[[["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)：2025-04-21。"],[[["This page provides guidance on managing configurations for deployed pipelines, including compute profiles, pipeline instrumentation, engine parameters, resource allocation, and alerts."],["You can customize the compute profile that runs the pipeline and set parameters, with the option to manage profiles and view Dataproc provisioner properties."],["Instrumentation can be enabled or disabled to generate metrics for each pipeline node, which can help in performance monitoring, and is recommended unless resources are constrained."],["Configurations can also be made to allow for custom Spark parameters, memory and CPU specifications for the driver and executor, and the setting of batch intervals for streaming data."],["Pipeline alerts and post-processing tasks can be set up during pipeline design and viewed after deployment, with the flexibility to enable transformation pushdown for BigQuery execution."]]],[]]
