IMPORTANT: No additional bug fixes or documentation updates will be released for this version. For the latest information, see the current release documentation.

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Language analyzers

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Language analyzers

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A set of analyzers aimed at analyzing specific language text. The following types are supported: arabic, armenian, basque, bengali, brazilian, bulgarian, catalan, cjk, czech, danish, dutch, english, estonian, finnish, french, galician, german, greek, hindi, hungarian, indonesian, irish, italian, latvian, lithuanian, norwegian, persian, portuguese, romanian, russian, sorani, spanish, swedish, turkish, thai.

Configuring language analyzers

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Stopwords

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All analyzers support setting custom stopwords either internally in the config, or by using an external stopwords file by setting stopwords_path. Check Stop Analyzer for more details.

Excluding words from stemming

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The stem_exclusion parameter allows you to specify an array of lowercase words that should not be stemmed. Internally, this functionality is implemented by adding the keyword_marker token filter with the keywords set to the value of the stem_exclusion parameter.

The following analyzers support setting custom stem_exclusion list: arabic, armenian, basque, bengali, bulgarian, catalan, czech, dutch, english, finnish, french, galician, german, hindi, hungarian, indonesian, irish, italian, latvian, lithuanian, norwegian, portuguese, romanian, russian, sorani, spanish, swedish, turkish.

Reimplementing language analyzers

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The built-in language analyzers can be reimplemented as custom analyzers (as described below) in order to customize their behaviour.

If you do not intend to exclude words from being stemmed (the equivalent of the stem_exclusion parameter above), then you should remove the keyword_marker token filter from the custom analyzer configuration.

`arabic` analyzer

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The arabic analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'arabic_example',
  body: {
    settings: {
      analysis: {
        filter: {
          arabic_stop: {
            type: 'stop',
            stopwords: '_arabic_'
          },
          arabic_keywords: {
            type: 'keyword_marker',
            keywords: [
              'مثال'
            ]
          },
          arabic_stemmer: {
            type: 'stemmer',
            language: 'arabic'
          }
        },
        analyzer: {
          rebuilt_arabic: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'decimal_digit',
              'arabic_stop',
              'arabic_normalization',
              'arabic_keywords',
              'arabic_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /arabic_example
{
  "settings": {
    "analysis": {
      "filter": {
        "arabic_stop": {
          "type":       "stop",
          "stopwords":  "_arabic_" 
        },
        "arabic_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["مثال"] 
        },
        "arabic_stemmer": {
          "type":       "stemmer",
          "language":   "arabic"
        }
      },
      "analyzer": {
        "rebuilt_arabic": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "decimal_digit",
            "arabic_stop",
            "arabic_normalization",
            "arabic_keywords",
            "arabic_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`armenian` analyzer

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The armenian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'armenian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          armenian_stop: {
            type: 'stop',
            stopwords: '_armenian_'
          },
          armenian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'օրինակ'
            ]
          },
          armenian_stemmer: {
            type: 'stemmer',
            language: 'armenian'
          }
        },
        analyzer: {
          rebuilt_armenian: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'armenian_stop',
              'armenian_keywords',
              'armenian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /armenian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "armenian_stop": {
          "type":       "stop",
          "stopwords":  "_armenian_" 
        },
        "armenian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["օրինակ"] 
        },
        "armenian_stemmer": {
          "type":       "stemmer",
          "language":   "armenian"
        }
      },
      "analyzer": {
        "rebuilt_armenian": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "armenian_stop",
            "armenian_keywords",
            "armenian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`basque` analyzer

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The basque analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'basque_example',
  body: {
    settings: {
      analysis: {
        filter: {
          basque_stop: {
            type: 'stop',
            stopwords: '_basque_'
          },
          basque_keywords: {
            type: 'keyword_marker',
            keywords: [
              'Adibidez'
            ]
          },
          basque_stemmer: {
            type: 'stemmer',
            language: 'basque'
          }
        },
        analyzer: {
          rebuilt_basque: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'basque_stop',
              'basque_keywords',
              'basque_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /basque_example
{
  "settings": {
    "analysis": {
      "filter": {
        "basque_stop": {
          "type":       "stop",
          "stopwords":  "_basque_" 
        },
        "basque_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["Adibidez"] 
        },
        "basque_stemmer": {
          "type":       "stemmer",
          "language":   "basque"
        }
      },
      "analyzer": {
        "rebuilt_basque": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "basque_stop",
            "basque_keywords",
            "basque_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`bengali` analyzer

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The bengali analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'bengali_example',
  body: {
    settings: {
      analysis: {
        filter: {
          bengali_stop: {
            type: 'stop',
            stopwords: '_bengali_'
          },
          bengali_keywords: {
            type: 'keyword_marker',
            keywords: [
              'উদাহরণ'
            ]
          },
          bengali_stemmer: {
            type: 'stemmer',
            language: 'bengali'
          }
        },
        analyzer: {
          rebuilt_bengali: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'decimal_digit',
              'bengali_keywords',
              'indic_normalization',
              'bengali_normalization',
              'bengali_stop',
              'bengali_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /bengali_example
{
  "settings": {
    "analysis": {
      "filter": {
        "bengali_stop": {
          "type":       "stop",
          "stopwords":  "_bengali_" 
        },
        "bengali_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["উদাহরণ"] 
        },
        "bengali_stemmer": {
          "type":       "stemmer",
          "language":   "bengali"
        }
      },
      "analyzer": {
        "rebuilt_bengali": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "decimal_digit",
            "bengali_keywords",
            "indic_normalization",
            "bengali_normalization",
            "bengali_stop",
            "bengali_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`brazilian` analyzer

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The brazilian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'brazilian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          brazilian_stop: {
            type: 'stop',
            stopwords: '_brazilian_'
          },
          brazilian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'exemplo'
            ]
          },
          brazilian_stemmer: {
            type: 'stemmer',
            language: 'brazilian'
          }
        },
        analyzer: {
          rebuilt_brazilian: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'brazilian_stop',
              'brazilian_keywords',
              'brazilian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /brazilian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "brazilian_stop": {
          "type":       "stop",
          "stopwords":  "_brazilian_" 
        },
        "brazilian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["exemplo"] 
        },
        "brazilian_stemmer": {
          "type":       "stemmer",
          "language":   "brazilian"
        }
      },
      "analyzer": {
        "rebuilt_brazilian": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "brazilian_stop",
            "brazilian_keywords",
            "brazilian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`bulgarian` analyzer

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The bulgarian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'bulgarian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          bulgarian_stop: {
            type: 'stop',
            stopwords: '_bulgarian_'
          },
          bulgarian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'пример'
            ]
          },
          bulgarian_stemmer: {
            type: 'stemmer',
            language: 'bulgarian'
          }
        },
        analyzer: {
          rebuilt_bulgarian: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'bulgarian_stop',
              'bulgarian_keywords',
              'bulgarian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /bulgarian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "bulgarian_stop": {
          "type":       "stop",
          "stopwords":  "_bulgarian_" 
        },
        "bulgarian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["пример"] 
        },
        "bulgarian_stemmer": {
          "type":       "stemmer",
          "language":   "bulgarian"
        }
      },
      "analyzer": {
        "rebuilt_bulgarian": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "bulgarian_stop",
            "bulgarian_keywords",
            "bulgarian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`catalan` analyzer

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The catalan analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'catalan_example',
  body: {
    settings: {
      analysis: {
        filter: {
          catalan_elision: {
            type: 'elision',
            articles: [
              'd',
              'l',
              'm',
              'n',
              's',
              't'
            ],
            articles_case: true
          },
          catalan_stop: {
            type: 'stop',
            stopwords: '_catalan_'
          },
          catalan_keywords: {
            type: 'keyword_marker',
            keywords: [
              'example'
            ]
          },
          catalan_stemmer: {
            type: 'stemmer',
            language: 'catalan'
          }
        },
        analyzer: {
          rebuilt_catalan: {
            tokenizer: 'standard',
            filter: [
              'catalan_elision',
              'lowercase',
              'catalan_stop',
              'catalan_keywords',
              'catalan_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /catalan_example
{
  "settings": {
    "analysis": {
      "filter": {
        "catalan_elision": {
          "type":       "elision",
          "articles":   [ "d", "l", "m", "n", "s", "t"],
          "articles_case": true
        },
        "catalan_stop": {
          "type":       "stop",
          "stopwords":  "_catalan_" 
        },
        "catalan_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["example"] 
        },
        "catalan_stemmer": {
          "type":       "stemmer",
          "language":   "catalan"
        }
      },
      "analyzer": {
        "rebuilt_catalan": {
          "tokenizer":  "standard",
          "filter": [
            "catalan_elision",
            "lowercase",
            "catalan_stop",
            "catalan_keywords",
            "catalan_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`cjk` analyzer

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You may find that icu_analyzer in the ICU analysis plugin works better for CJK text than the cjk analyzer. Experiment with your text and queries.

The cjk analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'cjk_example',
  body: {
    settings: {
      analysis: {
        filter: {
          english_stop: {
            type: 'stop',
            stopwords: [
              'a',
              'and',
              'are',
              'as',
              'at',
              'be',
              'but',
              'by',
              'for',
              'if',
              'in',
              'into',
              'is',
              'it',
              'no',
              'not',
              'of',
              'on',
              'or',
              's',
              'such',
              't',
              'that',
              'the',
              'their',
              'then',
              'there',
              'these',
              'they',
              'this',
              'to',
              'was',
              'will',
              'with',
              'www'
            ]
          }
        },
        analyzer: {
          rebuilt_cjk: {
            tokenizer: 'standard',
            filter: [
              'cjk_width',
              'lowercase',
              'cjk_bigram',
              'english_stop'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /cjk_example
{
  "settings": {
    "analysis": {
      "filter": {
        "english_stop": {
          "type":       "stop",
          "stopwords":  [ 
            "a", "and", "are", "as", "at", "be", "but", "by", "for",
            "if", "in", "into", "is", "it", "no", "not", "of", "on",
            "or", "s", "such", "t", "that", "the", "their", "then",
            "there", "these", "they", "this", "to", "was", "will",
            "with", "www"
          ]
        }
      },
      "analyzer": {
        "rebuilt_cjk": {
          "tokenizer":  "standard",
          "filter": [
            "cjk_width",
            "lowercase",
            "cjk_bigram",
            "english_stop"
          ]
        }
      }
    }
  }
}

The default stopwords can be overridden with the stopwords or stopwords_path parameters. The default stop words are almost the same as the _english_ set, but not exactly the same.

`czech` analyzer

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The czech analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'czech_example',
  body: {
    settings: {
      analysis: {
        filter: {
          czech_stop: {
            type: 'stop',
            stopwords: '_czech_'
          },
          czech_keywords: {
            type: 'keyword_marker',
            keywords: [
              'příklad'
            ]
          },
          czech_stemmer: {
            type: 'stemmer',
            language: 'czech'
          }
        },
        analyzer: {
          rebuilt_czech: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'czech_stop',
              'czech_keywords',
              'czech_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /czech_example
{
  "settings": {
    "analysis": {
      "filter": {
        "czech_stop": {
          "type":       "stop",
          "stopwords":  "_czech_" 
        },
        "czech_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["příklad"] 
        },
        "czech_stemmer": {
          "type":       "stemmer",
          "language":   "czech"
        }
      },
      "analyzer": {
        "rebuilt_czech": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "czech_stop",
            "czech_keywords",
            "czech_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`danish` analyzer

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The danish analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'danish_example',
  body: {
    settings: {
      analysis: {
        filter: {
          danish_stop: {
            type: 'stop',
            stopwords: '_danish_'
          },
          danish_keywords: {
            type: 'keyword_marker',
            keywords: [
              'eksempel'
            ]
          },
          danish_stemmer: {
            type: 'stemmer',
            language: 'danish'
          }
        },
        analyzer: {
          rebuilt_danish: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'danish_stop',
              'danish_keywords',
              'danish_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /danish_example
{
  "settings": {
    "analysis": {
      "filter": {
        "danish_stop": {
          "type":       "stop",
          "stopwords":  "_danish_" 
        },
        "danish_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["eksempel"] 
        },
        "danish_stemmer": {
          "type":       "stemmer",
          "language":   "danish"
        }
      },
      "analyzer": {
        "rebuilt_danish": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "danish_stop",
            "danish_keywords",
            "danish_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`dutch` analyzer

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The dutch analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'dutch_example',
  body: {
    settings: {
      analysis: {
        filter: {
          dutch_stop: {
            type: 'stop',
            stopwords: '_dutch_'
          },
          dutch_keywords: {
            type: 'keyword_marker',
            keywords: [
              'voorbeeld'
            ]
          },
          dutch_stemmer: {
            type: 'stemmer',
            language: 'dutch'
          },
          dutch_override: {
            type: 'stemmer_override',
            rules: [
              'fiets=>fiets',
              'bromfiets=>bromfiets',
              'ei=>eier',
              'kind=>kinder'
            ]
          }
        },
        analyzer: {
          rebuilt_dutch: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'dutch_stop',
              'dutch_keywords',
              'dutch_override',
              'dutch_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /dutch_example
{
  "settings": {
    "analysis": {
      "filter": {
        "dutch_stop": {
          "type":       "stop",
          "stopwords":  "_dutch_" 
        },
        "dutch_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["voorbeeld"] 
        },
        "dutch_stemmer": {
          "type":       "stemmer",
          "language":   "dutch"
        },
        "dutch_override": {
          "type":       "stemmer_override",
          "rules": [
            "fiets=>fiets",
            "bromfiets=>bromfiets",
            "ei=>eier",
            "kind=>kinder"
          ]
        }
      },
      "analyzer": {
        "rebuilt_dutch": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "dutch_stop",
            "dutch_keywords",
            "dutch_override",
            "dutch_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`english` analyzer

edit

The english analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'english_example',
  body: {
    settings: {
      analysis: {
        filter: {
          english_stop: {
            type: 'stop',
            stopwords: '_english_'
          },
          english_keywords: {
            type: 'keyword_marker',
            keywords: [
              'example'
            ]
          },
          english_stemmer: {
            type: 'stemmer',
            language: 'english'
          },
          english_possessive_stemmer: {
            type: 'stemmer',
            language: 'possessive_english'
          }
        },
        analyzer: {
          rebuilt_english: {
            tokenizer: 'standard',
            filter: [
              'english_possessive_stemmer',
              'lowercase',
              'english_stop',
              'english_keywords',
              'english_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /english_example
{
  "settings": {
    "analysis": {
      "filter": {
        "english_stop": {
          "type":       "stop",
          "stopwords":  "_english_" 
        },
        "english_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["example"] 
        },
        "english_stemmer": {
          "type":       "stemmer",
          "language":   "english"
        },
        "english_possessive_stemmer": {
          "type":       "stemmer",
          "language":   "possessive_english"
        }
      },
      "analyzer": {
        "rebuilt_english": {
          "tokenizer":  "standard",
          "filter": [
            "english_possessive_stemmer",
            "lowercase",
            "english_stop",
            "english_keywords",
            "english_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`estonian` analyzer

edit

The estonian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'estonian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          estonian_stop: {
            type: 'stop',
            stopwords: '_estonian_'
          },
          estonian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'näide'
            ]
          },
          estonian_stemmer: {
            type: 'stemmer',
            language: 'estonian'
          }
        },
        analyzer: {
          rebuilt_estonian: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'estonian_stop',
              'estonian_keywords',
              'estonian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /estonian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "estonian_stop": {
          "type":       "stop",
          "stopwords":  "_estonian_" 
        },
        "estonian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["näide"] 
        },
        "estonian_stemmer": {
          "type":       "stemmer",
          "language":   "estonian"
        }
      },
      "analyzer": {
        "rebuilt_estonian": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "estonian_stop",
            "estonian_keywords",
            "estonian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`finnish` analyzer

edit

The finnish analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'finnish_example',
  body: {
    settings: {
      analysis: {
        filter: {
          finnish_stop: {
            type: 'stop',
            stopwords: '_finnish_'
          },
          finnish_keywords: {
            type: 'keyword_marker',
            keywords: [
              'esimerkki'
            ]
          },
          finnish_stemmer: {
            type: 'stemmer',
            language: 'finnish'
          }
        },
        analyzer: {
          rebuilt_finnish: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'finnish_stop',
              'finnish_keywords',
              'finnish_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /finnish_example
{
  "settings": {
    "analysis": {
      "filter": {
        "finnish_stop": {
          "type":       "stop",
          "stopwords":  "_finnish_" 
        },
        "finnish_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["esimerkki"] 
        },
        "finnish_stemmer": {
          "type":       "stemmer",
          "language":   "finnish"
        }
      },
      "analyzer": {
        "rebuilt_finnish": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "finnish_stop",
            "finnish_keywords",
            "finnish_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`french` analyzer

edit

The french analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'french_example',
  body: {
    settings: {
      analysis: {
        filter: {
          french_elision: {
            type: 'elision',
            articles_case: true,
            articles: [
              'l',
              'm',
              't',
              'qu',
              'n',
              's',
              'j',
              'd',
              'c',
              'jusqu',
              'quoiqu',
              'lorsqu',
              'puisqu'
            ]
          },
          french_stop: {
            type: 'stop',
            stopwords: '_french_'
          },
          french_keywords: {
            type: 'keyword_marker',
            keywords: [
              'Example'
            ]
          },
          french_stemmer: {
            type: 'stemmer',
            language: 'light_french'
          }
        },
        analyzer: {
          rebuilt_french: {
            tokenizer: 'standard',
            filter: [
              'french_elision',
              'lowercase',
              'french_stop',
              'french_keywords',
              'french_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /french_example
{
  "settings": {
    "analysis": {
      "filter": {
        "french_elision": {
          "type":         "elision",
          "articles_case": true,
          "articles": [
              "l", "m", "t", "qu", "n", "s",
              "j", "d", "c", "jusqu", "quoiqu",
              "lorsqu", "puisqu"
            ]
        },
        "french_stop": {
          "type":       "stop",
          "stopwords":  "_french_" 
        },
        "french_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["Example"] 
        },
        "french_stemmer": {
          "type":       "stemmer",
          "language":   "light_french"
        }
      },
      "analyzer": {
        "rebuilt_french": {
          "tokenizer":  "standard",
          "filter": [
            "french_elision",
            "lowercase",
            "french_stop",
            "french_keywords",
            "french_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`galician` analyzer

edit

The galician analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'galician_example',
  body: {
    settings: {
      analysis: {
        filter: {
          galician_stop: {
            type: 'stop',
            stopwords: '_galician_'
          },
          galician_keywords: {
            type: 'keyword_marker',
            keywords: [
              'exemplo'
            ]
          },
          galician_stemmer: {
            type: 'stemmer',
            language: 'galician'
          }
        },
        analyzer: {
          rebuilt_galician: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'galician_stop',
              'galician_keywords',
              'galician_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /galician_example
{
  "settings": {
    "analysis": {
      "filter": {
        "galician_stop": {
          "type":       "stop",
          "stopwords":  "_galician_" 
        },
        "galician_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["exemplo"] 
        },
        "galician_stemmer": {
          "type":       "stemmer",
          "language":   "galician"
        }
      },
      "analyzer": {
        "rebuilt_galician": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "galician_stop",
            "galician_keywords",
            "galician_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`german` analyzer

edit

The german analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'german_example',
  body: {
    settings: {
      analysis: {
        filter: {
          german_stop: {
            type: 'stop',
            stopwords: '_german_'
          },
          german_keywords: {
            type: 'keyword_marker',
            keywords: [
              'Beispiel'
            ]
          },
          german_stemmer: {
            type: 'stemmer',
            language: 'light_german'
          }
        },
        analyzer: {
          rebuilt_german: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'german_stop',
              'german_keywords',
              'german_normalization',
              'german_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /german_example
{
  "settings": {
    "analysis": {
      "filter": {
        "german_stop": {
          "type":       "stop",
          "stopwords":  "_german_" 
        },
        "german_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["Beispiel"] 
        },
        "german_stemmer": {
          "type":       "stemmer",
          "language":   "light_german"
        }
      },
      "analyzer": {
        "rebuilt_german": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "german_stop",
            "german_keywords",
            "german_normalization",
            "german_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`greek` analyzer

edit

The greek analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'greek_example',
  body: {
    settings: {
      analysis: {
        filter: {
          greek_stop: {
            type: 'stop',
            stopwords: '_greek_'
          },
          greek_lowercase: {
            type: 'lowercase',
            language: 'greek'
          },
          greek_keywords: {
            type: 'keyword_marker',
            keywords: [
              'παράδειγμα'
            ]
          },
          greek_stemmer: {
            type: 'stemmer',
            language: 'greek'
          }
        },
        analyzer: {
          rebuilt_greek: {
            tokenizer: 'standard',
            filter: [
              'greek_lowercase',
              'greek_stop',
              'greek_keywords',
              'greek_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /greek_example
{
  "settings": {
    "analysis": {
      "filter": {
        "greek_stop": {
          "type":       "stop",
          "stopwords":  "_greek_" 
        },
        "greek_lowercase": {
          "type":       "lowercase",
          "language":   "greek"
        },
        "greek_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["παράδειγμα"] 
        },
        "greek_stemmer": {
          "type":       "stemmer",
          "language":   "greek"
        }
      },
      "analyzer": {
        "rebuilt_greek": {
          "tokenizer":  "standard",
          "filter": [
            "greek_lowercase",
            "greek_stop",
            "greek_keywords",
            "greek_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`hindi` analyzer

edit

The hindi analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'hindi_example',
  body: {
    settings: {
      analysis: {
        filter: {
          hindi_stop: {
            type: 'stop',
            stopwords: '_hindi_'
          },
          hindi_keywords: {
            type: 'keyword_marker',
            keywords: [
              'उदाहरण'
            ]
          },
          hindi_stemmer: {
            type: 'stemmer',
            language: 'hindi'
          }
        },
        analyzer: {
          rebuilt_hindi: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'decimal_digit',
              'hindi_keywords',
              'indic_normalization',
              'hindi_normalization',
              'hindi_stop',
              'hindi_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /hindi_example
{
  "settings": {
    "analysis": {
      "filter": {
        "hindi_stop": {
          "type":       "stop",
          "stopwords":  "_hindi_" 
        },
        "hindi_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["उदाहरण"] 
        },
        "hindi_stemmer": {
          "type":       "stemmer",
          "language":   "hindi"
        }
      },
      "analyzer": {
        "rebuilt_hindi": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "decimal_digit",
            "hindi_keywords",
            "indic_normalization",
            "hindi_normalization",
            "hindi_stop",
            "hindi_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`hungarian` analyzer

edit

The hungarian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'hungarian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          hungarian_stop: {
            type: 'stop',
            stopwords: '_hungarian_'
          },
          hungarian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'példa'
            ]
          },
          hungarian_stemmer: {
            type: 'stemmer',
            language: 'hungarian'
          }
        },
        analyzer: {
          rebuilt_hungarian: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'hungarian_stop',
              'hungarian_keywords',
              'hungarian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /hungarian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "hungarian_stop": {
          "type":       "stop",
          "stopwords":  "_hungarian_" 
        },
        "hungarian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["példa"] 
        },
        "hungarian_stemmer": {
          "type":       "stemmer",
          "language":   "hungarian"
        }
      },
      "analyzer": {
        "rebuilt_hungarian": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "hungarian_stop",
            "hungarian_keywords",
            "hungarian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`indonesian` analyzer

edit

The indonesian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'indonesian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          indonesian_stop: {
            type: 'stop',
            stopwords: '_indonesian_'
          },
          indonesian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'contoh'
            ]
          },
          indonesian_stemmer: {
            type: 'stemmer',
            language: 'indonesian'
          }
        },
        analyzer: {
          rebuilt_indonesian: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'indonesian_stop',
              'indonesian_keywords',
              'indonesian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /indonesian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "indonesian_stop": {
          "type":       "stop",
          "stopwords":  "_indonesian_" 
        },
        "indonesian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["contoh"] 
        },
        "indonesian_stemmer": {
          "type":       "stemmer",
          "language":   "indonesian"
        }
      },
      "analyzer": {
        "rebuilt_indonesian": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "indonesian_stop",
            "indonesian_keywords",
            "indonesian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`irish` analyzer

edit

The irish analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'irish_example',
  body: {
    settings: {
      analysis: {
        filter: {
          irish_hyphenation: {
            type: 'stop',
            stopwords: [
              'h',
              'n',
              't'
            ],
            ignore_case: true
          },
          irish_elision: {
            type: 'elision',
            articles: [
              'd',
              'm',
              'b'
            ],
            articles_case: true
          },
          irish_stop: {
            type: 'stop',
            stopwords: '_irish_'
          },
          irish_lowercase: {
            type: 'lowercase',
            language: 'irish'
          },
          irish_keywords: {
            type: 'keyword_marker',
            keywords: [
              'sampla'
            ]
          },
          irish_stemmer: {
            type: 'stemmer',
            language: 'irish'
          }
        },
        analyzer: {
          rebuilt_irish: {
            tokenizer: 'standard',
            filter: [
              'irish_hyphenation',
              'irish_elision',
              'irish_lowercase',
              'irish_stop',
              'irish_keywords',
              'irish_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /irish_example
{
  "settings": {
    "analysis": {
      "filter": {
        "irish_hyphenation": {
          "type":       "stop",
          "stopwords":  [ "h", "n", "t" ],
          "ignore_case": true
        },
        "irish_elision": {
          "type":       "elision",
          "articles":   [ "d", "m", "b" ],
          "articles_case": true
        },
        "irish_stop": {
          "type":       "stop",
          "stopwords":  "_irish_" 
        },
        "irish_lowercase": {
          "type":       "lowercase",
          "language":   "irish"
        },
        "irish_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["sampla"] 
        },
        "irish_stemmer": {
          "type":       "stemmer",
          "language":   "irish"
        }
      },
      "analyzer": {
        "rebuilt_irish": {
          "tokenizer":  "standard",
          "filter": [
            "irish_hyphenation",
            "irish_elision",
            "irish_lowercase",
            "irish_stop",
            "irish_keywords",
            "irish_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`italian` analyzer

edit

The italian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'italian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          italian_elision: {
            type: 'elision',
            articles: [
              'c',
              'l',
              'all',
              'dall',
              'dell',
              'nell',
              'sull',
              'coll',
              'pell',
              'gl',
              'agl',
              'dagl',
              'degl',
              'negl',
              'sugl',
              'un',
              'm',
              't',
              's',
              'v',
              'd'
            ],
            articles_case: true
          },
          italian_stop: {
            type: 'stop',
            stopwords: '_italian_'
          },
          italian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'esempio'
            ]
          },
          italian_stemmer: {
            type: 'stemmer',
            language: 'light_italian'
          }
        },
        analyzer: {
          rebuilt_italian: {
            tokenizer: 'standard',
            filter: [
              'italian_elision',
              'lowercase',
              'italian_stop',
              'italian_keywords',
              'italian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /italian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "italian_elision": {
          "type": "elision",
          "articles": [
                "c", "l", "all", "dall", "dell",
                "nell", "sull", "coll", "pell",
                "gl", "agl", "dagl", "degl", "negl",
                "sugl", "un", "m", "t", "s", "v", "d"
          ],
          "articles_case": true
        },
        "italian_stop": {
          "type":       "stop",
          "stopwords":  "_italian_" 
        },
        "italian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["esempio"] 
        },
        "italian_stemmer": {
          "type":       "stemmer",
          "language":   "light_italian"
        }
      },
      "analyzer": {
        "rebuilt_italian": {
          "tokenizer":  "standard",
          "filter": [
            "italian_elision",
            "lowercase",
            "italian_stop",
            "italian_keywords",
            "italian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`latvian` analyzer

edit

The latvian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'latvian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          latvian_stop: {
            type: 'stop',
            stopwords: '_latvian_'
          },
          latvian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'piemērs'
            ]
          },
          latvian_stemmer: {
            type: 'stemmer',
            language: 'latvian'
          }
        },
        analyzer: {
          rebuilt_latvian: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'latvian_stop',
              'latvian_keywords',
              'latvian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /latvian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "latvian_stop": {
          "type":       "stop",
          "stopwords":  "_latvian_" 
        },
        "latvian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["piemērs"] 
        },
        "latvian_stemmer": {
          "type":       "stemmer",
          "language":   "latvian"
        }
      },
      "analyzer": {
        "rebuilt_latvian": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "latvian_stop",
            "latvian_keywords",
            "latvian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`lithuanian` analyzer

edit

The lithuanian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'lithuanian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          lithuanian_stop: {
            type: 'stop',
            stopwords: '_lithuanian_'
          },
          lithuanian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'pavyzdys'
            ]
          },
          lithuanian_stemmer: {
            type: 'stemmer',
            language: 'lithuanian'
          }
        },
        analyzer: {
          rebuilt_lithuanian: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'lithuanian_stop',
              'lithuanian_keywords',
              'lithuanian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /lithuanian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "lithuanian_stop": {
          "type":       "stop",
          "stopwords":  "_lithuanian_" 
        },
        "lithuanian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["pavyzdys"] 
        },
        "lithuanian_stemmer": {
          "type":       "stemmer",
          "language":   "lithuanian"
        }
      },
      "analyzer": {
        "rebuilt_lithuanian": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "lithuanian_stop",
            "lithuanian_keywords",
            "lithuanian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`norwegian` analyzer

edit

The norwegian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'norwegian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          norwegian_stop: {
            type: 'stop',
            stopwords: '_norwegian_'
          },
          norwegian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'eksempel'
            ]
          },
          norwegian_stemmer: {
            type: 'stemmer',
            language: 'norwegian'
          }
        },
        analyzer: {
          rebuilt_norwegian: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'norwegian_stop',
              'norwegian_keywords',
              'norwegian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /norwegian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "norwegian_stop": {
          "type":       "stop",
          "stopwords":  "_norwegian_" 
        },
        "norwegian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["eksempel"] 
        },
        "norwegian_stemmer": {
          "type":       "stemmer",
          "language":   "norwegian"
        }
      },
      "analyzer": {
        "rebuilt_norwegian": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "norwegian_stop",
            "norwegian_keywords",
            "norwegian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`persian` analyzer

edit

The persian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'persian_example',
  body: {
    settings: {
      analysis: {
        char_filter: {
          zero_width_spaces: {
            type: 'mapping',
            mappings: [
              '\\u200C=>\\u0020'
            ]
          }
        },
        filter: {
          persian_stop: {
            type: 'stop',
            stopwords: '_persian_'
          }
        },
        analyzer: {
          rebuilt_persian: {
            tokenizer: 'standard',
            char_filter: [
              'zero_width_spaces'
            ],
            filter: [
              'lowercase',
              'decimal_digit',
              'arabic_normalization',
              'persian_normalization',
              'persian_stop'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /persian_example
{
  "settings": {
    "analysis": {
      "char_filter": {
        "zero_width_spaces": {
            "type":       "mapping",
            "mappings": [ "\\u200C=>\\u0020"] 
        }
      },
      "filter": {
        "persian_stop": {
          "type":       "stop",
          "stopwords":  "_persian_" 
        }
      },
      "analyzer": {
        "rebuilt_persian": {
          "tokenizer":     "standard",
          "char_filter": [ "zero_width_spaces" ],
          "filter": [
            "lowercase",
            "decimal_digit",
            "arabic_normalization",
            "persian_normalization",
            "persian_stop"
          ]
        }
      }
    }
  }
}

	Replaces zero-width non-joiners with an ASCII space.
	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.

`portuguese` analyzer

edit

The portuguese analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'portuguese_example',
  body: {
    settings: {
      analysis: {
        filter: {
          portuguese_stop: {
            type: 'stop',
            stopwords: '_portuguese_'
          },
          portuguese_keywords: {
            type: 'keyword_marker',
            keywords: [
              'exemplo'
            ]
          },
          portuguese_stemmer: {
            type: 'stemmer',
            language: 'light_portuguese'
          }
        },
        analyzer: {
          rebuilt_portuguese: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'portuguese_stop',
              'portuguese_keywords',
              'portuguese_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /portuguese_example
{
  "settings": {
    "analysis": {
      "filter": {
        "portuguese_stop": {
          "type":       "stop",
          "stopwords":  "_portuguese_" 
        },
        "portuguese_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["exemplo"] 
        },
        "portuguese_stemmer": {
          "type":       "stemmer",
          "language":   "light_portuguese"
        }
      },
      "analyzer": {
        "rebuilt_portuguese": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "portuguese_stop",
            "portuguese_keywords",
            "portuguese_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`romanian` analyzer

edit

The romanian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'romanian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          romanian_stop: {
            type: 'stop',
            stopwords: '_romanian_'
          },
          romanian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'exemplu'
            ]
          },
          romanian_stemmer: {
            type: 'stemmer',
            language: 'romanian'
          }
        },
        analyzer: {
          rebuilt_romanian: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'romanian_stop',
              'romanian_keywords',
              'romanian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /romanian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "romanian_stop": {
          "type":       "stop",
          "stopwords":  "_romanian_" 
        },
        "romanian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["exemplu"] 
        },
        "romanian_stemmer": {
          "type":       "stemmer",
          "language":   "romanian"
        }
      },
      "analyzer": {
        "rebuilt_romanian": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "romanian_stop",
            "romanian_keywords",
            "romanian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`russian` analyzer

edit

The russian analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'russian_example',
  body: {
    settings: {
      analysis: {
        filter: {
          russian_stop: {
            type: 'stop',
            stopwords: '_russian_'
          },
          russian_keywords: {
            type: 'keyword_marker',
            keywords: [
              'пример'
            ]
          },
          russian_stemmer: {
            type: 'stemmer',
            language: 'russian'
          }
        },
        analyzer: {
          rebuilt_russian: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'russian_stop',
              'russian_keywords',
              'russian_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /russian_example
{
  "settings": {
    "analysis": {
      "filter": {
        "russian_stop": {
          "type":       "stop",
          "stopwords":  "_russian_" 
        },
        "russian_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["пример"] 
        },
        "russian_stemmer": {
          "type":       "stemmer",
          "language":   "russian"
        }
      },
      "analyzer": {
        "rebuilt_russian": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "russian_stop",
            "russian_keywords",
            "russian_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`sorani` analyzer

edit

The sorani analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'sorani_example',
  body: {
    settings: {
      analysis: {
        filter: {
          sorani_stop: {
            type: 'stop',
            stopwords: '_sorani_'
          },
          sorani_keywords: {
            type: 'keyword_marker',
            keywords: [
              'mînak'
            ]
          },
          sorani_stemmer: {
            type: 'stemmer',
            language: 'sorani'
          }
        },
        analyzer: {
          rebuilt_sorani: {
            tokenizer: 'standard',
            filter: [
              'sorani_normalization',
              'lowercase',
              'decimal_digit',
              'sorani_stop',
              'sorani_keywords',
              'sorani_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /sorani_example
{
  "settings": {
    "analysis": {
      "filter": {
        "sorani_stop": {
          "type":       "stop",
          "stopwords":  "_sorani_" 
        },
        "sorani_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["mînak"] 
        },
        "sorani_stemmer": {
          "type":       "stemmer",
          "language":   "sorani"
        }
      },
      "analyzer": {
        "rebuilt_sorani": {
          "tokenizer":  "standard",
          "filter": [
            "sorani_normalization",
            "lowercase",
            "decimal_digit",
            "sorani_stop",
            "sorani_keywords",
            "sorani_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`spanish` analyzer

edit

The spanish analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'spanish_example',
  body: {
    settings: {
      analysis: {
        filter: {
          spanish_stop: {
            type: 'stop',
            stopwords: '_spanish_'
          },
          spanish_keywords: {
            type: 'keyword_marker',
            keywords: [
              'ejemplo'
            ]
          },
          spanish_stemmer: {
            type: 'stemmer',
            language: 'light_spanish'
          }
        },
        analyzer: {
          rebuilt_spanish: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'spanish_stop',
              'spanish_keywords',
              'spanish_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /spanish_example
{
  "settings": {
    "analysis": {
      "filter": {
        "spanish_stop": {
          "type":       "stop",
          "stopwords":  "_spanish_" 
        },
        "spanish_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["ejemplo"] 
        },
        "spanish_stemmer": {
          "type":       "stemmer",
          "language":   "light_spanish"
        }
      },
      "analyzer": {
        "rebuilt_spanish": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "spanish_stop",
            "spanish_keywords",
            "spanish_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`swedish` analyzer

edit

The swedish analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'swedish_example',
  body: {
    settings: {
      analysis: {
        filter: {
          swedish_stop: {
            type: 'stop',
            stopwords: '_swedish_'
          },
          swedish_keywords: {
            type: 'keyword_marker',
            keywords: [
              'exempel'
            ]
          },
          swedish_stemmer: {
            type: 'stemmer',
            language: 'swedish'
          }
        },
        analyzer: {
          rebuilt_swedish: {
            tokenizer: 'standard',
            filter: [
              'lowercase',
              'swedish_stop',
              'swedish_keywords',
              'swedish_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /swedish_example
{
  "settings": {
    "analysis": {
      "filter": {
        "swedish_stop": {
          "type":       "stop",
          "stopwords":  "_swedish_" 
        },
        "swedish_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["exempel"] 
        },
        "swedish_stemmer": {
          "type":       "stemmer",
          "language":   "swedish"
        }
      },
      "analyzer": {
        "rebuilt_swedish": {
          "tokenizer":  "standard",
          "filter": [
            "lowercase",
            "swedish_stop",
            "swedish_keywords",
            "swedish_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`turkish` analyzer

edit

The turkish analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'turkish_example',
  body: {
    settings: {
      analysis: {
        filter: {
          turkish_stop: {
            type: 'stop',
            stopwords: '_turkish_'
          },
          turkish_lowercase: {
            type: 'lowercase',
            language: 'turkish'
          },
          turkish_keywords: {
            type: 'keyword_marker',
            keywords: [
              'örnek'
            ]
          },
          turkish_stemmer: {
            type: 'stemmer',
            language: 'turkish'
          }
        },
        analyzer: {
          rebuilt_turkish: {
            tokenizer: 'standard',
            filter: [
              'apostrophe',
              'turkish_lowercase',
              'turkish_stop',
              'turkish_keywords',
              'turkish_stemmer'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /turkish_example
{
  "settings": {
    "analysis": {
      "filter": {
        "turkish_stop": {
          "type":       "stop",
          "stopwords":  "_turkish_" 
        },
        "turkish_lowercase": {
          "type":       "lowercase",
          "language":   "turkish"
        },
        "turkish_keywords": {
          "type":       "keyword_marker",
          "keywords":   ["örnek"] 
        },
        "turkish_stemmer": {
          "type":       "stemmer",
          "language":   "turkish"
        }
      },
      "analyzer": {
        "rebuilt_turkish": {
          "tokenizer":  "standard",
          "filter": [
            "apostrophe",
            "turkish_lowercase",
            "turkish_stop",
            "turkish_keywords",
            "turkish_stemmer"
          ]
        }
      }
    }
  }
}

	The default stopwords can be overridden with the `stopwords` or `stopwords_path` parameters.
	This filter should be removed unless there are words which should be excluded from stemming.

`thai` analyzer

edit

The thai analyzer could be reimplemented as a custom analyzer as follows:

response = client.indices.create(
  index: 'thai_example',
  body: {
    settings: {
      analysis: {
        filter: {
          thai_stop: {
            type: 'stop',
            stopwords: '_thai_'
          }
        },
        analyzer: {
          rebuilt_thai: {
            tokenizer: 'thai',
            filter: [
              'lowercase',
              'decimal_digit',
              'thai_stop'
            ]
          }
        }
      }
    }
  }
)
puts response

PUT /thai_example
{
  "settings": {
    "analysis": {
      "filter": {
        "thai_stop": {
          "type":       "stop",
          "stopwords":  "_thai_" 
        }
      },
      "analyzer": {
        "rebuilt_thai": {
          "tokenizer":  "thai",
          "filter": [
            "lowercase",
            "decimal_digit",
            "thai_stop"
          ]
        }
      }
    }
  }
}

The default stopwords can be overridden with the stopwords or stopwords_path parameters.

« Keyword analyzer Pattern analyzer »

Language analyzers

Language analyzers

Configuring language analyzers

Stopwords

Excluding words from stemming

Reimplementing language analyzers

arabic analyzer

armenian analyzer

basque analyzer

bengali analyzer

brazilian analyzer

bulgarian analyzer

catalan analyzer

cjk analyzer

czech analyzer

danish analyzer

dutch analyzer

english analyzer

estonian analyzer

finnish analyzer

french analyzer

galician analyzer

german analyzer

greek analyzer

hindi analyzer

hungarian analyzer

indonesian analyzer

irish analyzer

italian analyzer

latvian analyzer

lithuanian analyzer

norwegian analyzer

persian analyzer

portuguese analyzer

romanian analyzer

russian analyzer

sorani analyzer

spanish analyzer

swedish analyzer

turkish analyzer

thai analyzer

`arabic` analyzer

`armenian` analyzer

`basque` analyzer

`bengali` analyzer

`brazilian` analyzer

`bulgarian` analyzer

`catalan` analyzer

`cjk` analyzer

`czech` analyzer

`danish` analyzer

`dutch` analyzer

`english` analyzer

`estonian` analyzer

`finnish` analyzer

`french` analyzer

`galician` analyzer

`german` analyzer

`greek` analyzer

`hindi` analyzer

`hungarian` analyzer

`indonesian` analyzer

`irish` analyzer

`italian` analyzer

`latvian` analyzer

`lithuanian` analyzer

`norwegian` analyzer

`persian` analyzer

`portuguese` analyzer

`romanian` analyzer

`russian` analyzer

`sorani` analyzer

`spanish` analyzer

`swedish` analyzer

`turkish` analyzer

`thai` analyzer