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

GET /_analyze
{
  "analyzer" : "standard",
  "text" : "this is a test"
}

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

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

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:

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

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

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

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

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

GET /analyze_sample/_analyze
{
  "text" : "this is a test"
}

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:

GET /analyze_sample/_analyze
{
  "analyzer" : "whitespace",
  "text" : "this is a test"
}

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

GET /analyze_sample/_analyze
{
  "field" : "obj1.field1",
  "text" : "this is a test"
}

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

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

GET /analyze_sample/_analyze
{
  "normalizer" : "my_normalizer",
  "text" : "BaR"
}

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

GET /_analyze
{
  "filter" : ["lowercase"],
  "text" : "BaR"
}

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.

GET /_analyze
{
  "tokenizer" : "standard",
  "filter" : ["snowball"],
  "text" : "detailed output",
  "explain" : true,
  "attributes" : ["keyword"] 
}

The request returns the following 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 
      }, {
        "token" : "output",
        "start_offset" : 9,
        "end_offset" : 15,
        "type" : "<ALPHANUM>",
        "position" : 1,
        "keyword" : false 
      } ]
    } ]
  }
}

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:

PUT /analyze_sample
{
  "settings" : {
    "index.analyze.max_token_count" : 20000
  }
}

GET /analyze_sample/_analyze
{
  "text" : "this is a test"
}