{
"_id" : ObjectId("58f5a22d22679039176d2ee8"),
"MachineID" : NumberInt("1001"),
"Timestamp" : ISODate("2017-04-18T07:01:01.000+05:30"), 
"Utilization" : NumberInt("63654480"),
"RunStatus" : NumberInt("1"),   
"ProductsCount" : NumberInt("681350")   
},
{
"_id" : ObjectId("58f5a22d22679039176d2ee9"),
"MachineID" : NumberInt("1001"),
"Timestamp" : ISODate("2017-04-18T07:02:02.000+05:30"), 
"Utilization" : NumberInt("63655480"),
"RunStatus" : NumberInt("1"),   
"ProductsCount" : NumberInt("681370")   
},
{
"_id" : ObjectId("58f5a22d22679039176d2eea"),
"MachineID" : NumberInt("1001"),
"Timestamp" : ISODate("2017-04-18T07:03:02.000+05:30"), 
"Utilization" : NumberInt("63656480"),
"RunStatus" : NumberInt("0"),   
"ProductsCount" : NumberInt("681390")   
},
{
"_id" : ObjectId("58f5a22d22679039176d2eeb"),
"MachineID" : NumberInt("1001"),
"Timestamp" : ISODate("2017-04-18T07:04:02.000+05:30"), 
"Utilization" : NumberInt("63657480"),
"RunStatus" : NumberInt("1"),   
"ProductsCount" : NumberInt("681420")   
},
{
"_id" : ObjectId("58f5a22d22679039176d2eec"),
"MachineID" : NumberInt("1001"),
"Timestamp" : ISODate("2017-04-18T07:05:02.000+05:30"), 
"Utilization" : NumberInt("63658480"),
"RunStatus" : NumberInt("1"),   
"ProductsCount" : NumberInt("681450"),  
},
{
"_id" : ObjectId("58f5a22d22679039176d2eed"),
"MachineID" : NumberInt("1001"),
"Timestamp" : ISODate("2017-04-18T07:06:02.000+05:30"), 
"Utilization" : NumberInt("63659480"),
"RunStatus" : NumberInt("1"),   
"ProductsCount" : NumberInt("681470")   
},
{
"_id" : ObjectId("58f5a22d22679039176d2eee"),
"MachineID" : NumberInt("1001"),
"Timestamp" : ISODate("2017-04-18T07:07:02.000+05:30"), 
"Utilization" : NumberInt("63659780"),
"RunStatus" : NumberInt("0"),   
"ProductsCount" : NumberInt("681490")   
},
{
"_id" : ObjectId("58f5a22d22679039176d2eef"),
"MachineID" : NumberInt("1001"),
"Timestamp" : ISODate("2017-04-18T07:08:03.000+05:30"), 
"Utilization" : NumberInt("63659880"),
"RunStatus" : NumberInt("1"),   
"ProductsCount" : NumberInt("681525")   
},
{
"_id" : ObjectId("58f5a22d22679039176d2ef0"),
"MachineID" : NumberInt("1001"),
"Timestamp" : ISODate("2017-04-18T07:09:03.000+05:30"), 
"Utilization" : NumberInt("63659980"),
"RunStatus" : ("0"),
"ProductsCount" : NumberInt("681563")
}

从上述集合中，Utilization 和 ProductsCount 是累积值，并且随时间递增。

需要减去当前行的Utilization和下一行的Utilization，按升序排列。以及基于 RunStatus 的 ProductsCount 的相同操作。

如果当前行的RunStatus为1，下一行为0，则Utilization和ProductsCount的差异应该映射到RunStatus 为 0。

然后根据MachineID和RunStatus

预期结果

/* 1 */
{   
"MachineID" : 1001,
"RunStatus" : 1,
"Utilization" : 4100,
"ProducedCount" : 135
},

/* 2 */
{   
"MachineID" : NumberInt("1001"),
"RunStatus" : NumberInt("0"),
"Utilization" : 1400,
"ProducedCount" : 78
}

聚合框架需要结果。请帮忙。

这是我试过的，

db.collection.aggregate([
{ "$match" : { "$and" : [ { "MachineID" : { "$in" : [ 1001]}} , 
    { "Timestamp" : { "$gte" : ISODate("2017-04-18T01:30:00.000Z"), 
    "$lte" : ISODate("2017-04-19T01:30:00.000Z")}},]}
}, 
{
    "$addFields": {"lastUtilization": 0}
},
{
    "$addFields": {"lastProductsCount" : 0}
},
{
    "$group": {
        "_id": 
        {
             MachineID : '$MachineID',
            "RunStatus": "$RunStatus"
        },
        "Utilization" : 
        {
            "$sum" : 
            {
                "$cond": [
                        { "$ne": [ "$lastUtilization", 0 ] },
                         {"$subtract" : ["$Utilization", 
"$lastUtilization"]}, 0
                    ]
            }
        }, 
        "ProductsCount" : 
        {
            "$sum" : 
            {
                "$cond": [
                        { "$ne": [ "$lastProductsCount", 0 ] },
                         {"$subtract" : ["$ProductsCount", 
"$lastProductsCount"]}, 0
                    ]
            }
        }, 
        "lastProductsCount" : { "$avg" : "$ProductsCount"}, 
        "lastUtilization" : { "$avg" : "$Utilization"}
}
},
{
    "$project": 
    {
        "MachineID": "$_id.MachineID", 
        "RunStatus" : "$_id.RunStatus", 
        "Utilization" : "$Utilization", 
        "ProductsCount" : "$ProductsCount"
    }
},
]);

最佳答案

这是怎么回事？它不计算小时，但它会做其他所有事情。

[
    {
      $match: {
          $and: [
              {MachineID: {$in: [1001]}},
              {
                Timestamp: {
                    $gte: ISODate("2017-04-18T01:30:00.000Z"),
                    $lte: ISODate("2017-04-19T01:30:00.000Z")
                }
              }
          ]
      }
    },
    // Add all data to one array.
    {$group: {_id: "$MachineID", all: {$push: "$$ROOT"}}},
    // Create an array of (element, array index) pairs.
    {$addFields: {allWithIndex: {$zip: {inputs: ["$all", {$range: [0, {$size: "$all"}]}]}}}},
    // Create an array of {current: <element>, previous: <previous element>} pairs.
    {
      $project: {
          pairs: {
              $map: {
                  input: "$allWithIndex",
                  in : {
                      current: {$arrayElemAt: ["$$this", 0]},
                      prev: {
                          $arrayElemAt: [
                              "$all",
                              // Set prev == current for the first element.
                              {$max: [0, {$subtract: [{$arrayElemAt: ["$$this", 1]}, 1]}]}
                          ]
                      }
                  }
              }
          }
      }
    },
    // Compute the deltas.
    {$unwind: "$pairs"},
    {
      $group: {
          _id: {MachineID: "$_id", RunStatus: "$pairs.current.RunStatus"},
          ProductsCount:
              {$sum: {$subtract: ["$pairs.current.ProductsCount", "$pairs.prev.ProductsCount"]}},
          Utilization:
              {$sum: {$subtract: ["$pairs.current.Utilization", "$pairs.prev.Utilization"]}},
      }
    }
]

关于Mongodb聚合查询对累积值进行减法和分组，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/43560777/