[[["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)：2025-08-18。"],[[["\u003cp\u003eDataflow pipelines using Runner v2 support the use of custom container images to customize the runtime environment of user code.\u003c/p\u003e\n"],["\u003cp\u003eBy default, Dataflow pipelines use prebuilt Apache Beam images, but users can specify their own custom container images for their Dataflow jobs.\u003c/p\u003e\n"],["\u003cp\u003eCustom containers allow users to preinstall pipeline dependencies, including those not in public repositories, and to manage dependencies when access to public repositories is restricted.\u003c/p\u003e\n"],["\u003cp\u003eUsing custom containers also allows you to prestage large files and launch third-party software to customize the execution environment.\u003c/p\u003e\n"],["\u003cp\u003eThe main use cases of custom containers are to reduce worker start time, customize the environment, and to manage dependencies.\u003c/p\u003e\n"]]],[],null,[]]
