thanks
>>            Vineeth
>>
>>
>> On Mon, Sep 8, 2014 at 6:24 PM, Darren Trzynka <[email protected]>
>> wrote:
>>
>>> Vineeth,
>>> Thanks for responding.  What I am looking for is provided I perform a
>>> search for various terms, how given the search result can I understand the
>>> frequency of the hits within documents.  For example, I perform a full text
>>> search on cat.  5 documents are returned.  I could today get the terms that
>>> were found highlighted but that is of course quite nasty.  Instead what I
>>> would like returned is the documents but something like for each document
>>> saying:
>>> Document 1 (group: 1): cat - 5
>>> Document 2 (group: 2): cat - 3
>>> Document 3 (group: 1): cat - 2
>>> ...
>>> Document n - cat - #
>>>
>>> Also, there is other metadata that it would be nice to aggregate on too
>>> so I could get an answer for the above scenario:
>>> group : 1 - cat - 7
>>> group : 2 - cat - 3
>>>
>>> Thanks
>>> Darren
>>>
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