Amazon EMR on EKS 6.11.0 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 6.11.0 release in general, see Amazon EMR 6.11.0 in the Amazon EMR Release Guide.

Amazon EMR on EKS 6.11 releases

The following Amazon EMR 6.11.0 releases are available for Amazon EMR on EKS. Select a specific emr-6.11.0-XXXX release to view more details such as the related container image tag.

emr-6.11.0-spark-rapids-latest
emr-6.11.0-spark-rapids-20230509
emr-6.11.0-java11-latest
emr-6.11.0-java11-20230509
notebook-spark/emr-6.11.0-latest
notebook-spark/emr-6.11.0-20230509
notebook-python/emr-6.11.0-latest
notebook-python/emr-6.11.0-20230509

Release notes

Release notes for Amazon EMR on EKS 6.11.0

Supported applications ‐ Amazon SDK for Java 1.12.446, Apache Spark 3.3.2-amzn-0, Apache Hudi 0.13.0-amzn-0, Apache Iceberg 1.2.0-amzn-0, Delta 2.2.0, Apache Spark RAPIDS 23.02.0-amzn-0, Jupyter Enterprise Gateway 2.6.0
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-site`	Change values in the `core-site.xml` Hadoop file.
`emrfs-site`	Change EMRFS settings.
`spark-metrics`	Change values in the `metrics.properties` Spark file.
`spark-defaults`	Change values in the `spark-defaults.conf` Spark file.
`spark-env`	Change values in the Spark environment.
`spark-hive-site`	Change values in the `hive-site.xml` Spark file.
`spark-log4j`	Change values in the `log4j.properties` Spark file.

For use specifically with CreateManagedEndpoint APIs:

Classifications	Descriptions
`jeg-config`	Change values in Jupyter Enterprise Gateway `jupyter_enterprise_gateway_config.py` file.
`jupyter-kernel-overrides`	Change 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 6.11 release of Amazon EMR on EKS.

Amazon EMR on EKS base image in Amazon ECR Public Gallery – If you use the custom image capability, our base image provides the essential jars, configuration, and libraries to interact with Amazon EMR on EKS. You can now find the base image in the Amazon ECR Public Gallery.
Spark container log rotation – Amazon EMR on EKS 6.11 supports Spark container log rotation. You can enable the capability with containerLogRotationConfiguration within the MonitoringConfiguration operation of the StartJobRun API. You can configure the rotationSize and maxFilestoKeep to specify the number and size of the log files that you want Amazon EMR on EKS to keep in the Spark driver and executor pods. For more information, see Using Spark container log rotation.
Volcano support in Spark operator and spark-submit – Amazon EMR on EKS 6.11 supports running Spark jobs with Volcano as Kubernetes custom scheduler in Spark operator and spark-submit. You can use features like gang scheduling, queue management, preemption, and fair-share scheduling to achieve high scheduling throughput and optimized capacity. For more information, see Using Volcano as a custom scheduler for Apache Spark on Amazon EMR on EKS.

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emr-6.12.0-20230701

emr-6.11.0-latest