Split processor
The split processor is used to split a string field into an array of substrings based on a specified delimiter.
The following is the syntax for the split processor:
{
"split": {
"field": "field_to_split",
"separator": "<delimiter>",
"target_field": "split_field"
}
}
Configuration parameters
The following table lists the required and optional parameters for the split processor.
| Parameter | Required/Optional | Description |
|---|---|---|
field | Required | The field containing the string to be split. |
separator | Required | The delimiter used to split the string. This can be a regular expression pattern. |
preserve_trailing | Optional | If set to true, preserves empty trailing fields (for example, '') in the resulting array. If set to false, then empty trailing fields are removed from the resulting array. Default is false. |
target_field | Optional | The field where the array of substrings 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 split_pipeline that uses the split processor to split the log_message field on the comma character and store the resulting array in the log_parts field:
PUT _ingest/pipeline/split_pipeline
{
"description": "Split log messages by comma",
"processors": [
{
"split": {
"field": "log_message",
"separator": ",",
"target_field": "log_parts"
}
}
]
}
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/split_pipeline/_simulate
{
"docs": [
{
"_source": {
"log_message": "error,warning,info"
}
}
]
}
Response
The following example response confirms that the pipeline is working as expected:
{
"docs": [
{
"doc": {
"_index": "_index",
"_id": "_id",
"_source": {
"log_message": "error,warning,info",
"log_parts": [
"error",
"warning",
"info"
]
},
"_ingest": {
"timestamp": "2024-04-26T22:29:23.207849376Z"
}
}
}
]
}
Step 3: Ingest a document
The following query ingests a document into an index named testindex1:
PUT testindex1/_doc/1?pipeline=split_pipeline
{
"log_message": "error,warning,info"
}
Response
The request indexes the document into the index testindex1 and splits the log_message field on the comma delimiter before indexing, as shown in the following response:
{
"_index": "testindex1",
"_id": "1",
"_version": 70,
"result": "updated",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 72,
"_primary_term": 47
}
Step 4 (Optional): Retrieve the document
To retrieve the document, run the following query:
GET testindex1/_doc/1
Response
The response shows the log_message field as an array of values split on the comma delimiter:
{
"_index": "testindex1",
"_id": "1",
"_version": 70,
"_seq_no": 72,
"_primary_term": 47,
"found": true,
"_source": {
"log_message": "error,warning,info",
"log_parts": [
"error",
"warning",
"info"
]
}
}