Whitespace

The whitespace tokenizer divides text into terms whenever there is a space between words.

Configuration

To configure an analyzer using the whitespace tokenizer, set tokenizer to whitespace in analyzer_params.

analyzer_params = {
    "tokenizer": "whitespace",
}

Map<String, Object> analyzerParams = new HashMap<>();
analyzerParams.put("tokenizer", "whitespace");

The whitespace tokenizer can work in conjunction with one or more filters. For example, the following code defines an analyzer that uses the whitespace tokenizer and lowercase filter:

analyzer_params = {
    "tokenizer": "whitespace",
    "filter": ["lowercase"]
}

Map<String, Object> analyzerParams = new HashMap<>();
analyzerParams.put("tokenizer", "whitespace");
analyzerParams.put("filter", Collections.singletonList("lowercase"));

After defining analyzer_params, you can apply them to a VARCHAR field when defining a collection schema. This allows Milvus to process the text in that field using the specified analyzer for efficient tokenization and filtering. For details, refer to Example use.

Example output

Here’s an example of how the whitespace tokenizer processes text:

Original text:

"The Milvus vector database is built for scale!"

Expected output:

["The", "Milvus", "vector", "database", "is", "built", "for", "scale!"]