
Amazon EMR Serverless now supports interactive sessions with Spark Connect, enabling developers to run Apache Spark applications from notebooks and IDEs with persistent context, real-time monitoring, and granular cost visibility.


<div><p>This article announces Spark Connect support for Amazon EMR Serverless, enabling interactive development of Apache Spark applications from notebooks and IDEs.</p><ul><li>Interactive sessions with persistent Spark context across cells and scripts</li><li>Develop in SageMaker Unified Studio, Jupyter, Visual Studio Code, and other IDEs</li><li>Blend local Python code with remote Spark operations seamlessly</li><li>Monitor and debug sessions via EMR console and Spark UI</li><li>Real-time session monitoring and history tracking capabilities</li><li>Granular cost and usage visibility per session</li><li>Available with EMR release 7.13 in all EMR Serverless regions</li></ul><p>Spark Connect on EMR Serverless enables interactive data exploration and iterative development workflows while maintaining separation between client and Spark infrastructure.</p></div>


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