Amazon EMR on EKS 6.15.0 releases
This page describes the new and updated functionality for Amazon EMR that is specific to the Amazon EMR on EKS deployment. For details about Amazon EMR running on Amazon EC2 and about the Amazon EMR 6.15.0 release in general, see Amazon EMR 6.15.0 in the Amazon EMR Release Guide.
Amazon EMR on EKS 6.15 releases
The following Amazon EMR 6.15.0 releases are available for Amazon EMR on EKS. Select a specific emr-6.15.0-XXXX release to view more details such as the related container image tag.
Release notes
Release notes for Amazon EMR on EKS 6.15.0
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Supported applications ‐ AWS SDK for Java 1.12.569, Apache Spark 3.4.1-amzn-2, Apache Flink 1.17.1-amzn-1, Apache Hudi 0.14.0-amzn-0, Apache Iceberg 1.4.0-amzn-0, Delta 2.4.0, Apache Spark RAPIDS 23.08.01-amzn-0, Jupyter Enterprise Gateway 2.6.0
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Supported components ‐
aws-sagemaker-spark-sdk,emr-ddb,emr-goodies,emr-s3-select,emrfs,hadoop-client,hudi,hudi-spark,iceberg,spark-kubernetes. -
Supported configuration classifications
For use with StartJobRun and CreateManagedEndpoint APIs:
Classifications Descriptions core-siteChange values in the
core-site.xmlHadoop file.emrfs-siteChange EMRFS settings.
spark-metricsChange values in the
metrics.propertiesSpark file.spark-defaultsChange values in the
spark-defaults.confSpark file.spark-envChange values in the Spark environment.
spark-hive-siteChange values in the
hive-site.xmlSpark file.spark-log4jChange values in the
log4j2.propertiesSpark file.emr-job-submitterConfiguration for job submitter pod.
For use specifically with CreateManagedEndpoint APIs:
Classifications Descriptions jeg-configChange values in Jupyter Enterprise Gateway
jupyter_enterprise_gateway_config.pyfile.jupyter-kernel-overridesChange value for the Kernel Image in Jupyter Kernel Spec file.
Configuration classifications allow you to customize applications. These often correspond to a configuration XML file for the application, such as
spark-hive-site.xml. For more information, see Configure Applications.
Notable features
The following features are included with the 6.15 release of Amazon EMR on EKS.
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Amazon EMR on EKS with Apache Flink - With Amazon EMR on EKS 6.15.0, you can run your Apache Flink-based application along with other types of applications on the same Amazon EKS cluster. This helps improve resource utilization and simplify infrastructure management. You can leverage Spot Instances in a Flink application with graceful decommission, and achieve faster restart times with fine-grained recovery and task-local recovery with Amazon EBS. Accessibility and monitoring features include the ability to launch a Flink application with jars that are stored in Amazon S3, access to the AWS Glue Data Catalog, monitoring integration with Amazon S3 and Amazon CloudWatch, and container log rotation.
