mapReduce

//例子1函数准备：
function map(){
	emit(this.name,{count:1});
}

> function reduce(key,value){
...  var result = {count:0};
...  for(var i=0;i<value.length;i++){
...  result.count += value[i].count;
...  }
...  result.ext = "haha";
...  return result;
...  }

//对比例子1-1：
> db.person.find()
{ "_id" : ObjectId("566e89f8382a8419511d02ab"), "name" : "hxc", "age" : 20 }
{ "_id" : ObjectId("566e8a0c382a8419511d02ac"), "name" : "hxc", "age" : 24 }
{ "_id" : ObjectId("566e8a1c382a8419511d02ad"), "name" : "zjl", "age" : 34 }
{ "_id" : ObjectId("566e8a1c382a8419511d02ad"), "name" : "zjl", "age" : 26 }
{ "_id" : ObjectId("566e8a32382a8419511d02ae"), "name" : "xx", "age" : 32 }
{ "_id" : ObjectId("566e8a42382a8419511d02af"), "name" : "abcdweb", "age" : 32 }
{ "_id" : ObjectId("566e8a52382a8419511d02b0"), "name" : "abcdweb", "age" : 32 }
{ "_id" : ObjectId("566e8a5f382a8419511d02b1"), "name" : "xx", "age" : 32 }
> db.person.mapReduce(map,reduce,{"out":"collection"})
{
        "result" : "collection",
        "timeMillis" : 285,
        "counts" : {
                "input" : 8,
                "emit" : 8,
                "reduce" : 4,		//此值为4
                "output" : 4
        },
        "ok" : 1
}
> db.collection.find()
{ "_id" : "abcdweb", "value" : { "count" : 2, "ext" : "haha" } }
{ "_id" : "hxc", "value" : { "count" : 2, "ext" : "haha" } }
{ "_id" : "xx", "value" : { "count" : 2, "ext" : "haha" } }
{ "_id" : "zjl", "value" : { "count" : 2, "ext" : "haha" } }

//对比例子1-2：
> db.person.find()
{ "_id" : ObjectId("566e8a1c382a8419511d02ad"), "name" : "zjl", "age" : 34 }
{ "_id" : ObjectId("566e8a32382a8419511d02ae"), "name" : "xx", "age" : 32 }
{ "_id" : ObjectId("566e8a5f382a8419511d02b1"), "name" : "xx", "age" : 32 }
{ "_id" : ObjectId("566e8fdd382a8419511d02b2"), "name" : "zjl", "age" : 26 }
{ "_id" : ObjectId("566e90a4382a8419511d02b3"), "name" : "hxc", "age" : 20 }
{ "_id" : ObjectId("566e90bd382a8419511d02b4"), "name" : "abcdweb", "age" : 32 }
> db.person.mapReduce(map,reduce,{"out":"collection"})
{
        "result" : "collection",
        "timeMillis" : 271,
        "counts" : {
                "input" : 6,
                "emit" : 6,
                "reduce" : 2,		//此值为2
                "output" : 4
        },
        "ok" : 1
}
> db.collection.find()
{ "_id" : "abcdweb", "value" : { "count" : 1 } }
{ "_id" : "hxc", "value" : { "count" : 1 } }		//留意，此行和上一行均没有“ext”字段，表明该两组并没有执行reduce函数；value为emit的value
{ "_id" : "xx", "value" : { "count" : 2, "ext" : "haha" } }
{ "_id" : "zjl", "value" : { "count" : 2, "ext" : "haha" } }
>

总结：map是哪来分组的，具体实现是通过emit，emit的key则为分组字段，其value的集合（即数组）会传给reduce函数执行，
	若value集合长度小于2，则该分组不会传到reduce函数执行（因为reduce的字面意思是“简化”，是将集合数据进行精简，统计获取一个结果；而若集合只有一条数据，根本就不需要统计了

 

更多用法，参考：

MongoDB:MapReduce基础及实例

MongoDB MapReduce学习笔记