Posted On: Nov 16, 2023

Today, we are excited to announce that you can enable endpoints for interactive analytics on EMR Serverless applications. This launch allows you to pick EMR Serverless applications as the compute, in addition to EMR on EC2 clusters and EMR on EKS virtual clusters, to run Jupyterlab notebooks from EMR Studio workspaces. Amazon EMR Studio is an integrated development environment (IDE) that makes it simple for data scientists and data engineers to develop, visualize, and debug analytics applications written in PySpark, Python, and Scala. Amazon EMR Serverless is a serverless option for Amazon EMR that makes it simple to run open-source big data analytics frameworks such as Apache Spark without configuring, managing, and scaling clusters or servers. 

Starting today, you can enable EMR Serverless Applications to perform interactive analyses in EMR Studio. Once enabled, you can connect to your EMR Serverless application right from your EMR Studio workspaces. You can now interactively query, explore and visualize data, and run Spark workloads using the built-in SparkMagic Jupyterlab notebooks without having to manage clusters. You can launch the live Spark UI directly from notebooks to access logs and debug the application.

This feature is now generally available in Amazon Web Services China (Beijing) Region, operated by Sinnet and Amazon Web Services China (Ningxia) Region, operated by NWCD. To learn more, see the EMR documentation.