Amazon EMR on EKS 6.15.0 releases - Amazon EMR
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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.

Flink releases

The following Amazon EMR 6.15.0 releases are available for Amazon EMR on EKS when you run Flink applications.

Spark releases

The following Amazon EMR 6.15.0 releases are available for Amazon EMR on EKS when you run Spark applications.

  • emr-6.15.0-latest

  • emr-6.15.0-20231109

  • emr-6.15.0-spark-rapids-latest

  • emr-6.15.0-spark-rapids-20231109

  • emr-6.15.0-java11-latest

  • emr-6.15.0-java11-20231109

  • emr-6.15.0-java17-latest

  • emr-6.15.0-java17-20231109

  • emr-6.15.0-java17-al2023-latest

  • emr-6.15.0-java17-al2023-20231109

  • emr-6.15.0-spark-rapids-java17-latest

  • emr-6.15.0-spark-rapids-java17-20231109

  • emr-6.15.0-spark-rapids-java17-al2023-latest

  • emr-6.15.0-spark-rapids-java17-al2023-20231109

  • notebook-spark/emr-6.15.0-latest

  • notebook-spark/emr-6.15.0-20231109

  • notebook-spark/emr-6.15.0-spark-rapids-latest

  • notebook-spark/emr-6.15.0-spark-rapids-20231109

  • notebook-spark/emr-6.15.0-java11-latest

  • notebook-spark/emr-6.15.0-java11-20231109

  • notebook-spark/emr-6.15.0-java17-latest

  • notebook-spark/emr-6.15.0-java17-20231109

  • notebook-spark/emr-6.15.0-java17-al2023-latest

  • notebook-spark/emr-6.15.0-java17-al2023-20231109

  • notebook-python/emr-6.15.0-latest

  • notebook-python/emr-6.15.0-20231109

  • notebook-python/emr-6.15.0-spark-rapids-latest

  • notebook-python/emr-6.15.0-spark-rapids-20231109

  • notebook-python/emr-6.15.0-java11-latest

  • notebook-python/emr-6.15.0-java11-20231109

  • notebook-python/emr-6.15.0-java17-latest

  • notebook-python/emr-6.15.0-java17-20231109

  • notebook-python/emr-6.15.0-java17-al2023-latest

  • notebook-python/emr-6.15.0-java17-al2023-20231109

Release notes

Release notes for Amazon EMR on EKS 6.15.0

  • Supported applications ‐ Amazon 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

  • 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 log4j2.properties Spark file.

    emr-job-submitter

    Configuration for job submitter pod.

    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 6.15 release of Amazon EMR on EKS.

  • 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 Amazon Glue Data Catalog, monitoring integration with Amazon S3 and Amazon CloudWatch, and container log rotation.