Yep, thanks for confirming my understanding, in the case of using term
queries on non-analyzed fields, the search value must match the exact case
of the original value if I understand this correctly.

Bob
On Jan 16, 2014, at 6:23 PM, Ivan Brusic
<[email protected]<javascript:_e({}, 'cvml', '[email protected]');>>
wrote:

Correction: meant to say use *term* queries on non-analyzed fields, not
*text* queries.


On Thu, Jan 16, 2014 at 6:22 PM, Ivan Brusic
<[email protected]<javascript:_e({}, 'cvml', '[email protected]');>
> wrote:

> Correct. A term query does not analyze the terms, while a match query
> does. Generally, you should use text queries on non-analyzed fields, and
> match queries on analyzed ones. Analysis does not always mean lowercasing
> terms, but that is what the default (standard) analyzer does. All these
> concepts derive from Lucene.
>
> Cheers,
>
> Ivan
>
>
> On Thu, Jan 16, 2014 at 6:07 PM, Bob Ngu <[email protected]<javascript:_e({}, 
> 'cvml', '[email protected]');>
> > wrote:
>
>> Oh I think I get it now, the analyzed value in the index is all lowercase
>> and hence the exact match must be lowercase for an exact match using term
>> query. When using match query, the term is first analyzed making it
>> lowercase before doing the search, hence case insensitive. Am I right?
>>
>>
>> On Thursday, January 16, 2014, Bob <[email protected] <javascript:_e({},
>> 'cvml', '[email protected]');>> wrote:
>>
>>>  I am just learning ES and would appreciate a quick explanation on
>>> analyzed vs not analyzed searches. My basic understanding is that unless
>>> indicated otherwise, fields are analyzed during indexing time but when it
>>> comes to search time, a term query matches documents for terms that are not
>>> analyzed, hence it must match exactly. I am not sure what that means
>>> exactly because for one, the fields are already analyzed and tokenized
>>> during indexing time, secondly, when I execute a term query, it only
>>> matches in lowercase but with match or query_string queries, they are case
>>> insensitive. Any insights will be much appreciated.
>>>
>>> Thanks,
>>> Bob
>>>
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