Javascript MongoDB:aggregate函数中字符串字段的parseFloat（$avg）

我正在Mongo中存储一些包含任意字段的数据。此字段存储为字符串，但可以包含二进制数据、整数、浮点或其他任何内容（取决于应用程序和另一个字段“Type”）。无论如何，假设我确实知道我查询的文档在这个字段中存储了以字符串形式键入的浮动值，我想知道这些值在特定日期范围内的平均值。不幸的是，根据，它忽略了任何非数值的值。有没有办法强制parseFloat或类似的东西动态转换文档值以安抚$avg操作符

文档结构示例：

{
    "_id": ObjectId("540f4e29f287300b9097663d"),
    "DateReceived": ISODate("2014-09-09T18:59:53.717Z"),
    "Message": {
        "Version": 1,
        "Source": {
            "Device": "MS02166",
            "Application": "Performance Counter",
            "Category": "Disk - Reads/sec",
            "OriginDate": ISODate("2014-09-09T18:59:51.256Z"),
            "Level": 2
        },
        "PayloadText": "0"
    }
}

我平均的字段是

Message.PayloadText

（在本例中为0，但存在非零文档）

我能够生成的聚合管道查询是：

[{
    "$match": {
        "Message.Source.Application": "Performance Counter"
    }
}, {
    "$match": {
        "Message.Source.Category": "Processor"
    }
}, {
    "$match": {
        "Message.Source.Level": 2
    }
}, {
    "$match": {
        "Message.Source.Device": "MS02166"
    }
}, {
    "$match": {
        "DateReceived": {
            "$gte": ISODate("2014-09-14T07:00:00Z"),
            "$lt": ISODate("2014-09-15T07:00:00Z")
        }
    }
}, {
    "$group": {
        "_id": {
            "hour": {
                "$hour": "$DateReceived"
            }
        },
        "AvgUsage": {
            "$avg": "$Message.PayloadText"
        },
        "MinUsage": {
            "$min": "$Message.PayloadText"
        },
        "MaxUsage": {
            "$max": "$Message.PayloadText"
        }
    }
}]

我尝试了一些类似于

“$avg”：“parseFloat（$Message.PayloadText）”

和

“$avg”：“$parseFloat（$Message.PayloadText）”

的操作，但都没有成功。奇怪的是，$min和$max操作符确实产生了一个有意义的结果（下面的示例结果）

---

如果想要平均值，则需要存储一个数字。没有任何类型转换函数可用于将数字的字符串表示形式映射到数字

$min

和

$max

之所以有效，是因为每个BSON类型（包括字符串）以及不同BSON类型之间都定义了一个顺序，所以MongoDB始终可以找到任何字段的最大值

{ "_id" : { "hour" : 7 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }
{ "_id" : { "hour" : 8 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }
{ "_id" : { "hour" : 9 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }
{ "_id" : { "hour" : 10 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.858578" }
{ "_id" : { "hour" : 11 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.999424" }
{ "_id" : { "hour" : 12 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.999424" }
{ "_id" : { "hour" : 21 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.999424" }
{ "_id" : { "hour" : 16 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }
{ "_id" : { "hour" : 15 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }
{ "_id" : { "hour" : 23 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }
{ "_id" : { "hour" : 18 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "94.02982" }
{ "_id" : { "hour" : 0 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }
{ "_id" : { "hour" : 20 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }
{ "_id" : { "hour" : 22 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "98.48484" }
{ "_id" : { "hour" : 13 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }
{ "_id" : { "hour" : 17 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "98.76543" }
{ "_id" : { "hour" : 14 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "97.18308" }
{ "_id" : { "hour" : 19 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }
{ "_id" : { "hour" : 1 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }
{ "_id" : { "hour" : 4 }, "AvgUsage" : 0, "MinUsage" : "0", "MaxUsage" : "9.37442" }