Javascript 在MapReduce MongoDB中按键分组数据

我正在MongoDB中尝试MapReduce程序寻找共同的朋友，我在MongoDB中对密钥进行排序后获得了以下数据

{"user" : " Hari","friend" : "Shiva",
 "friendList": ["Hanks"," Tom"," Karma"," Hari"," Dinesh"]}


 {"user" : "Hari","friend" : " Shiva",
  "friendList" : ["Karma"," Tom"," Ram"," Bindu"," Shiva",
                   " Kishna"," Bikash"," Bakshi"," Dinesh"]}

现在，我想将这些具有相同键的数据集分组到单个组中，在将键值对发送到还原器之前，在map函数中使用Javascript，如何对数据进行分组？例如，我想要像这样的输出

{"user" : " Hari","friend" : "Shiva",
 "friendList": ["Hanks"," Tom"," Karma"," Hari"," Dinesh"],["Karma"," Tom"," Ram"," Bindu"," Shiva"," Kishna"," Bikash"," Bakshi"," Dinesh"]}

---

您可以将两条记录的

friendlist

数组合并到一个数组中，以创建如下对象：

   {
  "_id": {
    "user": " Hari",
    "friend": "Shiva"
  },
  "value": {
    "friendList": [
      "Hanks",
      " Tom",
      " Karma",
      " Hari",
      " Dinesh",
      "Karma",
      " Tom",
      " Ram",
      " Bindu",
      " Shiva",
      " Kishna",
      " Bikash",
      " Bakshi",
      " Dinesh"
    ]
  }
}

{
  "_id": {
    "user": " Hari",
    "friend": "Shiva"
  },
  "value": {
    "friendList": [
      [
        "Hanks",
        " Tom",
        " Karma",
        " Hari",
        " Dinesh"
      ],
      [
        "Karma",
        " Tom",
        " Ram",
        " Bindu",
        " Shiva",
        " Kishna",
        " Bikash",
        " Bakshi",
        " Dinesh"
      ]
    ]
  }
}

请参阅处的代码以创建此单个对象

如果希望

好友列表

为二维数组，即：

   {
  "_id": {
    "user": " Hari",
    "friend": "Shiva"
  },
  "value": {
    "friendList": [
      "Hanks",
      " Tom",
      " Karma",
      " Hari",
      " Dinesh",
      "Karma",
      " Tom",
      " Ram",
      " Bindu",
      " Shiva",
      " Kishna",
      " Bikash",
      " Bakshi",
      " Dinesh"
    ]
  }
}

{
  "_id": {
    "user": " Hari",
    "friend": "Shiva"
  },
  "value": {
    "friendList": [
      [
        "Hanks",
        " Tom",
        " Karma",
        " Hari",
        " Dinesh"
      ],
      [
        "Karma",
        " Tom",
        " Ram",
        " Bindu",
        " Shiva",
        " Kishna",
        " Bikash",
        " Bakshi",
        " Dinesh"
      ]
    ]
  }
}

---

您可以使用Friend上的代码，如果map reduce将对同一个键的值进行分组并将其作为键提供给reduce，列出[values]，那么您为什么要为同一个键的数据值分组呢

我强烈建议您在reducer中执行分组任务，而不是Map。其背后的主要原因是，由于map任务逐记录读取并执行collect操作，因此识别相同密钥组的负担由算法承担，而如何使用分组值设计输出则由我们在reduce逻辑中负责

您可以将减速机的输出用于进一步处理

输入：

{"_id" : {"user" : " Hari","friend" : "Shiva"},
 "value" : {"friendList": ["Hanks"," Tom"," Karma"," Hari"," Dinesh"]}}


 {"_id" : {"user" : "Hari","friend" : " Shiva"},
  "value" : {"friendList" : ["Karma"," Tom"," Ram"," Bindu"," Shiva",
                             " Kishna"," Bikash"," Bakshi"," Dinesh"]}}

var mapper = function () {
    var key = {"user" : this.user, "friend" : this.friend};
    emit(key, {"value":{"friendList":this.friendList}});
};

var reducer = function(key, value){
var combinedfriendList = {"friendList":[]};

    for (var i in values) {
        var inter = values[i];
        for (var j in inter.friendList) {
            combinedfriendList.friendList.push(inter.friendList[j]);
        }
    }
return {"_id": {"user":key.user, "friend": key.friend}, "value":combinedfriendList};
};

{"_id" : {"user" : " Hari","friend" : "Shiva"},
 "value" : {"friendList": ["Hanks"," Tom"," Karma"," Hari"," Dinesh","Karma"," Tom"," Ram"," Bindu"," Shiva"," Kishna"," Bikash"," Bakshi"," Dinesh"]}}

Mapreduce代码：

{"_id" : {"user" : " Hari","friend" : "Shiva"},
 "value" : {"friendList": ["Hanks"," Tom"," Karma"," Hari"," Dinesh"]}}


 {"_id" : {"user" : "Hari","friend" : " Shiva"},
  "value" : {"friendList" : ["Karma"," Tom"," Ram"," Bindu"," Shiva",
                             " Kishna"," Bikash"," Bakshi"," Dinesh"]}}

var mapper = function () {
    var key = {"user" : this.user, "friend" : this.friend};
    emit(key, {"value":{"friendList":this.friendList}});
};

var reducer = function(key, value){
var combinedfriendList = {"friendList":[]};

    for (var i in values) {
        var inter = values[i];
        for (var j in inter.friendList) {
            combinedfriendList.friendList.push(inter.friendList[j]);
        }
    }
return {"_id": {"user":key.user, "friend": key.friend}, "value":combinedfriendList};
};

{"_id" : {"user" : " Hari","friend" : "Shiva"},
 "value" : {"friendList": ["Hanks"," Tom"," Karma"," Hari"," Dinesh","Karma"," Tom"," Ram"," Bindu"," Shiva"," Kishna"," Bikash"," Bakshi"," Dinesh"]}}

预期输出：

{"_id" : {"user" : " Hari","friend" : "Shiva"},
 "value" : {"friendList": ["Hanks"," Tom"," Karma"," Hari"," Dinesh"]}}


 {"_id" : {"user" : "Hari","friend" : " Shiva"},
  "value" : {"friendList" : ["Karma"," Tom"," Ram"," Bindu"," Shiva",
                             " Kishna"," Bikash"," Bakshi"," Dinesh"]}}

var mapper = function () {
    var key = {"user" : this.user, "friend" : this.friend};
    emit(key, {"value":{"friendList":this.friendList}});
};

var reducer = function(key, value){
var combinedfriendList = {"friendList":[]};

    for (var i in values) {
        var inter = values[i];
        for (var j in inter.friendList) {
            combinedfriendList.friendList.push(inter.friendList[j]);
        }
    }
return {"_id": {"user":key.user, "friend": key.friend}, "value":combinedfriendList};
};

{"_id" : {"user" : " Hari","friend" : "Shiva"},
 "value" : {"friendList": ["Hanks"," Tom"," Karma"," Hari"," Dinesh","Karma"," Tom"," Ram"," Bindu"," Shiva"," Kishna"," Bikash"," Bakshi"," Dinesh"]}}

---

希望这能给你一些帮助。你可以在你的环境中测试它（如果需要，可以更改）并分享你的反馈。

你可以简单地进行

聚合

，根据用户和朋友字段进行

$group

db.collection.aggregate([
{$group:{
_id:{
       user:'$user',
       friend:'$friend'
    },
    friendList:{$push:'$friendList'}
}},

// project the fields as your wish
{$project:{
    user:'$_id.user',
    friend:'$_id.friend',
    friendList:'$friendList'
}}
])

---

希望此聚合管道可以返回您期望的结果

这里我希望输出包含两个数组，正如我上面所指出的，我正在使用javascript实现mapreduce函数，我不知道更多的javascript，所以我可以按上面的格式获取它吗？这不是有效的JSON:

{“friendList”：[“Hanks”、“Tom”、“Karma”、“Hari”、“Dinesh”]，[“Karma”，“汤姆”、“拉姆”、“宾都”、“湿婆”、“基须那”、“比卡什”、“巴克什”、“迪内什”]}

所以我创建了一个串联数组。请为最终的

好友列表提供一个有效的JSON

另请参见编辑后的答案以创建一个二维

好友列表

我已经尝试了，但无法得到我想要的…..我想你会清楚我在做什么…非常感谢你的帮助我的朋友..@bikas请参考我的直肠请不要发表评论，希望能有所帮助