运行 Azure Data Flow 脚本/Expression Builder 中的代码片段的简单方法?

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英文:

An easy way of running code snippets written in Azure Data Flow script / Expression Builder?

问题

Sure, here are the translated parts:

一些背景:
当您使用Azure数据工厂时,您可以创建“数据流”,其中包含图形逻辑砖块,这些砖块本身可以使用嵌入的代码编辑器(“数据流表达式生成器”)来转换数据,允许您执行以Azure数据流脚本为基础的脚本(请参见图片)。

问题:

  1. 这个语言的真正名称是什么?它有更常见的名称吗?这种语言是另一种更广泛采用的语言的孪生兄弟吗?

  2. 是否有一种简单的方式来执行它的代码片段?如今,您可以直接在Web浏览器中执行C#或许多其他语言,例如“Fiddle”等网站。是否有一个地方我可以测试这种脚本语言的简单脚本,而不必设置Azure数据流,这些令人难以阅读和运行速度令人难以忍受?

注:我的具体用例是我想快速测试一些正则表达式和文本替换,但即使在调试模式下也非常慢,每次更改后运行流程需要几分钟。

英文:

Some context :
When you use Azure Data Factory, you can create "Data Flows" which in turn contain graphical logic bricks, which themselves can transform data with an embedded code editor (the "Dataflow expression builder") that lets you execute scripts written in a native language called Azure Data Flows script (see picture).

运行 Azure Data Flow 脚本/Expression Builder 中的代码片段的简单方法?

Questions:

  1. Is that the real name of this language? Does it have a more common name? Is this language the twin brother of another, more widely adopted language?

  2. Is there an easy way of executing code snippets of it? Nowadays you can execute C# or many other languages directly in the web browser, with sites such as "Fiddle" and whatnot. Is there a place where I can test simple scripts of this scripting language without all the hassle of setting up Azure Data Flows, which are unbearably unreadable and unbearably slow?

Note: My specific use case is that I quickly want to test some regExp and text replacement, but even the Debug mode is excruciatingly slow, it takes several minutes to run the flow after each change.

答案1

得分: 1

这种语言是数据流表达式语言。数据流在运行时作为Spark笔记本执行,因此代码最终会转换为Scala。

由于转换是在内部处理的,您无法插入自定义代码片段。Synapse更容易支持自定义笔记本,而不是Data Factory。

英文:

The language is the Data Flow Expression language. Data Flows are executed as Spark Notebooks at run time, so the code is ultimately converted to Scala.

Since the conversion is handled internally, there is no way for you to interject custom code snippets. Synapse can more readily support custom notebooks than Data Factory.

答案2

得分: 0

如果您正在操作管道级别(而非数据流级别),则可以创建一个“设置变量”活动,将表达式的结果放入其中。至少这样您可以查看任何文本转换或其他容易出错的脚本的结果。

英文:

If you're working at Pipeline level (not data flow level) then you may create a "set Variable" activity where you put the result of the expression. At least it lets you see the result of any text transformation or any other error-prone script.

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  • 本文由 发表于 2023年4月19日 22:52:27
  • 转载请务必保留本文链接:https://go.coder-hub.com/76055936.html
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