What about fields `index_analyzer` and `search_analyzer`? I had hope
that `index_analyzer` would split string `message_suggest.input` into
array, but it doesn't seem to do it. What are they for then?

On Mon, Apr 7, 2014 at 11:20 AM, Alexander Reelsen <a...@spinscale.de> wrote:
> Hey,
>
> there is no automation for this. The main reason why your solution might
> work in your specific use-case is, that you do not have billions of
> documents. Otherwise there would be a lot of documents, which contain for
> example piece (pi suggestions) or winner (wi), and you would get a lot of
> results. However the goal of a good suggestions is not to get a lot of
> results but few very good ones, which are likely to be chosen by the user
> for further queries. Just adding arbitrary suggestions without
> scoring/weighting them does not make help the user a lot from my experience.
>
> Hope it makes sense..
>
>
> --Alex
>
>
> On Wed, Apr 2, 2014 at 10:26 AM, Sviatoslav Abakumov
> <abakumov.sviatos...@progforce.com> wrote:
>>
>> Hello,
>>
>> I have an index `facebook` with type `post`. I need to provide users with
>> autocompletions using terms that appear in `post.message`. Also the list of
>> completions should be sorted by score.
>>
>> The mapping is as follows:
>> {
>>     "post": {
>>         "properties": {
>>             "created_time": {
>>                 "type": "date",
>>                 "format": "dateOptionalTime"
>>             },
>>             "link": {
>>                 "type": "string"
>>             },
>>             "message": {
>>                 "type": "string"
>>             },
>>             "object_id": {
>>                 "type": "string"
>>             },
>>             "picture": {
>>                 "type": "string"
>>             },
>>             "shares_count": {
>>                 "type": "long"
>>             },
>>             "type": {
>>                 "type": "string"
>>             },
>>             "update_time": {
>>                 "type": "date",
>>                 "format": "dateOptionalTime"
>>             },
>>             "user": {
>>                 "type": "long"
>>             }
>>         }
>>     }
>> }
>>
>> An example document:
>> {
>>     "picture": "...",
>>     "update_time": "2014-03-19T23:16:59",
>>     "message": "The
>>  day has finally arrived - the first piece of the 1,000,000 Swag Bucks
>> pie has been served!!  Check to see if you're our first winner!",
>>     "object_id": "",
>>     "shares_count": 0,
>>     "link": "...",
>>     "user": ...,
>>     "created_time": "2014-03-17T21:02:32",
>>     "type": "link"
>> }
>>
>> To achieve the goal I've added one more field to the mapping:
>> "message_suggest": {
>>     "type": "completion"
>> }
>>
>> Every time I write a document, I query ES to tokenize the string
>> `message`:
>> POST _analyze?_tokenizer=standard
>> The day has finally arrived - the first piece of the 1,000,000 Swag Bucks
>> pie has been served!!  Check to see if you're our first winner!
>>
>> Then I get the list of tokens from the response and add it to
>> `post.message_suggest.input`.
>>
>> When I do the following request, I get what I wanted:
>> POST facebook/_suggest
>> {
>>     "messages": {
>>         "text": "pi",
>>         "completion": {
>>             "field": "message_suggest"
>>         }
>>     }
>> }
>>
>> I sense that this approach is not right or at least not optimal. I am new
>> to Elasticsearch and I would appreciate any input.
>>
>> Best,
>> Sviatoslav.
>>
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