[[["わかりやすい","easyToUnderstand","thumb-up"],["問題の解決に役立った","solvedMyProblem","thumb-up"],["その他","otherUp","thumb-up"]],[["わかりにくい","hardToUnderstand","thumb-down"],["情報またはサンプルコードが不正確","incorrectInformationOrSampleCode","thumb-down"],["必要な情報 / サンプルがない","missingTheInformationSamplesINeed","thumb-down"],["翻訳に関する問題","translationIssue","thumb-down"],["その他","otherDown","thumb-down"]],["最終更新日 2025-09-04 UTC。"],[[["\u003cp\u003eDataproc Serverless LTS runtime versions are supported for 30 months, while non-LTS versions are supported for 12 months.\u003c/p\u003e\n"],["\u003cp\u003eAll Dataproc Serverless runtime versions remain available for two years following their end-of-support date.\u003c/p\u003e\n"],["\u003cp\u003eThe current default Dataproc Serverless runtime version can be found in the "Supported Dataproc Serverless for Spark runtime versions" section.\u003c/p\u003e\n"],["\u003cp\u003eYou can select a different Dataproc Serverless runtime version when submitting a batch workload using the Google Cloud console, gcloud CLI, or the Dataproc API.\u003c/p\u003e\n"],["\u003cp\u003eDataproc Serverless for Spark runtime versions \u003ccode\u003e1.2\u003c/code\u003e and \u003ccode\u003e2.1+\u003c/code\u003e do not offer subminor version pinning.\u003c/p\u003e\n"]]],[],null,["# Serverless for Apache Spark runtime versions\n\n| **Dataproc Serverless** is now **Google Cloud Serverless for Apache Spark**. Until updated, some documents will refer to the previous name.\n\n\u003cbr /\u003e\n\n| - Serverless for Apache Spark LTS (Long-Time-Support) runtime versions are supported for 30 months. Serverless for Apache Spark non-LTS runtime versions are supported for 12 months.\n| - Serverless for Apache Spark runtime versions continue to be available for two years after their end-of-support date.\n| - **For runtime version `1.1` only** : You can specify a `major.minor.subminor` version for a batch workload or interactive session within one year of a `1.1` subminor release. The workload or session will fail if submitted after one-year from the release of the specified subminor runtime version. Other Serverless for Apache Spark runtime versions don't support subminor version pinning.\n\nSupported Serverless for Apache Spark runtime versions\n------------------------------------------------------\n\n### How to choose a Serverless for Apache Spark runtime version\n\nThe current default Serverless for Apache Spark runtime version is listed in\n[Supported Serverless for Apache Spark runtime versions](#supported-dataproc-serverless-for-spark-runtime-versions).\nYou can choose a different `major.minor` runtime version when you\n[submit a batch workload](/dataproc-serverless/docs/quickstarts/spark-batch#submit_a_spark_batch_workload)\nor [create a interactive session](/dataproc-serverless/docs/guides/create-serverless-sessions-templates#create-an-interactive-session)\nor [session template](/dataproc-serverless/docs/guides/create-serverless-sessions-templates#create-a-session-template).\n\nUnsupported Serverless for Apache Spark runtime versions\n--------------------------------------------------------\n\nThe following Serverless for Apache Spark versions are unsupported."]]
