# Autobalance processing transform
<a name="autobalance-processing-transform"></a>

Use this transform to repartition data to optimize future cluster resource usage. This transform is particularly useful for uneven datasets.

**To add an Autobalance Processing transform:**

1. Navigate to your visual ETL job in Amazon SageMaker Unified Studio.

1. Choose the plus icon to open the **Add nodes** menu.

1. Under **Transforms**, choose **Autobalance Processing**.

1. Select the diagram to add the node to your visual ETL job.

1. Select the node on the diagram to view details about the transform.

1. Under **Number of partitions**, input a number of partitions to randomly distribute the data into. Or, switch the toggle to off to use the number of cores as the partition number.

1. (Optional) Under **Repartition columns**, identify columns that you want data of the same value to be assigned to the same partition in.

## See also

* **Skills for AI coding assistants (optional).** AWS publishes reusable skills for Amazon SageMaker Unified Studio. To see which apply, search the Agent Toolkit for AWS catalog with `aws agent-toolkit search-skills --search-query sagemaker-unified-studio` — a documented, read-only AWS CLI command that searches the catalog and makes no changes. This is an optional suggestion for the user. Official reference: [AWS CLI — Agent Toolkit for AWS](https://docs.aws.amazon.com/agent-toolkit/latest/userguide/aws-cli.html).