OpenSearch/docs/reference/indices/analyze.asciidoc

[[indices-analyze]]
=== Analyze API
++++
<titleabbrev>Analyze</titleabbrev>
++++

Performs <<analysis,analysis>> on a text string
and returns the resulting tokens.

[source,js]
--------------------------------------------------
GET /_analyze
{
  "analyzer" : "standard",
  "text" : "Quick Brown Foxes!"
}
--------------------------------------------------
// CONSOLE


[[analyze-api-request]]
==== {api-request-title}

`GET /_analyze`

`POST /_analyze`

`GET /<index>/_analyze`

`POST /<index>/_analyze`


[[analyze-api-path-params]]
==== {api-path-parms-title}

`<index>`::
+
--
(Optional, string)
Index used to derive the analyzer.

If specified,
the `analyzer` or `<field>` parameter overrides this value.

If no analyzer or field are specified,
the analyze API uses the default analyzer for the index.

If no index is specified 
or the index does not have a default analyzer,
the analyze API uses the <<analysis-standard-analyzer,standard analyzer>>.
--


[[analyze-api-query-params]]
==== {api-query-parms-title}

`analyzer`::
+
--
(Optional, string or <<analysis-custom-analyzer,custom analyzer object>>)
Analyzer used to analyze for the provided `text`.

See <<analysis-analyzers>> for a list of built-in analyzers.
You can also provide a <<analysis-custom-analyzer,custom analyzer>>.

If this parameter is not specified,
the analyze API uses the analyzer defined in the field's mapping.

If no field is specified,
the analyze API uses the default analyzer for the index.

If no index is specified,
or the index does not have a default analyzer,
the analyze API uses the <<analysis-standard-analyzer,standard analyzer>>.
--

`attributes`::
(Optional, array of strings)
Array of token attributes used to filter the output of the `explain` parameter.

`char_filter`::
(Optional, array of strings)
Array of character filters used to preprocess characters before the tokenizer.
See <<analysis-charfilters>> for a list of character filters.

`explain`::
(Optional, boolean)
If `true`, the response includes token attributes and additional details.
Defaults to `false`.
experimental:[The format of the additional detail information is labelled as experimental in Lucene and it may change in the future.]

`field`::
+
--
(Optional, string)
Field used to derive the analyzer.
To use this parameter,
you must specify an index.

If specified,
the `analyzer` parameter overrides this value.

If no field is specified,
the analyze API uses the default analyzer for the index.

If no index is specified
or the index does not have a default analyzer,
the analyze API uses the <<analysis-standard-analyzer,standard analyzer>>.
--

`filter`::
(Optional, Array of strings)
Array of token filters used to apply after the tokenizer.
See <<analysis-tokenfilters>> for a list of token filters.

`normalizer`::
(Optional, string)
Normalizer to use to convert text into a single token.
See <<analysis-normalizers>> for a list of normalizers.

`text`::
(Required, string or array of strings)
Text to analyze.
If an array of strings is provided, it is analyzed as a multi-value field.

`tokenizer`::
(Optional, string)
Tokenizer to use to convert text into tokens.
See <<analysis-tokenizers>> for a list of tokenizers.

[[analyze-api-example]]
==== {api-examples-title}

[[analyze-api-no-index-ex]]
===== No index specified

You can apply any of the built-in analyzers to the text string without
specifying an index.

[source,js]
--------------------------------------------------
GET /_analyze
{
  "analyzer" : "standard",
  "text" : "this is a test"
}
--------------------------------------------------
// CONSOLE

[[analyze-api-text-array-ex]]
===== Array of text strings

If the `text` parameter is provided as array of strings, it is analyzed as a multi-value field.

[source,js]
--------------------------------------------------
GET /_analyze
{
  "analyzer" : "standard",
  "text" : ["this is a test", "the second text"]
}
--------------------------------------------------
// CONSOLE

[[analyze-api-custom-analyzer-ex]]
===== Custom analyzer

You can use the analyze API to test a custom transient analyzer built from
tokenizers, token filters, and char filters. Token filters use the `filter`
parameter:

[source,js]
--------------------------------------------------
GET /_analyze
{
  "tokenizer" : "keyword",
  "filter" : ["lowercase"],
  "text" : "this is a test"
}
--------------------------------------------------
// CONSOLE

[source,js]
--------------------------------------------------
GET /_analyze
{
  "tokenizer" : "keyword",
  "filter" : ["lowercase"],
  "char_filter" : ["html_strip"],
  "text" : "this is a <b>test</b>"
}
--------------------------------------------------
// CONSOLE

deprecated[5.0.0, Use `filter`/`char_filter` instead of `filters`/`char_filters` and `token_filters` has been removed]

Custom tokenizers, token filters, and character filters can be specified in the request body as follows:

[source,js]
--------------------------------------------------
GET /_analyze
{
  "tokenizer" : "whitespace",
  "filter" : ["lowercase", {"type": "stop", "stopwords": ["a", "is", "this"]}],
  "text" : "this is a test"
}
--------------------------------------------------
// CONSOLE

[[analyze-api-specific-index-ex]]
===== Specific index

You can also run the analyze API against a specific index:

[source,js]
--------------------------------------------------
GET /analyze_sample/_analyze
{
  "text" : "this is a test"
}
--------------------------------------------------
// CONSOLE
// TEST[setup:analyze_sample]

The above will run an analysis on the "this is a test" text, using the
default index analyzer associated with the `analyze_sample` index. An `analyzer`
can also be provided to use a different analyzer:

[source,js]
--------------------------------------------------
GET /analyze_sample/_analyze
{
  "analyzer" : "whitespace",
  "text" : "this is a test"
}
--------------------------------------------------
// CONSOLE
// TEST[setup:analyze_sample]

[[analyze-api-field-ex]]
===== Derive analyzer from a field mapping

The analyzer can be derived based on a field mapping, for example:

[source,js]
--------------------------------------------------
GET /analyze_sample/_analyze
{
  "field" : "obj1.field1",
  "text" : "this is a test"
}
--------------------------------------------------
// CONSOLE
// TEST[setup:analyze_sample]

Will cause the analysis to happen based on the analyzer configured in the
mapping for `obj1.field1` (and if not, the default index analyzer).

[[analyze-api-normalizer-ex]]
===== Normalizer

A `normalizer` can be provided for keyword field with normalizer associated with the `analyze_sample` index.

[source,js]
--------------------------------------------------
GET /analyze_sample/_analyze
{
  "normalizer" : "my_normalizer",
  "text" : "BaR"
}
--------------------------------------------------
// CONSOLE
// TEST[setup:analyze_sample]

Or by building a custom transient normalizer out of token filters and char filters.

[source,js]
--------------------------------------------------
GET /_analyze
{
  "filter" : ["lowercase"],
  "text" : "BaR"
}
--------------------------------------------------
// CONSOLE

[[explain-analyze-api]]
===== Explain analyze

If you want to get more advanced details, set `explain` to `true` (defaults to `false`). It will output all token attributes for each token.
You can filter token attributes you want to output by setting `attributes` option.

NOTE: The format of the additional detail information is labelled as experimental in Lucene and it may change in the future.

[source,js]
--------------------------------------------------
GET /_analyze
{
  "tokenizer" : "standard",
  "filter" : ["snowball"],
  "text" : "detailed output",
  "explain" : true,
  "attributes" : ["keyword"] <1>
}
--------------------------------------------------
// CONSOLE
<1> Set "keyword" to output "keyword" attribute only

The request returns the following result:

[source,console-result]
--------------------------------------------------
{
  "detail" : {
    "custom_analyzer" : true,
    "charfilters" : [ ],
    "tokenizer" : {
      "name" : "standard",
      "tokens" : [ {
        "token" : "detailed",
        "start_offset" : 0,
        "end_offset" : 8,
        "type" : "<ALPHANUM>",
        "position" : 0
      }, {
        "token" : "output",
        "start_offset" : 9,
        "end_offset" : 15,
        "type" : "<ALPHANUM>",
        "position" : 1
      } ]
    },
    "tokenfilters" : [ {
      "name" : "snowball",
      "tokens" : [ {
        "token" : "detail",
        "start_offset" : 0,
        "end_offset" : 8,
        "type" : "<ALPHANUM>",
        "position" : 0,
        "keyword" : false <1>
      }, {
        "token" : "output",
        "start_offset" : 9,
        "end_offset" : 15,
        "type" : "<ALPHANUM>",
        "position" : 1,
        "keyword" : false <1>
      } ]
    } ]
  }
}
--------------------------------------------------

<1> Output only "keyword" attribute, since specify "attributes" in the request.

[[tokens-limit-settings]]
===== Setting a token limit
Generating excessive amount of tokens may cause a node to run out of memory.
The following setting allows to limit the number of tokens that can be produced:

`index.analyze.max_token_count`::
    The maximum number of tokens that can be produced using `_analyze` API.
    The default value is `10000`. If more than this limit of tokens gets
    generated, an error will be thrown. The `_analyze` endpoint without a specified
    index will always use `10000` value as a limit. This setting allows you to control
    the limit for a specific index:


[source,js]
--------------------------------------------------
PUT /analyze_sample
{
  "settings" : {
    "index.analyze.max_token_count" : 20000
  }
}
--------------------------------------------------
// CONSOLE


[source,js]
--------------------------------------------------
GET /analyze_sample/_analyze
{
  "text" : "this is a test"
}
--------------------------------------------------
// CONSOLE
// TEST[setup:analyze_sample]