OpenSearch/docs/reference/analysis/tokenizers/pattern-tokenizer.asciidoc

[[analysis-pattern-tokenizer]]
=== Pattern tokenizer
++++
<titleabbrev>Pattern</titleabbrev>
++++

The `pattern` tokenizer uses a regular expression to either split text into
terms whenever it matches a word separator, or to capture matching text as
terms.

The default pattern is `\W+`, which splits text whenever it encounters
non-word characters.

[WARNING]
.Beware of Pathological Regular Expressions
========================================

The pattern tokenizer uses
http://docs.oracle.com/javase/8/docs/api/java/util/regex/Pattern.html[Java Regular Expressions].

A badly written regular expression could run very slowly or even throw a
StackOverflowError and cause the node it is running on to exit suddenly.

Read more about http://www.regular-expressions.info/catastrophic.html[pathological regular expressions and how to avoid them].

========================================

[float]
=== Example output

[source,console]
---------------------------
POST _analyze
{
  "tokenizer": "pattern",
  "text": "The foo_bar_size's default is 5."
}
---------------------------

/////////////////////

[source,console-result]
----------------------------
{
  "tokens": [
    {
      "token": "The",
      "start_offset": 0,
      "end_offset": 3,
      "type": "word",
      "position": 0
    },
    {
      "token": "foo_bar_size",
      "start_offset": 4,
      "end_offset": 16,
      "type": "word",
      "position": 1
    },
    {
      "token": "s",
      "start_offset": 17,
      "end_offset": 18,
      "type": "word",
      "position": 2
    },
    {
      "token": "default",
      "start_offset": 19,
      "end_offset": 26,
      "type": "word",
      "position": 3
    },
    {
      "token": "is",
      "start_offset": 27,
      "end_offset": 29,
      "type": "word",
      "position": 4
    },
    {
      "token": "5",
      "start_offset": 30,
      "end_offset": 31,
      "type": "word",
      "position": 5
    }
  ]
}
----------------------------

/////////////////////


The above sentence would produce the following terms:

[source,text]
---------------------------
[ The, foo_bar_size, s, default, is, 5 ]
---------------------------

[float]
=== Configuration

The `pattern` tokenizer accepts the following parameters:

[horizontal]
`pattern`::

    A http://docs.oracle.com/javase/8/docs/api/java/util/regex/Pattern.html[Java regular expression], defaults to `\W+`.

`flags`::

    Java regular expression http://docs.oracle.com/javase/8/docs/api/java/util/regex/Pattern.html#field.summary[flags].
    Flags should be pipe-separated, eg `"CASE_INSENSITIVE|COMMENTS"`.

`group`::

    Which capture group to extract as tokens.  Defaults to `-1` (split).

[float]
=== Example configuration

In this example, we configure the `pattern` tokenizer to break text into
tokens when it encounters commas:

[source,console]
----------------------------
PUT my_index
{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer": {
          "tokenizer": "my_tokenizer"
        }
      },
      "tokenizer": {
        "my_tokenizer": {
          "type": "pattern",
          "pattern": ","
        }
      }
    }
  }
}

POST my_index/_analyze
{
  "analyzer": "my_analyzer",
  "text": "comma,separated,values"
}
----------------------------

/////////////////////

[source,console-result]
----------------------------
{
  "tokens": [
    {
      "token": "comma",
      "start_offset": 0,
      "end_offset": 5,
      "type": "word",
      "position": 0
    },
    {
      "token": "separated",
      "start_offset": 6,
      "end_offset": 15,
      "type": "word",
      "position": 1
    },
    {
      "token": "values",
      "start_offset": 16,
      "end_offset": 22,
      "type": "word",
      "position": 2
    }
  ]
}
----------------------------

/////////////////////


The above example produces the following terms:

[source,text]
---------------------------
[ comma, separated, values ]
---------------------------

In the next example, we configure the `pattern` tokenizer to capture values
enclosed in double quotes (ignoring embedded escaped quotes `\"`).  The regex
itself looks like this:

    "((?:\\"|[^"]|\\")*)"

And reads as follows:

* A literal `"`
* Start capturing:
** A literal `\"` OR any character except `"`
** Repeat until no more characters match
* A literal closing `"`

When the pattern is specified in JSON, the `"` and `\` characters need to be
escaped, so the pattern ends up looking like:

    \"((?:\\\\\"|[^\"]|\\\\\")+)\"

[source,console]
----------------------------
PUT my_index
{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer": {
          "tokenizer": "my_tokenizer"
        }
      },
      "tokenizer": {
        "my_tokenizer": {
          "type": "pattern",
          "pattern": "\"((?:\\\\\"|[^\"]|\\\\\")+)\"",
          "group": 1
        }
      }
    }
  }
}

POST my_index/_analyze
{
  "analyzer": "my_analyzer",
  "text": "\"value\", \"value with embedded \\\" quote\""
}
----------------------------

/////////////////////

[source,console-result]
----------------------------
{
  "tokens": [
    {
      "token": "value",
      "start_offset": 1,
      "end_offset": 6,
      "type": "word",
      "position": 0
    },
    {
      "token": "value with embedded \\\" quote",
      "start_offset": 10,
      "end_offset": 38,
      "type": "word",
      "position": 1
    }
  ]
}
----------------------------

/////////////////////

The above example produces the following two terms:

[source,text]
---------------------------
[ value, value with embedded \" quote ]
---------------------------