Azure 数据工厂中的视觉对象创作Visual authoring in Azure Data Factory

适用于:是 Azure 数据工厂是 Azure Synapse Analytics(预览版)APPLIES TO: yesAzure Data Factory yesAzure Synapse Analytics (Preview)

Azure 数据工厂用户界面体验 (UX) 允许你以可视方式创作和部署资源为你的数据工厂而无需编写任何代码。The Azure Data Factory user interface experience (UX) lets you visually author and deploy resources for your data factory without having to write any code. 通过此无代码的界面,可将活动拖放到管道画布上、执行测试运行、以迭代方式进行调试,以及部署和监视管道运行。You can drag activities to a pipeline canvas, perform test runs, debug iteratively, and deploy and monitor your pipeline runs.

目前,仅在 Microsoft Edge 和 Google Chrome 中支持 Azure 数据工厂 UX。Currently, the Azure Data Factory UX is only supported in Microsoft Edge and Google Chrome.

创作画布Authoring canvas

若要打开创作画布,请单击铅笔图标。To open the authoring canvas, click on the pencil icon.


在这里,你将创作构成工厂的管道、活动、数据集、链接服务、触发器和集成运行时。Here, you will author the pipelines, activities, datasets, linked services, triggers, and integration runtimes that comprise your factory. 若要开始使用创作画布构建管道,请参阅使用复制活动复制数据To get started building a pipeline using the authoring canvas, see Copy data using the copy Activity.

表达式和函数Expressions and functions

可以使用表达式和函数代替静态值来指定 Azure 数据工厂中的许多属性。Expressions and functions can be used instead of static values to specify many properties in Azure Data Factory.

若要指定属性值的表达式,请选择“添加动态内容” 或在焦点在字段上时单击 Alt + PTo specify an expression for a property value, select Add Dynamic Content or click Alt + P while focusing on the field.


这将打开数据工厂表达式生成器,你可以从支持的系统变量、活动输出、函数和用户指定的变量或参数构建表达式。This opens the Data Factory Expression Builder where you can build expressions from supported system variables, activity output, functions, and user-specified variables or parameters.


有关表达式语言的信息,请参阅 Azure 数据工厂中的表达式和函数For information about the expression language, see Expressions and functions in Azure Data Factory.

提供反馈Provide feedback

选择“反馈”可发表有关功能的看法,或者告知 Azure 出现了工具问题 :Select Feedback to comment about features or to notify Azure about issues with the tool:


后续步骤Next steps

若要了解有关监视和管理管道的信息,请参阅以编程方式监视和管理管道To learn more about monitoring and managing pipelines, see Monitor and manage pipelines programmatically.