我有以下间隔为 15 分钟的数据。

[{
    "_id" : ObjectId("5500a5e6f37a84d0509526ba"),
    "runtimeMilliSeconds" : NumberLong("1426105802063"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 71.72000122070312,
        "currentMemoryUtilization" : 77.4000015258789
    }
}
{
    "_id" : ObjectId("5500a96af37a84d0509526f8"),
    "runtimeMilliSeconds" : NumberLong("1426106701622"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 70.30000305175781,
        "currentMemoryUtilization" : 77.4000015258789
    }
}
{
    "_id" : ObjectId("5500aceef37a84d050952739"),
    "runtimeMilliSeconds" : NumberLong("1426107601441"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 73.2300033569336,
        "currentMemoryUtilization" : 77.4000015258789
    }
}
{
    "_id" : ObjectId("5500b07ff37a84d050952776"),
    "runtimeMilliSeconds" : NumberLong("1426108501342"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 60.61000061035156,
        "currentMemoryUtilization" : 77.4000015258789
    }
}


{
    "_id" : ObjectId("5500b404f37a84d0509527b7"),
    "runtimeMilliSeconds" : NumberLong("1426109402199"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 60.060001373291016,
        "currentMemoryUtilization" : 77.41000366210938
    }
}
{
    "_id" : ObjectId("5500b788f25a6f9765950f65"),
    "runtimeMilliSeconds" : NumberLong("1426110301345"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 58.689998626708984,
        "currentMemoryUtilization" : 77.41000366210938
    }
}
{
    "_id" : ObjectId("5500bb0cf37a84d050952837"),
    "runtimeMilliSeconds" : NumberLong("1426111202063"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 70.69999694824219,
        "currentMemoryUtilization" : 77.41000366210938
    }
}
{
    "_id" : ObjectId("5500be83f25a6f9765950fde"),
    "runtimeMilliSeconds" : NumberLong("1426112101980"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 69.41000366210938,
        "currentMemoryUtilization" : 77.44000244140625
    }
}

{
    "_id" : ObjectId("5500c206f37a84d0509528ac"),
    "runtimeMilliSeconds" : NumberLong("1426113001781"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 70.63999938964844,
        "currentMemoryUtilization" : 77.44000244140625
    }
}
{
    "_id" : ObjectId("5500c58cf37a84d0509528ea"),
    "runtimeMilliSeconds" : NumberLong("1426113901510"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 68.38999938964844,
        "currentMemoryUtilization" : 77.44000244140625
    }
}
{
    "_id" : ObjectId("5500c911f25a6f97659510a0"),
    "runtimeMilliSeconds" : NumberLong("1426114801403"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 77.7300033569336,
        "currentMemoryUtilization" : 77.44999694824219
    }
}
{
    "_id" : ObjectId("5500cca0f37a84d050952968"),
    "runtimeMilliSeconds" : NumberLong("1426115702206"),
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 74.23999786376953,
        "currentMemoryUtilization" : 77.4800033569336
    }
}]

我想按小时间隔对这些数据进行分组。这意味着我想将每小时的 4 个文档分组为单个文档，这样“cpuMemoryStats”键中的值将是所有四个文档的平均值。 runtimeMilliSeconds 也是 4 个文档的平均值。

即我想要它像第一到第四，第五到第八个文档。 我想要 12 个以上文档中的 4 个文档，平均键数。

示例输出是:

[{
    "_id" : ObjectId("5500a5e6f37a84d0509526ba"),
    "runtimeMilliSeconds" : 1426107152000,
    "cpuMemoryStats" : {
        "currentCpuUtilization" : 68.96500206,
        "currentMemoryUtilization" : 77.400001526
    }
}
.
.
..
]

我尝试了以下:

db.collection.aggregate({"$match": { "hostId" : "1.1.1.1" , "customerId"   : "customerId" ,
"runtimeMilliSeconds" : { "$gte" : 1426104902206}}},

{"$group" : {"_id" : { "$subtract" :[ {"$divide" : ["$runtimeMilliSeconds", 3600 ]},

{ "$mod" : [{"$divide" : ["$runtimeMilliSeconds", 3600 ]},1] } ] },

"memoryUtilization":{"$avg":"$cpuMemoryStats.currentMemoryUtilization"},
  "runtime":{"$avg":"$runtimeMilliSeconds"}}})

如何使用mongo按小时对数据进行分组？？？

最佳答案

日期数学似乎是您存储格式的明确案例:

 db.collection.aggregate([
     { "$match": { 
         "hostId" : "1.1.1.1" , 
         "customerId" : "customerId" ,
         "runtimeMilliSeconds" : { "$gte" : 1426104902206 },
     }},
     { "$group" : {
         "_id" : { 
             "$subtract": [
                  "$runtimemilliSeconds",
                  { "$mod": [
                      "$runtimemilliSeconds",
                      1000 * 60 * 15 // 1000 ms x 60 sec * 15 mins     
                  ]}
             ]
         },
         "memoryUtilization": { "$avg": "$cpuMemoryStats.currentMemoryUtilization" },
         "runtime":{ "$avg": "$runtimeMilliSeconds" }
     }}
])

所以为了记录，除了一般结构之外，您正在寻找的是 900000 的正确“常量”，如图所示，是:

 1000 milliseconds
 x 60 seconds
 x 15 minutes

为了实际以一个小时为间隔，您只需更改数字

 1000 milliseconds
 x 60 seconds
 x 60 minutes

也就是一小时。所有的间隔都是这样完成的。但它是取模而不是除法。

关于mongodb - 如何使用mongodb对数据进行分组？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/29118751/