[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC):2025-08-12。"],[[["\u003cp\u003eThis guide addresses the issue of failed ephemeral Dataproc cluster deletions in Cloud Data Fusion, which can occur after a pipeline run.\u003c/p\u003e\n"],["\u003cp\u003eUpgrading to the latest Cloud Data Fusion version is strongly recommended to ensure automatic cluster cleanup.\u003c/p\u003e\n"],["\u003cp\u003eConfiguring the \u003ccode\u003eMax Idle Time\u003c/code\u003e setting (available in versions 6.4+) enables automatic cluster deletion by Dataproc even if the pipeline deletion fails, with a default of 4 hours in version 6.6+.\u003c/p\u003e\n"],["\u003cp\u003eIf upgrading or setting \u003ccode\u003eMax Idle Time\u003c/code\u003e isn't possible, you can manually delete stale clusters by identifying the relevant project IDs and deleting the clusters from the Dataproc Clusters page.\u003c/p\u003e\n"],["\u003cp\u003eFor debugging, the \u003ccode\u003eSkip Cluster Deletion\u003c/code\u003e property can be set to \u003ccode\u003eTrue\u003c/code\u003e to prevent cluster deletion after a pipeline run, but you must manually delete the cluster afterward.\u003c/p\u003e\n"]]],[],null,[]]