Trim token filter
Removes leading and trailing whitespace from each token in a stream. While this can change the length of a token, the trim filter does not change a token’s offsets.
The trim filter uses Lucene’s TrimFilter.
Many commonly used tokenizers, such as the standard or whitespace tokenizer, remove whitespace by default. When using these tokenizers, you don’t need to add a separate trim filter.
To see how the trim filter works, you first need to produce a token containing whitespace.
The following analyze API request uses the keyword tokenizer to produce a token for " fox ".
GET _analyze {
"tokenizer" : "keyword",
"text" : " fox "
}
The API returns the following response. Note the " fox " token contains the original text’s whitespace. Note that despite changing the token’s length, the start_offset and end_offset remain the same.
{
"tokens": [
{
"token": " fox ",
"start_offset": 0,
"end_offset": 5,
"type": "word",
"position": 0
}
]
}
To remove the whitespace, add the trim filter to the previous analyze API request.
GET _analyze {
"tokenizer" : "keyword",
"filter" : ["trim"],
"text" : " fox "
}
The API returns the following response. The returned fox token does not include any leading or trailing whitespace.
{
"tokens": [
{
"token": "fox",
"start_offset": 0,
"end_offset": 5,
"type": "word",
"position": 0
}
]
}
The following create index API request uses the trim filter to configure a new custom analyzer.
PUT trim_example {
"settings": {
"analysis": {
"analyzer": {
"keyword_trim": {
"tokenizer": "keyword",
"filter": [ "trim" ]
}
}
}
}
}