navigation_title: "Fingerprint" mapped_pages:
The fingerprint analyzer implements a fingerprinting algorithm which is used by the OpenRefine project to assist in clustering.
Input text is lowercased, normalized to remove extended characters, sorted, deduplicated and concatenated into a single token. If a stopword list is configured, stop words will also be removed.
POST _analyze
{
  "analyzer": "fingerprint",
  "text": "Yes yes, Gödel said this sentence is consistent and."
}
The above sentence would produce the following single term:
[ and consistent godel is said sentence this yes ]
The fingerprint analyzer accepts the following parameters:
separator
:   The character to use to concatenate the terms. Defaults to a space.
max_output_size
:   The maximum token size to emit. Defaults to 255. Tokens larger than this size will be discarded.
stopwords
:   A pre-defined stop words list like _english_ or an array containing a list of stop words. Defaults to _none_.
stopwords_path
:   The path to a file containing stop words.
See the Stop Token Filter for more information about stop word configuration.
In this example, we configure the fingerprint analyzer to use the pre-defined list of English stop words:
PUT my-index-000001
{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_fingerprint_analyzer": {
          "type": "fingerprint",
          "stopwords": "_english_"
        }
      }
    }
  }
}
POST my-index-000001/_analyze
{
  "analyzer": "my_fingerprint_analyzer",
  "text": "Yes yes, Gödel said this sentence is consistent and."
}
The above example produces the following term:
[ consistent godel said sentence yes ]
The fingerprint tokenizer consists of:
Tokenizer : * Standard Tokenizer
Token Filters (in order) : * Lower Case Token Filter
If you need to customize the fingerprint analyzer beyond the configuration parameters then you need to recreate it as a custom analyzer and modify it, usually by adding token filters. This would recreate the built-in fingerprint analyzer and you can use it as a starting point for further customization:
PUT /fingerprint_example
{
  "settings": {
    "analysis": {
      "analyzer": {
        "rebuilt_fingerprint": {
          "tokenizer": "standard",
          "filter": [
            "lowercase",
            "asciifolding",
            "fingerprint"
          ]
        }
      }
    }
  }
}