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

Date processor

The date processor is used to parse dates from document fields and to add the parsed data to a new field. By default, the parsed data is stored in the @timestamp field.

Syntax example

The following is the syntax for the date processor:

{
  "date": {
    "field": "date_field",
    "formats": ["yyyy-MM-dd'T'HH:mm:ss.SSSZZ"]
  }
}

Configuration parameters

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

Parameter Required/Optional Description
field Required The name of the field containing the data to be converted.
formats Required An array of the expected date formats. The processor tries every format in the order specified. If more than one format can parse the date, the last matching format determines the result. Can be a date format or one of the following formats: ISO8601, UNIX, UNIX_MS, or TAI64N.
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.
locale Optional The locale to use when parsing the date. If not specified, the root locale is used, which parses English month and day names. Supports template snippets.
on_failure Optional A list of processors to run if the processor fails.
output_format Optional The date format to use for the target field. Default is yyyy-MM-dd'T'HH:mm:ss.SSSXXX, for example, 2023-06-30T00:00:00.000Z.
tag Optional An identifier tag for the processor. Useful for debugging in order to distinguish between processors of the same type. For more information, see Using processor tags for monitoring and debugging.
target_field Optional The name of the field in which to store the parsed data. Default target field is @timestamp.
timezone Optional The time zone to use when parsing the date. Default is UTC. Supports template snippets.

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 date-output-format, that uses the date processor to convert from European date format to US date format, adding the new field date_us with the desired output_format:

PUT /_ingest/pipeline/date-output-format
{
  "description": "Pipeline that converts European date format to US date format",
  "processors": [
    {
      "date": {
        "field" : "date_european",
        "formats" : ["dd/MM/yyyy", "UNIX"],
        "target_field": "date_us",
        "output_format": "MM/dd/yyy",
        "timezone" : "UTC"
      }
    }
  ]
}

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/date-output-format/_simulate
{
  "docs": [
    {
      "_index": "testindex1",
      "_id": "1",
      "_source": {
        "date_european": "30/06/2023"
      }
    }
  ]
}

Response

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

{
  "docs": [
    {
      "doc": {
        "_index": "testindex1",
        "_id": "1",
        "_source": {
          "date_us": "06/30/2023",
          "date_european": "30/06/2023"
        },
        "_ingest": {
          "timestamp": "2023-08-22T17:08:46.275195504Z"
        }
      }
    }
  ]
}

Step 3: Ingest a document

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

PUT testindex1/_doc/1?pipeline=date-output-format
{
  "date_european": "30/06/2023"
}

Step 4 (Optional): Retrieve the document

To retrieve the document, run the following query:

GET testindex1/_doc/1

Using time zones and locales from the document

Because the timezone and locale parameters support template snippets, you can read them from fields in the document being processed. This is useful when documents come from sources in different regions. The following request parses a French date string using the time zone and locale stored in the store object:

POST _ingest/pipeline/_simulate
{
  "pipeline": {
    "processors": [
      {
        "date": {
          "field": "order_date",
          "formats": ["dd MMMM yyyy HH:mm"],
          "timezone": "{{{store.timezone}}}",
          "locale": "{{{store.locale}}}"
        }
      }
    ]
  },
  "docs": [
    {
      "_source": {
        "order_date": "14 octobre 2026 09:30",
        "store": {
          "timezone": "Europe/Paris",
          "locale": "fr"
        }
      }
    }
  ]
}

The response shows that the date was parsed using the French month name and the Paris time zone:

{
  "docs": [
    {
      "doc": {
        "_index": "_index",
        "_id": "_id",
        "_source": {
          "order_date": "14 octobre 2026 09:30",
          "store": {
            "locale": "fr",
            "timezone": "Europe/Paris"
          },
          "@timestamp": "2026-10-14T09:30:00.000+02:00"
        },
        "_ingest": {
          "timestamp": "2026-10-14T20:32:15.764960761Z"
        }
      }
    }
  ]
}
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