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This documentation describes using the uppercase processor in OpenSearch ingest pipelines. Consider using the Data Prepper uppercase_string processor, which runs on the OpenSearch cluster, if your use case involves large or complex datasets.

Uppercase processor

The uppercase processor converts all the text in a specific field to uppercase letters.

Syntax

The following is the syntax for the uppercase processor:

{
  "uppercase": {
    "field": "field_name"
  }
}

Configuration parameters

The following table lists the required and optional parameters for the uppercase processor.

Parameter Required/Optional Description
field Required The name of the field containing the data to be appended. Supports template snippets.
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 errors. If set to true, failures are ignored. Default is false.
ignore_missing Optional Specifies whether the processor should ignore documents that do not contain the specified field. If set to true, the processor does not modify the document if the field does not exist or is null. 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.
target_field Optional The name of the field in which to store the parsed data. Default is field. By default, field is updated in place.

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 uppercase, that converts the text in the field field to uppercase:

PUT _ingest/pipeline/uppercase
{
  "processors": [
    {
      "uppercase": {
        "field": "name"
      }
    }
  ]
}

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/uppercase/_simulate
{
  "docs": [
    {
      "_index": "testindex1",
      "_id": "1",
      "_source": {
        "name": "John"
      }
    }
  ]
}

Response

The following example response confirms that the pipeline is working as expected:

{
  "docs": [
    {
      "doc": {
        "_index": "testindex1",
        "_id": "1",
        "_source": {
          "name": "JOHN"
        },
        "_ingest": {
          "timestamp": "2023-08-28T19:54:42.289624792Z"
        }
      }
    }
  ]
}

Step 3: Ingest a document

The following query ingests a document into an index named testindex1:

PUT testindex1/_doc/1?pipeline=uppercase
{
  "name": "John"
}

Step 4 (Optional): Retrieve the document

To retrieve the document, run the following query:

GET testindex1/_doc/1

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