Amazon SageMaker Unified Studio is in preview release and is subject to change.
Using the Amazon Q data integration in AWS Glue
Amazon SageMaker Unified Studio supports the Amazon Q data integration in AWS Glue. It helps data engineers and ETL developers create data integration jobs using natural language letting you automate aspects of code authoring.
When using the Amazon Q data integration in AWS Glue, in the Jupyter Lab IDE, you enter comments using natural language instructions, and then the PySpark kernel generates the code on your behalf. You can customize the generated code to meet your own needs.
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Open a Python notebook, and ensure the kernel is configured to use a PySpark connection.
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You can request a prompt response by adding a comment and then placing it in a prompt, which will start Amazon Q processing.
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If the prompt is AWS Glue related, the data integration generates a AWS Glue job script using PySpark.
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Alternatively, you can continue to use your default auto-completions from Amazon Q Developer. If a prompt isn't Glue related, Amazon Q Developer will use autocomplete instead.
