MongoDB groupby与regex

Question

说，有两个这样的文件

{
    "_id" : ObjectId("56554226da00060cd7dd7db5"),
    "SegmentName" : "LTV90-Sub Prime",
    "Segment_Behaviour" : "LTV90",
    "Segment_Risk" : "Sub Prime",
    "CohortMonthYear" : "01-01-2010",
    "CohortQuarterYear" : "Q1 2010",
    "DriverName" : "Active rate",
    "MonthsOnBooks" : 2,
    "DriverValue" : 0.9315880000000000,
    "Accounts" : 5400,
    "PortfolioId" : ObjectId("56554225c95a8a161c262853")
}

{
    "_id" : ObjectId("56554226da00060cd7dd7db4"),
    "SegmentName" : "LTV140-Near Prime",
    "Segment_Behaviour" : "LTV140",
    "Segment_Risk" : "Near Prime",
    "CohortMonthYear" : "01-01-2010",
    "CohortQuarterYear" : "Q1 2010",
    "DriverName" : "Active rate",
    "MonthsOnBooks" : 1,
    "DriverValue" : 0.9800000000000000,
    "Accounts" : 5400,
    "PortfolioId" : ObjectId("56554225c95a8a161c262853")
}

当正则表达式“Segment_”匹配时，我需要进行聚合并提取所有字段名称和值。

目前我正在使用PortfolioId匹配文档，然后使用以下查询聚合SegmentName，Accounts。

db.PortfolioData.aggregate([{$match:{PortfolioId:ObjectId("56554225c95a8a161c262853")}},
            {"$group": {
                "_id": {"PortfolioId": "$PortfolioId", "SegmentName": "$SegmentName", "Accounts": "$Accounts"},}}]
            );

现在，当正则表达式与“Segment _”匹配时，我还需要获取字段名称和值。

当前结果

{
    "result" : [ 
        {
            "_id" : {
                "PortfolioId" : ObjectId("56554225c95a8a161c262853"),
                "SegmentName" : "LTV90-Sub Prime",
                "Accounts" : 5400
            }
        }, 
        {
            "_id" : {
                "PortfolioId" : ObjectId("56554225c95a8a161c262853"),
                "SegmentName" : "LTV140-Near Prime",
                "Accounts" : 24718
            }
        }, 
   ],
    "ok" : 1.0000000000000000
}

预期结果：

{
    "result": [
        {
            "_id": {
                "PortfolioId": ObjectId("56554225c95a8a161c262853"),
                "SegmentName": "LTV90-Sub Prime",
                "Segment_Behaviour": "LTV90",
                "Segment_Risk": "Sub Prime",
                "Accounts": 7675
            }
        },
        {
            "_id": {
                "PortfolioId": ObjectId("56554225c95a8a161c262853"),
                "SegmentName": "LTV140-Near Prime",
                "Segment_Behaviour": "LTV140",
                "Segment_Risk": "Near Prime",
                "Accounts": 24718
            }
        },
    ],
    "ok": 1.0000000000000000
}

由于