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[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],[],[[["\u003cp\u003eThis page demonstrates how to instantiate an inline workflow template using Cloud Client Libraries for Dataproc.\u003c/p\u003e\n"],["\u003cp\u003eThe code samples provided use Go, Java, Node.js, and Python, showcasing the process of creating a workflow with Hadoop jobs (teragen and terasort) and cluster placement configurations.\u003c/p\u003e\n"],["\u003cp\u003eEach code example requires setting up Application Default Credentials for authentication and following the language-specific quickstart guides for Dataproc.\u003c/p\u003e\n"],["\u003cp\u003eThe workflow involves creating jobs, defining cluster placement, and then submitting a request to instantiate the workflow from the inline template, which will run within a managed cluster.\u003c/p\u003e\n"],["\u003cp\u003eThe provided code defines a workflow consisting of two Hadoop jobs, "teragen" and "terasort," and includes the ability to specify a cluster zone or utilize auto zone placement.\u003c/p\u003e\n"]]],[],null,[]]