[[["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)：2025-04-03。"],[[["Dataproc on GKE enables the execution of Big Data applications on GKE clusters through the Dataproc `jobs` API."],["You can create a Dataproc on GKE virtual cluster and then submit Spark, PySpark, SparkR, or Spark-SQL jobs via the Google Cloud console, Cloud CLI, or the Dataproc API."],["Dataproc on GKE utilizes virtual clusters, which, unlike Dataproc on Compute Engine clusters, do not have separate master and worker VMs."],["Dataproc on GKE job are run as pods on node pools and is managed by GKE."],["Dataproc on GKE supports Spark 3.5 versions."]]],[]]
