排序
使用集合让一切井井有条
根据您的偏好保存内容并对其进行分类。
如未另行说明,那么本页面中的内容已根据知识共享署名 4.0 许可获得了许可,并且代码示例已根据 Apache 2.0 许可获得了许可。有关详情,请参阅 Google 开发者网站政策。Java 是 Oracle 和/或其关联公司的注册商标。
[[["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"]],[],[[["\u003cp\u003eThis webpage provides an example of a PySpark sort job using the Dataproc service.\u003c/p\u003e\n"],["\u003cp\u003eThe code sample demonstrates how to use PySpark to create an RDD, sort a list of strings, and then print the sorted list.\u003c/p\u003e\n"],["\u003cp\u003eAuthentication to Dataproc requires setting up Application Default Credentials, as detailed in the provided link.\u003c/p\u003e\n"],["\u003cp\u003eThe page also links to further documentation for the Dataproc Python API and the Dataproc quickstart using client libraries.\u003c/p\u003e\n"]]],[],null,["An example PySpark sort job.\n\nCode sample \n\nPython\n\n\nBefore trying this sample, follow the Python setup instructions in the\n[Dataproc quickstart using\nclient libraries](/dataproc/docs/quickstarts/quickstart-lib).\n\n\nFor more information, see the\n[Dataproc Python API\nreference documentation](/python/docs/reference/dataproc/latest).\n\n\nTo authenticate to Dataproc, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n import pyspark\n\n sc = pyspark.SparkContext()\n rdd = sc.parallelize([\"Hello,\", \"world!\", \"dog\", \"elephant\", \"panther\"])\n words = sorted(rdd.collect())\n print(words)\n\nWhat's next\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=dataproc)."]]