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›Elasticsearch Guide [7.17] ›Text analysis

Normalizers

Normalizers are similar to analyzers except that they may only emit a single token. As a consequence, they do not have a tokenizer and only accept a subset of the available char filters and token filters. Only the filters that work on a per-character basis are allowed. For instance a lowercasing filter would be allowed, but not a stemming filter, which needs to look at the keyword as a whole. The current list of filters that can be used in a normalizer definition are: arabic_normalization, asciifolding, bengali_normalization, cjk_width, decimal_digit, elision, german_normalization, hindi_normalization, indic_normalization, lowercase, persian_normalization, scandinavian_folding, serbian_normalization, sorani_normalization, uppercase.

Elasticsearch ships with a lowercase built-in normalizer. For other forms of normalization, a custom configuration is required.

Custom normalizers

Custom normalizers take a list of character filters and a list of token filters.

PUT index
{
  "settings": {
    "analysis": {
      "char_filter": {
        "quote": {
          "type": "mapping",
          "mappings": [
            "« => \"",
            "» => \""
          ]
        }
      },
      "normalizer": {
        "my_normalizer": {
          "type": "custom",
          "char_filter": ["quote"],
          "filter": ["lowercase", "asciifolding"]
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "foo": {
        "type": "keyword",
        "normalizer": "my_normalizer"
      }
    }
  }
}

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https://www.elastic.co/guide/en/elasticsearch/reference/7.17/analysis-normalizers.html

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