Amazon EMR on EKS 7.11.0 releases - Amazon EMR
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Amazon EMR on EKS 7.11.0 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 7.11.0 release in general, see Amazon EMR 7.11.0 in the Amazon EMR Release Guide.

Amazon EMR on EKS 7.11 releases

The following Amazon EMR 7.11.0 releases are available for Amazon EMR on EKS. Select a specific emr-7.11.0-XXXX release to view more details such as the related container image tag.

Flink releases

The following Amazon EMR 7.11.0 releases are available for Amazon EMR on EKS when you run Flink applications.

Spark releases

The following Amazon EMR 7.11.0 releases are available for Amazon EMR on EKS when you run Spark applications.

  • emr-7.11.0-latest

  • emr-7.11.0-20251020

  • emr-7.11.0-spark-rapids-latest

  • emr-7.11.0-spark-rapids-20251020

  • emr-7.11.0-java11-latest

  • emr-7.11.0-java11-20251020

  • emr-7.11.0-java8-latest

  • emr-7.11.0-java8-20251020

  • emr-7.11.0-spark-rapids-java8-latest

  • emr-7.11.0-spark-rapids-java8-20251020

  • notebook-spark/emr-7.11.0-latest

  • notebook-spark/emr-7.11.0-20251020

  • notebook-spark/emr-7.11.0-spark-rapids-latest

  • notebook-spark/emr-7.11.0-spark-rapids-20251020

  • notebook-spark/emr-7.11.0-java11-latest

  • notebook-spark/emr-7.11.0-java11-20251020

  • notebook-spark/emr-7.11.0-java8-latest

  • notebook-spark/emr-7.11.0-java8-20251020

  • notebook-spark/emr-7.11.0-spark-rapids-java8-latest

  • notebook-spark/emr-7.11.0-spark-rapids-java8-20251020

  • notebook-python/emr-7.11.0-latest

  • notebook-python/emr-7.11.0-20251020

  • notebook-python/emr-7.11.0-spark-rapids-latest

  • notebook-python/emr-7.11.0-spark-rapids-20251020

  • notebook-python/emr-7.11.0-java11-latest

  • notebook-python/emr-7.11.0-java11-20251020

  • notebook-python/emr-7.11.0-java8-latest

  • notebook-python/emr-7.11.0-java8-20251020

  • notebook-python/emr-7.11.0-spark-rapids-java8-latest

  • notebook-python/emr-7.11.0-spark-rapids-java8-20251020

  • livy/emr-7.11.0-latest

  • livy/emr-7.11.0-20251020

  • livy/emr-7.11.0-java11-latest

  • livy/emr-7.11.0-java11-20251020

  • livy/emr-7.11.0-java8-latest

  • livy/emr-7.11.0-java8-20251020

Release notes

Release notes for Amazon EMR on EKS 7.11.0:

  • Supported applications ‐ Amazon SDK for Java 2.35.5 and 1.12.792, Apache Spark 3.5.6-amzn-0, Apache Hudi 1.0.2-amzn-0, Apache Iceberg 1.9.1-amzn-0, Delta 3.3.2-amzn-0, Apache Spark RAPIDS 25.04.0-amzn-0, Apache Flink 1.20.0-amzn-5

  • Supported components ‐ 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-log4j2

    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.

Changes and features

The following changes are included with the 7.11.0 release of Amazon EMR on EKS:

Amazon EMR on EKS now supports integration with SageMaker Unified Studio through a managed Livy solution including:

  • Managed Sessions: New interactive session resource type that provides a custom HTTPS endpoint for running Spark sessions on your EKS cluster through SageMaker Unified Studio

  • Lake Formation Integration: Supports data access control with two modes a) Fine-Grained Access Control b) Full Table Access (Compatibility Mode)

  • Identity Management: Flexible authentication options a) IAM role-based access control b) based access control.

  • User Background Sessions with integration: Supports long-running Spark workloads to continue running even after users log off from SageMaker Unified Studio, supporting sessions up to 90 days