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

Lowercase processor

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

Syntax

The following is the syntax for the lowercase processor:

  1. {
  2.   "lowercase": {
  3.     "field": "field_name"
  4.   }
  5. }

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Configuration parameters

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

ParameterRequiredDescription
fieldRequiredThe name of the field containing the data to be converted. Supports template snippets.
descriptionOptionalA brief description of the processor.
ifOptionalA condition for running the processor.
ignore_failureOptionalSpecifies whether the processor continues execution even if it encounters errors. If set to true, failures are ignored. Default is false.
on_failureOptionalA list of processors to run if the processor fails.
ignore_missingOptionalSpecifies 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.
tagOptionalAn identifier tag for the processor. Useful for debugging in order to distinguish between processors of the same type.
target_fieldOptionalThe 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 lowercase-title, that uses the lowercase processor to lowercase the title field of a document:

  1. PUT _ingest/pipeline/lowercase-title
  2. {
  3.   "description" : "Pipeline that lowercases the title field",
  4.   "processors" : [
  5.     {
  6.       "lowercase" : {
  7.         "field" : "title"
  8.       }
  9.     }
  10.   ]
  11. }

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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:

  1. POST _ingest/pipeline/lowercase-title/_simulate
  2. {
  3.   "docs": [
  4.     {
  5.       "_index": "testindex1",
  6.       "_id": "1",
  7.       "_source": {
  8.         "title": "WAR AND PEACE"
  9.       }
  10.     }
  11.   ]
  12. }

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Response

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

  1. {
  2.   "docs": [
  3.     {
  4.       "doc": {
  5.         "_index": "testindex1",
  6.         "_id": "1",
  7.         "_source": {
  8.           "title": "war and peace"
  9.         },
  10.         "_ingest": {
  11.           "timestamp": "2023-08-22T17:39:39.872671834Z"
  12.         }
  13.       }
  14.     }
  15.   ]
  16. }

Step 3: Ingest a document

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

  1. PUT testindex1/_doc/1?pipeline=lowercase-title
  2. {
  3.   "title": "WAR AND PEACE"
  4. }

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Step 4 (Optional): Retrieve the document

To retrieve the document, run the following query:

  1. GET testindex1/_doc/1

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