:Search analyzers

A TairSearch analyzer consists of character filters, a tokenizer, and token filters, which are applied sequentially. Character filters and token filters can be left empty. Description:

• Character filter: preprocesses documents. You can configure zero or more character filters that run in the specified sequence for a TairSearch analyzer. For example, a character filter can replace "(:" with "happy".

• Tokenizer: splits a document into multiple tokens. You can specify only a single tokenizer for each TairSearch analyzer. For example, you can use the whitespace tokenizer to split "I am very happy" into ["I", "am", "very", "happy"].

• Token filter: processes the tokens that are generated by the specified tokenizer. You can configure zero or more token filters that run in the specified sequence for a TairSearch analyzer. For example, you can use the stop token filter to filter stop words.

Components:

• Tokenizer: standard

• Token filters: lowercase and stop

Optional parameters:

• stopwords: the stop words to be filtered out. Data type: ARRAY. Each stop word must be a string. After you specify this parameter, the default stop words are overwritten. Default stop words:

  ["a", "an", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]

• max_token_length: the maximum number of characters that are allowed for a token. Default value: 255. Tokens that exceed the maximum length are split based on the specified maximum length.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"standard"
      }
    }
  }
}

# Use of custom stop words:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_analyzer":{
          "type":"standard",
          "max_token_length":10,
          "stopwords":[
            "memory",
            "disk",
            "is",
            "a"
          ]
        }
      }
    }
  }
}

Components:

• Tokenizer: lowercase

• Token filter: stop

Optional parameters:

• stopwords: the stop words to be filtered out. Data type: ARRAY. Each stop word must be a string. After you specify this parameter, the default stop words are overwritten. Default stop words:

  ["a", "an", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"stop"
      }
    }
  }
}

# Use of custom stop words:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_analyzer":{
          "type":"stop",
          "stopwords":[
            "memory",
            "disk",
            "is",
            "a"
          ]
        }
      }
    }
  }
}

Components:

• Tokenizer: jieba

• Token filters: lowercase and stop

Optional parameters:

• userwords: a dictionary of user-defined words. Data type: ARRAY. Each word must be a string. After you specify this parameter, the user-defined words are added to the default dictionary. For more information, see the default dictionary of jieba.

  Important

  • The jieba analyzer has a large built-in dictionary that is 20 MB in size. Only a single copy of this dictionary is retained in the memory of jieba. This dictionary is loaded only when jieba is used for the first time. This may cause a slight jitter in the latency while using jieba.

  • Words in the custom dictionary cannot contain spaces or the following special characters: \t, \n, ，, and 。 .

• use_hmm: specifies whether to use a hidden Markov model (HMM) to handle words that are not included in the dictionary. Valid values: true and false. Default value: true.

• stopwords: the stop words to be filtered out. Data type: ARRAY. Each stop word must be a string. After you specify this parameter, the default stop words are overwritten. For more information, see the default stop words of jieba.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"jieba"
      }
    }
  }
}

# Use of custom stop words:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_analyzer":{
          "type":"jieba",
          "stopwords":[
            "memory",
            "disk",
            "is",
            "a"
          ],"userwords":[
            "Redis",
            "open-source",
            "flexible"
          ],
          "use_hmm":true
        }
      }
    }
  }
}

Components:

• Tokenizer: IK

Optional parameters:

• stopwords: the stop words to be filtered out. Data type: ARRAY. Each stop word must be a string. After you specify this parameter, the default stop words are overwritten. Default stop words:

  ["a", "an", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]

• userwords: a dictionary of user-defined words. Data type: ARRAY. Each word must be a string. After you specify this parameter, the user-defined words are added to the default dictionary. For more information, see the default dictionary of IK.

• quantifiers: a dictionary of user-defined quantifiers. Data type: ARRAY. After you specify this parameter, the user-defined quantifiers are added to the default dictionary. For more information, see the default quantifier dictionary of IK.

• enable_lowercase: specifies whether to convert uppercase letters to lowercase letters. Valid values: true and false. Default value: true.

  Important

  If the custom dictionary contains uppercase letters, set this parameter to false because the conversion is performed before a document is split.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"ik_smart"
      },
      "f1":{
        "type":"text",
        "analyzer":"ik_max_word"
      }
    }
  }
}

# Use of custom stop words:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_ik_smart_analyzer"
      },
      "f1":{
        "type":"text",
        "analyzer":"my_ik_max_word_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_ik_smart_analyzer":{
          "type":"ik_smart",
          "stopwords":[
            "memory",
            "disk",
            "is",
            "a"
          ],"userwords":[
            "Redis",
            "open-source",
            "flexible"
          ],
          "quantifiers":[
            "ns"
          ],
          "enable_lowercase":false
        },
        "my_ik_max_word_analyzer":{
          "type":"ik_max_word",
          "stopwords":[
            "memory",
            "disk",
            "is",
            "a"
          ],"userwords":[
            "Redis",
            "open-source",
            "flexible"
          ],
          "quantifiers":[
            "ns"
          ],
          "enable_lowercase":false
        }
      }
    }
  }
}

Components:

• Tokenizer: pattern

• Token filters: lowercase and stop

Optional parameters:

• pattern: the regular expression. The words that are matched by the regular expression are used as delimiters. Default value: \W+. For more information about the syntax of regular expressions, visit GitHub.

• stopwords: the stop words to be filtered out. The dictionary of stop words must be an array, and each stop word must be a string. After you specify stop words, the default stop words are overwritten. Default stop words:

  ["a", "an", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]

• lowercase: specifies whether to convert tokens to lowercase letters. Valid values: true and false. Default value: true.

• flags: specifies whether the regular expression is case-sensitive. By default, this parameter is left empty, which indicates that the regular expression is case-sensitive. A value of CASE_INSENSITIVE indicates that the regular expression is case-insensitive.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"pattern"
      }
    }
  }
}

# Use of custom stop words:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_analyzer":{
          "type":"pattern",
          "pattern":"\\'([^\\']+)\\'",
          "stopwords":[
            "aaa",
            "@"
          ],
          "lowercase":false,
          "flags":"CASE_INSENSITIVE"
        }
      }
    }
  }
}

Components:

• Tokenizer: whitespace

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"whitespace"
      }
    }
  }
}

Components:

• Tokenizer: lowercase

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"simple"
      }
    }
  }
}

Components:

• Tokenizer: keyword

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"keyword"
      }
    }
  }
}

Optional parameters:

• stopwords: the stop words to be filtered out. The dictionary of stop words must be an array, and each stop word must be a string. After you specify stop words, the default stop words are overwritten. For more information about the default stop words for different languages, see the Appendix 4: Default stop words of the built-in language analyzer for different languages section of this topic.

  Note

  You cannot modify the stop words of the chinese analyzer.

• stem_exclusion: the words whose stems are not extracted. For example, if you extract the stem of "apples", the result is "apple". By default, this parameter is left empty. The value of the stem_exclusion parameter must be an array, and each word must be a string.

  Note

  This parameter is supported only for the brazilian, german, french, and dutch analyzers.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"arabic"
      }
    }
  }
}

# Use of custom stop words:
{
    "mappings":{
        "properties":{
            "f0":{
                "type":"text",
                "analyzer":"my_analyzer"
            }
        }
    },
    "settings":{
        "analysis":{
            "analyzer":{
                "my_analyzer":{
                    "type":"german",
                    "stopwords":[
                        "ein"
                    ],
                    "stem_exclusion":[
                        "speicher"
                    ]
                }
            }
        }
    }
}

The following table describes the parameters.

Configuration example:

# Configure the custom analyzer:
# In this example, emoticons and conjunctions are specified as the character filters. In addition, the whitespace tokenizer and the lowercase and stop token filters are specified. 
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"whitespace",
          "filter":[
            "lowercase",
            "stop"
          ],
          "char_filter": [
            "emoticons",
            "conjunctions"
          ]
        }
      },
      "char_filter":{
        "emoticons":{
          "type":"mapping",
          "mappings":[
            ":) => _happy_",
            ":( => _sad_"
           ]
        },
        "conjunctions":{
          "type":"mapping",
          "mappings":[
            "&=>and"
          ]
        }
      }
    }
  }
}

Parameters:

• mappings: This parameter is required. Data type: ARRAY. Each element must include =>. Example: "&=>and".

Configuration example:

{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"standard",
          "char_filter": [
            "emoticons"
          ]
        }
      },
      "char_filter":{
        "emoticons":{
          "type":"mapping",
          "mappings":[
            ":) => _happy_",
            ":( => _sad_"
          ]
        }
      }
    }
  }
}

Optional parameters:

• max_token_length: the maximum number of characters that are allowed for a token. Default value: 255. Tokens that exceed the maximum length are split based on the specified maximum length.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"whitespace"
        }
      }
    }
  }
}

# Custom configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"token1"
        }
      },
      "tokenizer":{
        "token1":{
          "type":"whitespace",
          "max_token_length":2
        }
      }
    }
  }
}

Optional parameters:

• max_token_length: the maximum number of characters that are allowed for a token. Default value: 255. Tokens that exceed the maximum length are split based on the specified maximum length.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"standard"
        }
      }
    }
  }
}
# Custom configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"token1"
        }
      },
      "tokenizer":{
        "token1":{
          "type":"standard",
          "max_token_length":2
        }
      }
    }
  }
}

The classic tokenizer splits a document based on English grammar and handles acronyms, company names, email addresses, and IP addresses in a special way, as described in the following section:

• Splits a document by punctuation and deletes punctuations. Periods (.) without whitespaces are not considered as punctuations. For example, red.apple is not split, and red.[space] apple is split into red and apple.

• Splits a document by hyphen. If numbers are contained in a token, the token is interpreted as a product number and is not split.

• Identifies email addresses and hostnames as tokens.

Optional parameters:

• max_token_length: the maximum number of characters that are allowed for a token. Default value: 255. Tokens that exceed the maximum length are skipped.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"classic"
        }
      }
    }
  }
}
# Custom configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"token1"
        }
      },
      "tokenizer":{
        "token1":{
          "type":"classic",
          "max_token_length":2
        }
      }
    }
  }
}

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"letter"
        }
      }
    }
  }
}

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"lowercase"
        }
      }
    }
  }
}

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"keyword"
        }
      }
    }
  }
}

Optional parameters:

• userwords: a dictionary of user-defined words. Data type: ARRAY. Each word must be a string. After you specify this parameter, the user-defined words are added to the default dictionary. For more information, see the default dictionary of jieba.

  Important

  Words in the custom dictionary cannot contain spaces or the following special characters: \t, \n, ，, and 。 .

• use_hmm: specifies whether to use a hidden Markov model (HMM) to handle words that are not included in the dictionary. Valid values: true and false. Default value: true.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"jieba"
        }
      }
    }
  }
}

# Custom configuration:
{
  "mappings":{
    "properties":{
      "f1":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"token1"
        }
      },
      "tokenizer":{
        "token1":{
          "type":"jieba",
          "userwords":[
            "Redis",
            "open-source",
            "flexible"
          ],
          "use_hmm":true
        }
      }
    }
  }
}

Optional parameters:

• pattern: the regular expression. Default value: \W+. For more information, visit GitHub.

• group: uses the specified regular expression as a delimiter or token. Default value: -1. Valid values:

  • -1: uses the matched words of the specified regular expression as delimiters. For example, if you use the "aaa" regular expression to split "bbbaaaccc", the splitting results are "bbb" and "ccc".

  • 0 or an integer greater than 0: identifies words that are matched by the regular expression as tokens. A value of 0 indicates that TairSearch matches words by the whole regular expression. A value of 1 or an integer greater than 1 indicates that TairSearch matches words by the corresponding capture group in the regular expression. For example, assume that the "a(b+)c" regular expression is used to split "abbbcdefabc". If group is set to 0, the splitting results are "abbbc" and "abc". If group is set to 1, the first capture group b+ in "a(b+)c" is used to match words. In this case, the splitting results are "bbb" and "b".

• flags: specifies whether the specified regular expression is case-sensitive. By default, this parameter is left empty, which indicates that the regular expression is case-sensitive. A value of CASE_INSENSITIVE indicates that the specified regular expression is case-insensitive.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"pattern"
        }
      }
    }
  }
}

# Custom configuration:
{
  "mappings":{
    "properties":{
      "f1":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"pattern_tokenizer"
        }
      },
      "tokenizer":{
        "pattern_tokenizer":{
          "type":"pattern",
          "pattern":"AB(A(\\w+)C)",
          "flags":"CASE_INSENSITIVE",
          "group":2
        }
      }
    }
  }
}

Optional parameters:

• stopwords: the stop words to be filtered out. Data type: ARRAY. Each stop word must be a string. After you specify this parameter, the default stop words are overwritten. Default stop words:

  ["a", "an", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]

• userwords: a dictionary of user-defined words. Data type: ARRAY. Each word must be a string. After you specify this parameter, the user-defined words are added to the default dictionary. For more information, see the default dictionary of IK.

• quantifiers: a dictionary of user-defined quantifiers. Data type: ARRAY. After you specify this parameter, the user-defined quantifiers are added to the default dictionary. For more information, see the default quantifier dictionary of IK.

• enable_lowercase: specifies whether to convert uppercase letters to lowercase letters. Valid values: true and false. Default value: true.

  Important

  If the custom dictionary contains uppercase letters, set this parameter to false because the conversion is performed before a document is split.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_ik_smart_analyzer"
      },
      "f1":{
        "type":"text",
        "analyzer":"my_custom_ik_max_word_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_ik_smart_analyzer":{
          "type":"custom",
          "tokenizer":"ik_smart"
        },
        "my_custom_ik_max_word_analyzer":{
          "type":"custom",
          "tokenizer":"ik_max_word"
        }
      }
    }
  }
}

# Custom configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_ik_smart_analyzer"
      },
      "f1":{
        "type":"text",
        "analyzer":"my_custom_ik_max_word_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_ik_smart_analyzer":{
          "type":"custom",
          "tokenizer":"my_ik_smart_tokenizer"

        },
        "my_custom_ik_max_word_analyzer":{
          "type":"custom",
          "tokenizer":"my_ik_max_word_tokenizer"

        }
      },
      "tokenizer":{
        "my_ik_smart_tokenizer":{
          "type":"ik_smart",
          "userwords":[
            "The tokenizer for the Chinese language",
            "The custom stop words"
          ],
          "stopwords":[
            "about",
            "test"
          ],
          "quantifiers":[
            "ns"
          ],
          "enable_lowercase":false
        },
        "my_ik_max_word_tokenizer":{
          "type":"ik_max_word",
          "userwords":[
            "The tokenizer for the Chinese language",
            "The custom stop words"
          ],
          "stopwords":[
            "about",
            "test"
          ],
          "quantifiers":[
            "ns"
          ],
          "enable_lowercase":false
        }
      }
    }
  }
}

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"classic",
          "filter":["classic"]
        }
      }
    }
  }
}

Optional parameters:

• articles: the specified elisions. This parameter is required if you want to specify custom elisions. Data type: ARRAY. Each element in the array must be a string. Default value: ["l", "m", "t", "qu", "n", "s", "j"]. After you specify this parameter, the default value is overwritten.

• articles_case: specifies whether the elisions are case-sensitive. This parameter is optional. Valid values: true and false. Default value: false.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"whitespace",
          "filter":["elision"]
        }
      }
    }
  }
}

# Custom configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"whitespace",
          "filter":["elision_filter"]
        }
      },
      "filter":{
        "elision_filter":{
          "type":"elision",
          "articles":["l", "m", "t", "qu", "n", "s", "j"],
          "articles_case":true
        }
      }
    }
  }
}

Optional parameters:

• language: the language that the token filter uses. Valid values: greek and russian. If you do not specify this parameter, the token filter uses English.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"whitespace",
          "filter":["lowercase"]
        }
      }
    }
  }
}

# Custom configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_greek_analyzer"
      },
      "f1":{
        "type":"text",
        "analyzer":"my_custom_russian_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_greek_analyzer":{
          "type":"custom",
          "tokenizer":"whitespace",
          "filter":["greek_lowercase"]
        },
        "my_custom_russian_analyzer":{
          "type":"custom",
          "tokenizer":"whitespace",
          "filter":["russian_lowercase"]
        }
      },
      "filter":{
        "greek_lowercase":{
          "type":"lowercase",
          "language":"greek"
        },
        "russian_lowercase":{
          "type":"lowercase",
          "language":"russian"
        }
      }
    }
  }
}

Optional parameters:

• language: the language that the token filter uses. Valid values: english, german, french, and dutch. Default value: english.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"whitespace",
          "filter":["snowball"]
        }
      }
    }
  }
}

# Custom configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"standard",
          "filter":["my_filter"]
        }
      },
      "filter":{
        "my_filter":{
          "type":"snowball",
          "language":"english"
        }
      }
    }
  }
}

Optional parameters:

• stopwords: the array of stop words. Each stop word must be a string. After you specify this parameter, the default stop words are overwritten. Default stop words:

  ["a", "an", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]

• ignoreCase: specifies whether the stop words are case-sensitive. Valid values: true and false. Default value: false.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"whitespace",
          "filter":["stop"]
        }
      }
    }
  }
}

# Custom configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"standard",
          "filter":["stop_filter"]
        }
      },
      "filter":{
        "stop_filter":{
          "type":"stop",
          "stopwords":[
            "the"
          ],
          "ignore_case":true
        }
      }
    }
  }
}

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"standard",
          "filter":["asciifolding"]
        }
      }
    }
  }
}

Optional parameters:

• min: the minimum number of characters allowed for a token. Data type: INTEGER. Default value: 0.

• max: the maximum number of characters allowed for a token. Data type: INTEGER. Default value: 2^31 - 1.

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"whitespace",
          "filter":["length"]
        }
      }
    }
  }
}

# Custom configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_custom_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_custom_analyzer":{
          "type":"custom",
          "tokenizer":"whitespace",
          "filter":["length_filter"]
        }
      },
      "filter":{
        "length_filter":{
          "type":"length",
          "max":5,
          "min":2
        }
      }
    }
  }
}

Configuration example:

# Default configuration:
{
  "mappings":{
    "properties":{
      "f0":{
        "type":"text",
        "analyzer":"my_arabic_analyzer"
      },
      "f1":{
        "type":"text",
        "analyzer":"my_persian_analyzer"
      }
    }
  },
  "settings":{
    "analysis":{
      "analyzer":{
        "my_arabic_analyzer":{
          "type":"custom",
          "tokenizer":"arabic",
          "filter":["arabic_normalization"]
        },
        "my_persian_analyzer":{
          "type":"custom",
          "tokenizer":"arabic",
          "filter":["persian_normalization"]
        }
      }
    }
  }
}