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

Convert processor

The convert processor converts a field in a document to a different type, for example, a string to an integer or an integer to a string. For an array field, all values in the array are converted.

Syntax

The following is the syntax for the convert processor:

{
    "convert": {
        "field": "field_name",
        "type": "type-value"
    }
}

Configuration parameters

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

Parameter Required/Optional Description
field Required The name of the field containing the data to be converted. Supports template snippets.
type Required The type to convert the field value to. The supported types are integer, long, float, double, string, boolean, and auto. If the type is boolean, the value is set to true if the field value is a string true (ignoring case) and to false if the field value is a string false (ignoring case). If the value is not one of the allowed values, an error will occur.
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. If not specified, the value will be stored in the field field. Default is field.

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 convert-price, that converts price to a floating-point number, stores the converted value in the price_float field, and sets the value to 0 if it is less than 0:

PUT _ingest/pipeline/convert-price
{
  "description": "Pipeline that converts price to floating-point number and sets value to zero if price less than zero",
  "processors": [
    {
      "convert": {
        "field": "price",
        "type": "float",
        "target_field": "price_float"
      }
    },
    {
      "set": {
        "field": "price",
        "value": "0",
        "if": "ctx.price_float < 0"
      }
    }
  ]
}

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/convert-price/_simulate
{
  "docs": [
    {
      "_index": "testindex1",
      "_id": "1",
       "_source": {
        "price": "-10.5"
      }
    }
  ]
}

Response

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

{
  "docs": [
    {
      "doc": {
        "_index": "testindex1",
        "_id": "1",
        "_source": {
          "price_float": -10.5,
          "price": "0"
        },
        "_ingest": {
          "timestamp": "2023-08-22T15:38:21.180688799Z"
        }
      }
    }
  ]
}

Step 3: Ingest a document

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

PUT testindex1/_doc/1?pipeline=convert-price
{
  "price": "10.5"
}

Step 4 (Optional): Retrieve the document

To retrieve the document, run the following query:

GET testindex1/_doc/1

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