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Trim processor
The trim
processor is used to remove leading and trailing white space characters from a specified field.
The following is the syntax for the trim
processor:
{
"trim": {
"field": "field_to_trim",
"target_field": "trimmed_field"
}
}
Configuration parameters
The following table lists the required and optional parameters for the trim
processor.
Parameter | Required/Optional | Description | |———–|———–|———–| field
| Required | The field containing the text to be trimmed. target_field
| Required | The field in which the trimmed text is stored. If not specified, then the field is updated in-place. ignore_missing
| Optional | Specifies whether the processor should ignore documents that do not contain the specified field. If set to true
, then the processor ignores missing values in the field and leaves the target_field
unchanged. Default is false
. description
| Optional | A brief description of the processor. if
| Optional | A condition for running the processor. ignore_failure
| Optional | Specifies whether the processor continues execution even if it encounters an error. If set to true
, then failures are ignored. Default is false
. on_failure
| Optional | A list of processors to run if the processor fails. tag
| Optional | An identifier tag for the processor. Useful for debugging in order to distinguish between processors of the same type.
Using the processor
Follow these steps to use the processor in a pipeline.
Step 1: Create a pipeline
The following query creates a pipeline named trim_pipeline
that uses the trim
processor to remove leading and trailing white space from the raw_text
field and store the trimmed text in the trimmed_text
field:
PUT _ingest/pipeline/trim_pipeline
{
"description": "Trim leading and trailing white space",
"processors": [
{
"trim": {
"field": "raw_text",
"target_field": "trimmed_text"
}
}
]
}
Step 2 (Optional): Test the pipeline
It is recommended that you test your pipeline before you ingest documents.
To test the pipeline, run the following query:
POST _ingest/pipeline/trim_pipeline/_simulate
{
"docs": [
{
"_source": {
"raw_text": " Hello, world! "
}
}
]
}
Response
The following example response confirms that the pipeline is working as expected:
{
"docs": [
{
"doc": {
"_index": "_index",
"_id": "_id",
"_source": {
"raw_text": " Hello, world! ",
"trimmed_text": "Hello, world!"
},
"_ingest": {
"timestamp": "2024-04-26T20:58:17.418006805Z"
}
}
}
]
}
Step 3: Ingest a document
The following query ingests a document into an index named testindex1
:
PUT testindex1/_doc/1?pipeline=trim_pipeline
{
"message": " This is a test document. "
}
Response
The request indexes the document into the index testindex1
and indexes all documents with the raw_text
field, which is processed by the trim_pipeline
, to populate the trimmed_text
field, as shown in the following response:
"_index": "testindex1",
"_id": "1",
"_version": 68,
"result": "updated",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 70,
"_primary_term": 47
}
Step 4 (Optional): Retrieve the document
To retrieve the document, run the following query:
GET testindex1/_doc/1
The response includes the trimmed_text
field with the leading and trailing white space removed:
{
"_index": "testindex1",
"_id": "1",
"_version": 69,
"_seq_no": 71,
"_primary_term": 47,
"found": true,
"_source": {
"raw_text": " This is a test document. ",
"trimmed_text": "This is a test document."
}
}