DataweAve 转换：如何转换、连接、求和项目数组

Question

您能否帮忙将以下输入数据转换为给定的输出：

输入：

[
{
    "ID_TYPE": "4",
    "DATE": "20230529",
    "ADM_TIME": "17:00",
    "PAYLOAD_NUMBER": "597418",
    "PAYLOAD_COMMENT": "HELLO"
},
{
    "ID_TYPE": "4",
    "DATE": "20230531",
    "ADM_TIME": "17:00",
    "PAYLOAD_NUMBER": "597418",
    "PAYLOAD_COMMENT": "HELLO"
},
{
    "ID_TYPE": "4",
    "DATE": "20230602",
    "ADM_TIME": "17:00",
    "PAYLOAD_NUMBER": "597418",
    "PAYLOAD_COMMENT": "HELLO"
},
{
    "ID_TYPE": "4",
    "DATE": "20230628",
    "ADM_TIME": "8:00",
    "PAYLOAD_NUMBER": "597500",
    "PAYLOAD_COMMENT": "Comments"
},
{
    "ID_TYPE": "4",
    "DATE": "20230628",
    "ADM_TIME": "17:00",
    "PAYLOAD_NUMBER": "597500",
    "PAYLOAD_COMMENT": "Comments"
},
{
    "ID_TYPE": "4",
    "DATE": "20230629",
    "ADM_TIME": "12:00",
    "PAYLOAD_NUMBER": "597500",
    "PAYLOAD_COMMENT": "Comments"
},
{
    "ID_TYPE": "4",
    "DATE": "20230630",
    "ADM_TIME": "17:00",
    "PAYLOAD_NUMBER": "597500",
    "PAYLOAD_COMMENT": "Comments"
},
{
    "ID_TYPE": "4",
    "DATE": "20230702",
    "ADM_TIME": "12:00",
    "PAYLOAD_NUMBER": "597500",
    "PAYLOAD_COMMENT": "Comments"
}
]

输出：

[
    {
            "TIMES": "17:00",
            "MORNING": "0",
            "NOON": "0",
            "EVENING": "3",
            "TOTAL_QUANTITY": "3",
            "DATES": "2023/05/29, 2023/06/02, 2023/05/31",
            "PAYLOAD_NUMBER": "597418",
            "PAYLOAD_COMMENT": "HELLO"
        },
        {
            "TIMES": "8:00, 12:00, 17:00",
            "MORNING": "1",
            "NOON": "2",
            "EVENING": "2",
            "TOTAL_QUANTITY": "5",
            "DATES": "2023/06/28, 2023/06/29, 2023/06/30, 2023/07/02",
            "PAYLAOD_NUMBER": "597500",
            "PAYLOAD_COMMENT": "Comments"
        }
    ]

如果输入是 groupby PAYLOAD_NUMBER 那么：

• TIMES 是输入数据中的 ADM_TIME 列表，
• 早上，00:01 到 09:59 之间的时间计数，
• 中午，10:00 到 14:59 之间的次数，
• 晚上，计算 15:00PM 至 23:59 之间的次数，
• TOTAL_QUANTITY 是 MORNING、NOON 和 Evening 之间的总和，
• DATES 是 DATE 的列表。

谢谢你。

Answer 1

您需要使用 groupBy() 然后 mapObject() 根据需要对每个组进行汇总、排序和格式化，然后获取结果列表。

%dw 2.0
output application/json
fun normalizeTime(t: String)= t as LocalTime  {format: "H:mm"} as String {format: "HH:mm"}
fun normalizeDate(d: String)= d as Date {format: "yyyyMMdd"} as String {format: "yyyy/MM/dd"}
---
payload 
    groupBy ($.PAYLOAD_NUMBER)
    mapObject ((value, key, index) -> (key): {
        TIMES: value.*ADM_TIME distinctBy $ orderBy normalizeTime($) joinBy " ",
        MORNING: sizeOf(value.ADM_TIME filter (normalizeTime($) >= "00:00" and normalizeTime($) <= "09:59" )),
        NOON: sizeOf(value.ADM_TIME filter (normalizeTime($) >= "10:00" and normalizeTime($) <= "14:59" )),
        EVENING: sizeOf(value.ADM_TIME filter (normalizeTime($) >= "15:00" and normalizeTime($) <= "23:59" )),
        TOTAL_QUANTITY: sizeOf(value),
        DATES: value.*DATE distinctBy $ orderBy $ map normalizeDate($) joinBy " ",
        PAYLAOD_NUMBER: key as String,
        PAYLOAD_COMMENT: value[0].PAYLOAD_COMMENT
    })
    pluck ($)

输出：

[
  {
    "TIMES": "17:00",
    "MORNING": 0,
    "NOON": 0,
    "EVENING": 3,
    "TOTAL_QUANTITY": 3,
    "DATES": "2023/05/29 2023/05/31 2023/06/02",
    "PAYLAOD_NUMBER": "597418",
    "PAYLOAD_COMMENT": "HELLO"
  },
  {
    "TIMES": "8:00 12:00 17:00",
    "MORNING": 1,
    "NOON": 2,
    "EVENING": 2,
    "TOTAL_QUANTITY": 5,
    "DATES": "2023/06/28 2023/06/29 2023/06/30 2023/07/02",
    "PAYLAOD_NUMBER": "597500",
    "PAYLOAD_COMMENT": "Comments"
  }
]

我添加了缺失的“00:00”时间。随意改变。它