# SQL query transform
<a name="sql-query-transform"></a>

You can use a SQL query transform to write your own transform in the form of a SQL query. Writing the SQL query in Visual ETL creates a subset of the data corresponding to the query. A SQL transform node can have multiple datasets as inputs, but produces only a single dataset as output. It contains a text field, where you enter the SQL query.

**To add an SQL query node to your job diagram**

1. Open the menu and then choose SQL query to add a new transform to your job diagram, if needed.

1. (Optional) Choose the rename node icon to enter a new name for the node in the job diagram.

1. Modify the input schema:

   1. Make sure the alias in the "SQL aliases" box is appropriate. Visual ETL will autopopulate this field, but you can change it.

   1. Write an SQL statement that queries the data to suit your needs

1. (Optional) After configuring the node properties and transform properties, you can preview the modified dataset by choosing the Data preview tab in the node details panel.

![The Amazon SageMaker Unified Studio UI showing the configuration options for the SQL query transform.](http://docs.aws.amazon.com/sagemaker-unified-studio/latest/userguide/images/vis-etl/vis-etl-sqlquery.png)


## 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).