如何在Dataweave 2.0中压缩& Nest一个(CSV)有效载荷？

Question

我有一个CSV有效载荷TV Programs & Episodes，我想将其转换（Nest & Condense）为JSON，条件如下。

• 合并连续的节目行（后面没有插曲行），这样就变成了1个节目，有第1个实例的开始日期和持续时间的总和。
• 节目行后的插曲行在节目下嵌套。

输入

Channel|Name|Start|Duration|Type
ACME|Broke Girls|2018-02-01T00:00:00|600|Program
ACME|Broke Girls|2018-02-01T00:10:00|3000|Program
ACME|S03_8|2018-02-01T00:13:05|120|Episode
ACME|S03_9|2018-02-01T00:29:10|120|Episode
ACME|S04_1|2018-02-01T00:44:12|120|Episode
ACME|Lost In Translation|2018-02-01T02:01:00|1800|Program
ACME|Lost In Translation|2018-02-01T02:30:00|1800|Program
ACME|The Demolition Man|2018-02-01T03:00:00|1800|Program
ACME|The Demolition Man|2018-02-01T03:30:00|1800|Program
ACME|The Demolition Man|2018-02-01T04:00:00|1800|Program
ACME|The Demolition Man|2018-02-01T04:30:00|1800|Program
ACME|Photon|2018-02-01T05:00:00|1800|Program
ACME|Photon|2018-02-01T05:30:00|1800|Program
ACME|Miles & Smiles|2018-02-01T06:00:00|3600|Program
ACME|S015_1|2018-02-01T06:13:53|120|Episode
ACME|S015_2|2018-02-01T06:29:22|120|Episode
ACME|S015_3|2018-02-01T06:46:28|120|Episode
ACME|Ice Age|2018-02-01T07:00:00|300|Program
ACME|Ice Age|2018-02-01T07:05:00|600|Program
ACME|Ice Age|2018-02-01T07:15:00|2700|Program
ACME|S01_4|2018-02-01T07:17:17|120|Episode
ACME|S01_5|2018-02-01T07:32:11|120|Episode
ACME|S01_6|2018-02-01T07:47:20|120|Episode
ACME|My Girl Friday|2018-02-01T08:00:00|3600|Program
ACME|S05_7|2018-02-01T08:17:28|120|Episode
ACME|S05_8|2018-02-01T08:31:59|120|Episode
ACME|S05_9|2018-02-01T08:44:42|120|Episode
ACME|Pirate Bay|2018-02-01T09:00:00|3600|Program
ACME|S01_1|2018-02-01T09:33:12|120|Episode
ACME|S01_2|2018-02-01T09:46:19|120|Episode
ACME|Broke Girls|2018-02-01T10:00:00|1200|Program
ACME|S05_3|2018-02-01T10:13:05|120|Episode
ACME|S05_4|2018-02-01T10:29:10|120|Episode

输出

{
  "programs": [
    {
      "StartTime": "2018-02-01T00:00:00",
      "Duration": 3600,
      "Name": "Broke Girls",
      "episode": [
        {
          "name": "S03_8",
          "startDateTime": "2018-02-01T00:13:05",
          "duration": 120
        },
        {
          "name": "S03_9",
          "startDateTime": "2018-02-01T00:29:10",
          "duration": 120
        },
        {
          "name": "S04_1",
          "startDateTime": "2018-02-01T00:44:12",
          "duration": 120
        }
      ]
    },
    {
      "StartTime": "2018-02-01T06:00:00",
      "Duration": 3600,
      "Name": "Miles & Smiles",
      "episode": [
        {
          "name": "S015_1",
          "startDateTime": "2018-02-01T06:13:53",
          "duration": 120
        },
        {
          "name": "S015_2",
          "startDateTime": "2018-02-01T06:29:22",
          "duration": 120
        },
        {
          "name": "S015_3",
          "startDateTime": "2018-02-01T06:46:28",
          "duration": 120
        }
      ]
    },
    {
      "StartTime": "2018-02-01T07:00:00",
      "Duration": 3600,
      "Name": "Ice Age",
      "episode": [
        {
          "name": "S01_4",
          "startDateTime": "2018-02-01T07:17:17",
          "duration": 120
        },
        {
          "name": "S01_5",
          "startDateTime": "2018-02-01T07:32:11",
          "duration": 120
        },
        {
          "name": "S01_6",
          "startDateTime": "2018-02-01T07:47:20",
          "duration": 120
        }
      ]
    },
    {
      "StartTime": "2018-02-01T08:00:00",
      "Duration": 3600,
      "Name": "My Girl Friday",
      "episode": [
        {
          "name": "S05_7",
          "startDateTime": "2018-02-01T08:17:28",
          "duration": 120
        },
        {
          "name": "S05_8",
          "startDateTime": "2018-02-01T08:31:59",
          "duration": 120
        },
        {
          "name": "S05_9",
          "startDateTime": "2018-02-01T08:44:42",
          "duration": 120
        }
      ]
    },
    {
      "StartTime": "2018-02-01T09:00:00",
      "Duration": 3600,
      "Name": "Pirate Bay",
      "episode": [
        {
          "name": "S01_1",
          "startDateTime": "2018-02-01T09:33:12",
          "duration": 120
        },
        {
          "name": "S01_2",
          "startDateTime": "2018-02-01T09:46:19",
          "duration": 120
        }
      ]
    },
    {
      "StartTime": "2018-02-01T10:00:00",
      "Duration": 1200,
      "Name": "Broke Girls",
      "episode": [
        {
          "name": "S05_3",
          "startDateTime": "2018-02-01T10:13:05",
          "duration": 120
        },
        {
          "name": "S05_4",
          "startDateTime": "2018-02-01T10:29:10",
          "duration": 120
        }
      ]
    }
  ]
}

Answer 1

试试这个，评论已嵌入。

%dw 2.0
output application/dw
var data = readUrl("classpath://data.csv","application/csv",{separator:"|"})
var firstProgram = data[0].Name
---
// Identify the programs by adding a field
(data reduce (e,acc={l: firstProgram, c:0, d: []}) -> do {
    var next = acc.l != e.Name and e.Type == "Program" 
    var counter = if (next) acc.c+1 else acc.c
    ---
    {
        l: if (next) e.Name else acc.l,
        c: counter,
        d: acc.d + {(e), pc: counter}
    }
}).d 
// group by the identifier of individual programs
groupBy $.pc
// Get just the programs throw away the program identifiers 
pluck $
// Throw away the programs with no episodes
filter ($.*Type contains "Episode")
// Iterate over the programs
map do {
    // sum the program duration
    var d = $ dw::core::Arrays::sumBy (e) -> if (e.Type == "Program") e.Duration else 0
    // Get the episodes and do a little cleanup
    var es = $ map $-"pc" filter ($.Type == "Episode")
    ---
    // Form the desired structure
    {
        ($[0] - "pc" - "Duration"),
        Duration: d,
        Episode: es 
    }
}

注1: 我把内容存储在一个文件中，然后用以下方法读取它 readUrl您需要调整以适应您的数据来源。

注2: 也许你需要重新考虑你的投入，如果可能的话，把它们组织得更好。

注3: Studio会显示错误（至少Studio 7.5.1会）。 它们是假阳性，代码运行

注4: 很多步骤，因为非平凡的输入。 Potentialy the code could be optimized but I did spend enough time on it--I 'll let you deal with the optimization or somebody else from the community can help.