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Amazon EMR introduces Long Term Support with Apache Spark 4.1

Amazon EMR introduces LTS releases, starting with emr-spark-8.1.0 and Apache Spark 4.1, providing 36 months of support for designated versions with critical fixes.

Amazon EMR introduces a LTS release, starting with emr-spark-8.1.0 and Apache Spark 4.1. This LTS version supports specific AWS runtimes for 36 months, fixing critical security, bug, and data corruption issues. LTS allows production Spark workloads to run an additional version longer and upgrade on their own schedule without extra cost. The release adds full support for Apache Iceberg v3, bringing geospatial, high-precision timestamps, and schema evolution to tables. Spark SQL queries can reference catalogs by name, including cross-account and Amazon S3 Table Catalog, and automatically detect Apache Iceberg, Delta Lake, and Apache Hudi table formats. Fine-grained access control now covers more operations in Apache Iceberg and Delta Lake's VACUUM operation. Amazon EMR on EKS clusters support Spark Connect endpoints with token-based authentication. emr-spark-8.1.0 is available on Amazon EMR on EC2, Amazon EMR on EKS, and Amazon EMR Serverless in all AWS regions where Amazon EMR is offered.

Why it matters

This update affects users performing data processing and big data analytics. LTS releases provide long-term support and security updates, allowing flexible management of upgrade schedules.

Read the original AWS announcement

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