Normalizer

The normalizer mapping parameter defines a custom normalization process for keyword fields. Unlike analyzers for text fields, which generate multiple tokens, normalizers transform the entire field value into a single token using a set of token filters. When you define a normalizer, the keyword field is processed by the specified filters before it is stored while keeping the _source of the document unchanged.

Defining a normalizer

The following request creates an index named products with a custom normalizer called my_normalizer. The normalizer is applied to the code field, which uses the trim and lowercase filters:

PUT /products { "settings": { "analysis": { "normalizer": { "my_normalizer": { "type": "custom", "filter": ["trim", "lowercase"] } } } }, "mappings": { "properties": { "code": { "type": "keyword", "normalizer": "my_normalizer" } } } } 

When you ingest a document into the index, the code field is normalized by trimming any extra spaces and converting the text to lowercase:

PUT /products/_doc/1 { "code": " ABC-123 EXTRA " } 

Search for the indexed document using lowercase and trimmed text in the query:

POST /products/_search { "query": { "term": { "code": "abc-123 extra" } } } 

Because the code field is normalized, the term query successfully matches the stored document:

{ ... "hits": { "total": { "value": 1, "relation": "eq" }, "max_score": 0.2876821, "hits": [ { "_index": "products", "_id": "1", "_score": 0.2876821, "_source": { "code": " ABC-123 EXTRA " } } ] } }