Reduce方法未在mongodb mapreduce中运行

Question

我需要使用一个临时变量在reduce函数中临时存储值。在我的输出日志中，结果显示reduce函数的运行次数为0。然而，一旦我执行其他类型的计算，它就会运行。

reduce函数在执行代码时无法访问prev对象。如果有任何帮助的话，我正在使用nodejs的mongojs库。

var  map = function() {
        emit(this._id,
             {
             d1: this.day_chan1,
             d2: this.day_chan2,
             d3: this.day_chan3
           });
    };       
var reduce = function(key, values) {
                       var data = {};
                       var curr = values[0];
                       data.d1 =  curr.d1 - prev.d1;
                       data.d2 =  curr.d2 - prev.d2;
                       data.d3 =  curr.d3 - prev.d3;
                       prev = curr;
                       return { timestamp: key , data: data };
        };
var prev = { d1: 0, d2: 0, d3: 0 };
this
    .db
    .mapReduce(
                  map,
                          reduce,                                                 
                          {  
                           scope: { prev : prev },
                           sort: { timestamp: 1 },
                             query: {},
                             out: 'temp'                                                  
                            }
                         ,
                         function (err, data) {                                        
                            if(err) callback(err);
                            else callback(data);
                         });

这是我正在处理的数据样本

{ 
    "_id" : ObjectId("5650845744aeea3dba90326d"), 
    "timestamp" : "2015-09-21 05:02:52", 
    "curr_property" : NumberInt(1818), 
    "curr_property_cost" : NumberInt(21), 
    "day_property" : NumberInt(30), 
    "day_property_cost" : NumberInt(18), 
    "curr_solar_generating" : NumberInt(676), 
    "curr_solar_export" : NumberInt(0), 
    "day_solar_generated" : NumberInt(11), 
    "day_solar_export" : NumberInt(0), 
    "curr_chan1" : NumberInt(676), 
    "curr_chan2" : NumberInt(676), 
    "curr_chan3" : NumberInt(466), 
    "day_chan1" : NumberInt(11), 
    "day_chan2" : NumberInt(11), 
    "day_chan3" : NumberInt(7), 
    "gatewayId" : 23.0
}
{ 
    "_id" : ObjectId("5650845744aeea3dba90326e"), 
    "timestamp" : "2015-09-21 05:03:52", 
    "curr_property" : NumberInt(1818), 
    "curr_property_cost" : NumberInt(21), 
    "day_property" : NumberInt(60), 
    "day_property_cost" : NumberInt(18), 
    "curr_solar_generating" : NumberInt(676), 
    "curr_solar_export" : NumberInt(0), 
    "day_solar_generated" : NumberInt(22), 
    "day_solar_export" : NumberInt(0), 
    "curr_chan1" : NumberInt(676), 
    "curr_chan2" : NumberInt(676), 
    "curr_chan3" : NumberInt(466), 
    "day_chan1" : NumberInt(22), 
    "day_chan2" : NumberInt(22), 
    "day_chan3" : NumberInt(15), 
    "gatewayId" : 23.0
}
{ 
    "_id" : ObjectId("5650845744aeea3dba90326f"), 
    "timestamp" : "2015-09-21 05:04:52", 
    "curr_property" : NumberInt(1818), 
    "curr_property_cost" : NumberInt(21), 
    "day_property" : NumberInt(91), 
    "day_property_cost" : NumberInt(19), 
    "curr_solar_generating" : NumberInt(676), 
    "curr_solar_export" : NumberInt(0), 
    "day_solar_generated" : NumberInt(33), 
    "day_solar_export" : NumberInt(0), 
    "curr_chan1" : NumberInt(676), 
    "curr_chan2" : NumberInt(676), 
    "curr_chan3" : NumberInt(466), 
    "day_chan1" : NumberInt(33), 
    "day_chan2" : NumberInt(33), 
    "day_chan3" : NumberInt(23), 
    "gatewayId" : 23.0
}

这是我的日志上的输出

{
    "result" : "temp",
    "timeMillis" : 3362,
    "counts" : {
        "input" : 39781,
        "emit" : 39781,
        "reduce" : 0,
        "output" : 39781
    },
    "ok" : 1
}

这就是操作后临时集合的外观

{ 
    "_id" : ObjectId("5650845744aeea3dba90326d"), 
    "value" : {
        "d1" : 11.0, 
        "d2" : 11.0, 
        "d3" : 7.0
    }
}
{ 
    "_id" : ObjectId("5650845744aeea3dba90326e"), 
    "value" : {
        "d1" : 22.0, 
        "d2" : 22.0, 
        "d3" : 15.0
    }
}
{ 
    "_id" : ObjectId("5650845744aeea3dba90326f"), 
    "value" : {
        "d1" : 33.0, 
        "d2" : 33.0, 
        "d3" : 23.0
    }
}

以下是我希望得到的

    { 
    "_id" : ObjectId("5650845744aeea3dba90326d"), 
    "value" : {
        "d1" : 0, 
        "d2" : 0, 
        "d3" : 0
    }
}
{ 
    "_id" : ObjectId("5650845744aeea3dba90326e"), 
    "value" : {
        "d1" : 11.0, 
        "d2" : 11.0, 
        "d3" : 9.0
    }
}
{ 
    "_id" : ObjectId("5650845744aeea3dba90326f"), 
    "value" : {
        "d1" : 11.0, 
        "d2" : 11.0, 
        "d3" : 18.0
    }
}

我对这件事很感兴趣，非常感谢你的帮助。

更新：

该代码目前正在mongojs中的一个服务方法中运行。这是它在mongo控制台中的等效功能。

db.testdb.mapReduce(map,
                    reduce,                                               
                    {  
                           scope: { prev : prev },
                           sort: { timestamp: 1 },
                             query: {},
                             out: 'temp'                                                  
                    });

map和reduce方法的声明与顶部的声明相同。

Answer 1

@Bazinga777因此，尽管您的map函数可以做它想要的事情并发出它想要的东西，但我将mapreduce功能解释为一件事。MongoDB不会为只有一个值的键调用reduce函数。values参数是一个数组，其元素是"映射"到该键的值对象https://docs.mongodb.org/manual/reference/command/mapReduce/#mapreduce-map cmd