OpenSearch/docs/reference/mapping/params/analyzer.asciidoc

[[analyzer]]
=== `analyzer`

[IMPORTANT]
====
Only <<text,`text`>> fields support the `analyzer` mapping parameter.
====

The `analyzer` parameter specifies the <<analyzer-anatomy,analyzer>> used for
<<analysis,text analysis>> when indexing or searching a `text` field.

Unless overridden with the <<search-analyzer,`search_analyzer`>> mapping
parameter, this analyzer is used for both <<analysis-index-search-time,index and
search analysis>>. See <<specify-analyzer>>.

[TIP]
====
We recommend testing analyzers before using them in production. See
<<test-analyzer>>.
====

[[search-quote-analyzer]]
==== `search_quote_analyzer`

The `search_quote_analyzer` setting allows you to specify an analyzer for phrases, this is particularly useful when dealing with disabling
stop words for phrase queries.

To disable stop words for phrases a field utilising three analyzer settings will be required:

1. An `analyzer` setting for indexing all terms including stop words
2. A `search_analyzer` setting for non-phrase queries that will remove stop words
3. A `search_quote_analyzer` setting for phrase queries that will not remove stop words

[source,console]
--------------------------------------------------
PUT my_index
{
   "settings":{
      "analysis":{
         "analyzer":{
            "my_analyzer":{ <1>
               "type":"custom",
               "tokenizer":"standard",
               "filter":[
                  "lowercase"
               ]
            },
            "my_stop_analyzer":{ <2>
               "type":"custom",
               "tokenizer":"standard",
               "filter":[
                  "lowercase",
                  "english_stop"
               ]
            }
         },
         "filter":{
            "english_stop":{
               "type":"stop",
               "stopwords":"_english_"
            }
         }
      }
   },
   "mappings":{
       "properties":{
          "title": {
             "type":"text",
             "analyzer":"my_analyzer", <3>
             "search_analyzer":"my_stop_analyzer", <4>
             "search_quote_analyzer":"my_analyzer" <5>
         }
      }
   }
}

PUT my_index/_doc/1
{
   "title":"The Quick Brown Fox"
}

PUT my_index/_doc/2
{
   "title":"A Quick Brown Fox"
}

GET my_index/_search
{
   "query":{
      "query_string":{
         "query":"\"the quick brown fox\"" <6>
      }
   }
}
--------------------------------------------------

<1> `my_analyzer` analyzer which tokens all terms including stop words
<2> `my_stop_analyzer` analyzer which removes stop words
<3> `analyzer` setting that points to the `my_analyzer` analyzer which will be used at index time
<4> `search_analyzer` setting that points to the `my_stop_analyzer` and removes stop words for non-phrase queries
<5> `search_quote_analyzer` setting that points to the `my_analyzer` analyzer and ensures that stop words are not removed from phrase queries
<6> Since the query is wrapped in quotes it is detected as a phrase query therefore the `search_quote_analyzer` kicks in and ensures the stop words
are not removed from the query. The `my_analyzer` analyzer will then return the following tokens [`the`, `quick`, `brown`, `fox`] which will match one
of the documents. Meanwhile term queries will be analyzed with the `my_stop_analyzer` analyzer which will filter out stop words. So a search for either
`The quick brown fox` or `A quick brown fox` will return both documents since both documents contain the following tokens [`quick`, `brown`, `fox`].
Without the `search_quote_analyzer` it would not be possible to do exact matches for phrase queries as the stop words from phrase queries would be
removed resulting in both documents matching.