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Fingerprint token filter

Sorts and removes duplicate tokens from a token stream, then concatenates the stream into a single output token.

For example, this filter changes the [ the, fox, was, very, very, quick ] token stream as follows:

Sorts the tokens alphabetically to [ fox, quick, the, very, very, was ]
Removes a duplicate instance of the very token.
Concatenates the token stream to a output single token: [fox quick the very was ]

Output tokens produced by this filter are useful for fingerprinting and clustering a body of text as described in the OpenRefine project.

This filter uses Lucene’s FingerprintFilter.

Example

The following analyze API request uses the fingerprint filter to create a single output token for the text zebra jumps over resting resting dog:

resp = client.indices.analyze(
    tokenizer="whitespace",
    filter=[
        "fingerprint"
    ],
    text="zebra jumps over resting resting dog",
)
print(resp)

response = client.indices.analyze(
  body: {
    tokenizer: 'whitespace',
    filter: [
      'fingerprint'
    ],
    text: 'zebra jumps over resting resting dog'
  }
)
puts response

const response = await client.indices.analyze({
  tokenizer: "whitespace",
  filter: ["fingerprint"],
  text: "zebra jumps over resting resting dog",
});
console.log(response);

GET _analyze
{
  "tokenizer" : "whitespace",
  "filter" : ["fingerprint"],
  "text" : "zebra jumps over resting resting dog"
}

The filter produces the following token:

[ dog jumps over resting zebra ]

Add to an analyzer

The following create index API request uses the fingerprint filter to configure a new custom analyzer.

resp = client.indices.create(
    index="fingerprint_example",
    settings={
        "analysis": {
            "analyzer": {
                "whitespace_fingerprint": {
                    "tokenizer": "whitespace",
                    "filter": [
                        "fingerprint"
                    ]
                }
            }
        }
    },
)
print(resp)

response = client.indices.create(
  index: 'fingerprint_example',
  body: {
    settings: {
      analysis: {
        analyzer: {
          whitespace_fingerprint: {
            tokenizer: 'whitespace',
            filter: [
              'fingerprint'
            ]
          }
        }
      }
    }
  }
)
puts response

const response = await client.indices.create({
  index: "fingerprint_example",
  settings: {
    analysis: {
      analyzer: {
        whitespace_fingerprint: {
          tokenizer: "whitespace",
          filter: ["fingerprint"],
        },
      },
    },
  },
});
console.log(response);

PUT fingerprint_example
{
  "settings": {
    "analysis": {
      "analyzer": {
        "whitespace_fingerprint": {
          "tokenizer": "whitespace",
          "filter": [ "fingerprint" ]
        }
      }
    }
  }
}

Configurable parameters

max_output_size: (Optional, integer) Maximum character length, including whitespace, of the output token. Defaults to 255. Concatenated tokens longer than this will result in no token output.
separator: (Optional, string) Character to use to concatenate the token stream input. Defaults to a space.

Customize

To customize the fingerprint filter, duplicate it to create the basis for a new custom token filter. You can modify the filter using its configurable parameters.

For example, the following request creates a custom fingerprint filter with that use + to concatenate token streams. The filter also limits output tokens to 100 characters or fewer.

resp = client.indices.create(
    index="custom_fingerprint_example",
    settings={
        "analysis": {
            "analyzer": {
                "whitespace_": {
                    "tokenizer": "whitespace",
                    "filter": [
                        "fingerprint_plus_concat"
                    ]
                }
            },
            "filter": {
                "fingerprint_plus_concat": {
                    "type": "fingerprint",
                    "max_output_size": 100,
                    "separator": "+"
                }
            }
        }
    },
)
print(resp)

response = client.indices.create(
  index: 'custom_fingerprint_example',
  body: {
    settings: {
      analysis: {
        analyzer: {
          whitespace_: {
            tokenizer: 'whitespace',
            filter: [
              'fingerprint_plus_concat'
            ]
          }
        },
        filter: {
          fingerprint_plus_concat: {
            type: 'fingerprint',
            max_output_size: 100,
            separator: '+'
          }
        }
      }
    }
  }
)
puts response

const response = await client.indices.create({
  index: "custom_fingerprint_example",
  settings: {
    analysis: {
      analyzer: {
        whitespace_: {
          tokenizer: "whitespace",
          filter: ["fingerprint_plus_concat"],
        },
      },
      filter: {
        fingerprint_plus_concat: {
          type: "fingerprint",
          max_output_size: 100,
          separator: "+",
        },
      },
    },
  },
});
console.log(response);

PUT custom_fingerprint_example
{
  "settings": {
    "analysis": {
      "analyzer": {
        "whitespace_": {
          "tokenizer": "whitespace",
          "filter": [ "fingerprint_plus_concat" ]
        }
      },
      "filter": {
        "fingerprint_plus_concat": {
          "type": "fingerprint",
          "max_output_size": 100,
          "separator": "+"
        }
      }
    }
  }
}

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https://www.elastic.co/guide/en/elasticsearch/reference/8.17/analysis-fingerprint-tokenfilter.html