Amazon EMR Adds Support for Spark 2.4.4, Flink 1.8.1, and the Ability to Reconfigure Multiple Master Nodes
With Amazon EMR release 5.27.0, you can now reconfigure your multi-master clusters on the fly, without needing to recreate your cluster. EMR 5.23 added the capability to run multiple master nodes, helping you protect your long running clusters that run important data pipelines, streaming applications, or HBase clusters from the potential loss of a master node. EMR also gives you the ability to reconfigure running clusters, giving you the ability to change configuration using the EMR console, CLI, and SDK. With EMR release 5.27.0, you can now reconfigure your running multiple master node clusters, allowing you to easily change the EMR application configuration in your running cluster without having to recreate it.
With Amazon EMR release 5.27.0, you can now reconfigure your multi-master clusters on the fly, without needing to recreate your cluster. EMR 5.23 added the capability to run multiple master nodes, helping you protect your long running clusters that run important data pipelines, streaming applications, or HBase clusters from the potential loss of a master node. EMR also gives you the ability to reconfigure running clusters, giving you the ability to change configuration using the EMR console, CLI, and SDK. With EMR release 5.27.0, you can now reconfigure your running multiple master node clusters, allowing you to easily change the EMR application configuration in your running cluster without having to recreate it.
The EMR release 5.27.0 also includes new versions of Apache Flink 1.8.1, Apache Spark 2.4.4 with Scala 2.11, JupyterHub 1.0.0, and Tensorflow 1.14.0. Additionally, you can now deploy Apache Flink in a multiple master node cluster.
Amazon EMR release 5.27.0 is now available in all supported regions for Amazon EMR.
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