13 updates from Amazon Web Services.
Amazon EMR Serverless now offers enhanced serverless storage capabilities with support for up to 1TB shuffle operations, raising the previous 200 GB per-job limit. Amazon EMR Serverless makes it…
Amazon EMR on EKS now supports interactive Apache Spark sessions with Spark Connect. Data engineers and data scientists can develop and debug Apache Spark applications interactively from managed…
Amazon EMR 7.14 is now available with new features across Amazon EMR on EC2, Amazon EMR on EKS, and Amazon EMR Serverless, along with version upgrades for additional applications. This release also…
Amazon EMR introduces Long Term Support (LTS) releases, starting with emr-spark-8.1.0 and Apache Spark 4.1. With LTS, designated versions of the AWS runtime for Apache Spark receive 36 months of…
Amazon EMR now gives you more time, at no additional cost, to migrate off older releases before they reach end of support. If you are actively migrating, your workloads on eligible releases keep…
Amazon EMR on EKS lets you run open-source big data frameworks such as Apache Spark and Flink on AWS EKS(Elastic Kubernetes Service) clusters. You submit jobs to a virtual cluster, which maps to a…
Amazon EMR on EC2 now supports interactive Apache Spark sessions with Spark Connect. Data engineers and data scientists can develop and debug Apache Spark applications interactively from managed…
Amazon EMR on EKS now supports the Apache Spark troubleshooting agent. Data engineers can now diagnose EMR on EKS job failures through natural language, receiving automated root cause analysis and…
Amazon EMR Serverless now supports updates to key application configurations such as maximum capacity, and custom image settings — without stopping and restarting the application. New workloads…
Amazon EMR Serverless now supports interactive sessions with Spark Connect, enabling you to develop and run Apache Spark applications from managed notebooks in Amazon SageMaker Unified Studio, as…
Amazon EMR now supports Apache Spark 4.0.2 across all three deployment models. With Spark 4.0.2, you can build and maintain data pipelines more easily with ANSI SQL and VARIANT data types, enforce…
Amazon EMR Serverless is now generally available in six additional AWS Regions - Asia Pacific (Hyderabad), Asia Pacific (Malaysia), Asia Pacific (New Zealand), Asia Pacific (Taipei), Asia Pacific…
Amazon EMR 7.13 is now available with Python 3.11 and version upgrades for additional applications. EMR 7.13 ships with Python 3.11 for Apache Spark by default. This release also includes patch…