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 is
following: 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 does not ship with built-in normalizers so far, so the only way to get one is by building a custom one. Custom normalizers take a list of char 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" } } } }