有没有办法使用 Dataweave 地图创建更灵活的循环？

Question

我有一个问题，用任何其他语言都需要十秒钟，但在这里我无法使用 Dataweave 解决它。

我的 JSON 看起来像这样：

{
    "100": [{
        "courseID": "100",
        "course": "physics",
        "instructor": "John S",
        "section": "A",
        "date": "01-01-1900"
    }],
    "200": [{
        "courseID": "200",
        "course": "math",
        "instructor": "Jim R",
        "section": "A",
        "date": "01-03-1900"
    },
    {
        "courseID": "200",
        "course": "math",
        "instructor": "Jim R",
        "section": "B",
        "date": "01-07-1900"
    },
    {
        "courseID": "200",
        "course": "math",
        "instructor": "Jim R",
        "section": "C",
        "date": "01-08-1900"
    }

    ]}
}

我确定数组中的对象包含重复信息，但部分和日期除外。所以我需要把它浓缩转化成这样：

{
    "courses": [{
        "courseID": "100",
        "course": "physics",
        "instructor": "John S",
        "sections": [{
            "section": "A",
            "date": "01-01-1900"
        }]
    },
    {
        "courseID": "200",
        "course": "math",
        "instructor": "Jim R",
        "sections": [{
            "section": "A",
            "date": "01-03-1900"
        },
        {
            "section": "B",
            "date": "01-07-1900"
        },
        {
            "section": "C",
            "date": "01-08-1900"
        }]
]}

我不能让这发生。我已经尝试了所有可以看到的方法来迭代文档，使用 map()、mapObject() 和 pluck()。我认为它们需要嵌套，我只想从它迭代的第一门课程中提取 ID、课程和讲师，然后继续使用部分数据构建对象。嵌套似乎会引起问题，因为对象和数组混合在一起，如果嵌套函数返回错误的类型，则 map() 和 mapObject() 会抱怨。这是我一直在尝试但没有成功的事情：

%dw 2.0
output application/json
---
"courses": payload.pluck(courseValue, courseKey, courseIndex) -> 
               courseValue map (classValue, classKey, classIndex) ->
                   { courseID: classValue.courseID,
                     instructor: classValue.instructor
                     etc...
 }

我希望一切都清楚。我被它弄乱了这么久已经筋疲力尽了。有没有可能我想做的事情对 DW 来说太复杂了，我应该使用另一种方法？

Answer 1

此解决方案应适用于所有 DataWeave 版本

courses: (payload pluck $$) map using (c = payload[$]) {
  courseID : $,
  course: c[0].course,
  instructor: c[0].instructor,
  sections: c map {
    section: $.section,
    date: $.date
  }
}

此解决方案在 Mule 3.x 中有效，但在 4.x 中无效，此博客文章“从对象到数组的自动强制转换”下对此进行了解释：https://blogs.mulesoft.com/dev/mule-dev/dataweave-mule-4-beta-syntax-changes-part-1/

courses: payload map {
  courseID: $[0].courseID,
  course: $[0].course,
  instructor: $[0].instructor,
  sections: $ map {
    section: $.section,
    date: $.date
  }
}

Answer 2

我看到您使用的是 DataWeave 2.0。这是您可以使用的简单 DataWeave 转换器。

变压器：

        <ee:transform doc:name="Transform Message" >
            <ee:message >
                <ee:set-payload ><![CDATA[%dw 2.0
output application/json
---
{
    courses: (payload pluck $$) map ((courseValue, courseKey) -> {
        courseID: payload[courseValue][0].courseID,
        course: payload[courseValue][0].course,
        instructor: payload[courseValue][0].instructor,
        sections: payload[courseValue] map ((sectionValue, sectionKey) -> {
            section: sectionValue.section,
            date: sectionValue.date
        }) 
    })  
}
]]></ee:set-payload>
            </ee:message>
        </ee:transform>

输入：

{
  "100": [
    {
      "courseID": "100",
      "course": "physics",
      "instructor": "John S",
      "section": "A",
      "date": "01-01-1900"
    }
  ],
  "200": [
    {
      "courseID": "200",
      "course": "math",
      "instructor": "Jim R",
      "section": "A",
      "date": "01-03-1900"
    },
    {
      "courseID": "200",
      "course": "math",
      "instructor": "Jim R",
      "section": "B",
      "date": "01-07-1900"
    },
    {
      "courseID": "200",
      "course": "math",
      "instructor": "Jim R",
      "section": "C",
      "date": "01-08-1900"
    }
  ]
}

输出：

{
  "courses": [
    {
      "courseID": "100",
      "course": "physics",
      "instructor": "John S",
      "sections": [
        {
          "section": "A",
          "date": "01-01-1900"
        }
      ]
    },
    {
      "courseID": "200",
      "course": "math",
      "instructor": "Jim R",
      "sections": [
        {
          "section": "A",
          "date": "01-03-1900"
        },
        {
          "section": "B",
          "date": "01-07-1900"
        },
        {
          "section": "C",
          "date": "01-08-1900"
        }
      ]
    }
  ]
}