我有一个有列的电影数据库 userId , movieId , movie-categoryId , reviewId , movieRating 以及 reviewDate .
在我的Map器中，我想提取userid->（movieid，movierating）
然后在reducer中，我想把所有的movieid，movierating对按用户分组。
以下是我的尝试：
Map功能：

var map = function() {
    var values={movieId : this.movieId, movieRating : this.movieRating};
    emit(this.userId, values);}

减少功能：

var reduce = function(key,values) {
    var ratings = [];
    values.forEach(function(V){
        var temp = {movieId : V.movieId, movieRating : V.movieRating};
        Array.prototype.push.apply(ratings, temp);
        });
    return {userId : key, ratings : ratings };
}

运行mapreduce:

db.ratings.mapReduce(map, reduce, { out: "map_reduce_step1" })

输出： db.map_reduce_step1.find() ```
{ "_id" : 1, "value" : { "userId" : 1, "ratings" : [ ] } }
{ "_id" : 2, "value" : { "userId" : 2, "ratings" : [ ] } }
{ "_id" : 3, "value" : { "userId" : 3, "ratings" : [ ] } }
{ "_id" : 4, "value" : { "userId" : 4, "ratings" : [ ] } }
{ "_id" : 5, "value" : { "userId" : 5, "ratings" : [ ] } }
{ "_id" : 6, "value" : { "userId" : 6, "ratings" : [ ] } }
{ "_id" : 7, "value" : { "userId" : 7, "ratings" : [ ] } }
{ "_id" : 8, "value" : { "userId" : 8, "ratings" : [ ] } }
{ "_id" : 9, "value" : { "userId" : 9, "ratings" : [ ] } }
{ "_id" : 10, "value" : { "userId" : 10, "ratings" : [ ] } }
{ "_id" : 11, "value" : { "userId" : 11, "ratings" : [ ] } }
{ "_id" : 12, "value" : { "userId" : 12, "ratings" : [ ] } }
{ "_id" : 13, "value" : { "userId" : 13, "ratings" : [ ] } }
{ "_id" : 14, "value" : { "userId" : 14, "ratings" : [ ] } }
{ "_id" : 15, "value" : { "movieId" : 1, "movieRating" : 3 } }
{ "_id" : 16, "value" : { "userId" : 16, "ratings" : [ ] } }

我没有得到预期的产出。事实上，这个输出对我来说毫无意义！
下面是我在reducer中尝试做的python等价物（以防上面没有明确reducer的用途）：

def reducer_ratings_by_user(self, user_id, itemRatings):
#Group (item, rating) pairs by userID
ratings = []
for movieID, rating in itemRatings:
ratings.append((movieID, rating))
yield user_id, ratings

编辑1@chridam
以下是我在这里真正想做的事情的概要：
movies.csv文件如下所示：
userid，movieid，moviecategoryid，reviewid，movierating，reviewdate
1,1,1,1,5,7/12/2000
2,1,1,2,5,7/12/2000
3,1,1,3,5,7/12/2000
4,1,1,4,4,7/12/2000
5,1,1,5,4,7/12/2000
6,1,1,6,5,7/15/2000
1,2,1,7,4,7/25/2000
8,1,1,8,4,7/28/2000
9,1,1,9,3,8/3/2000
...
...
我将其导入mongodb：

mongoimport --db SomeName --collection ratings --type csv --headerline --file Movies.csv

然后我尝试应用上面定义的map reduce函数。之后，我将通过执行以下操作将其导出回csv：

mongoexport --db SomeName --collection map_reduce_step1 --csv --out movie_ratings_out.csv --fields ...

这个 `movie_ratings_out.csv` 文件应如下所示：
userid，movieid1，rating1，movieid2，rating2，。。。
1,1,5,2,4
...
...
因此，每一行都包含每个用户的所有（电影、分级）对。
编辑2
样品：

db.ratings.find().pretty()
{
"_id" : ObjectId("57f4a0dd9cb74fc4d344a40f"),
"userId" : 4,
"movieId" : 1,
"movie-categoryId" : 1,
"reviewId" : 4,
"movieRating" : 4,
"reviewDate" : "7/12/2000"
}
{
"_id" : ObjectId("57f4a0dd9cb74fc4d344a410"),
"userId" : 5,
"movieId" : 1,
"movie-categoryId" : 1,
"reviewId" : 5,
"movieRating" : 4,
"reviewDate" : "7/12/2000"
}
{
"_id" : ObjectId("57f4a0dd9cb74fc4d344a411"),
"userId" : 4,
"movieId" : 2,
"movie-categoryId" : 1,
"reviewId" : 6,
"movieRating" : 5,
"reviewDate" : "7/15/2000"
}
{
"_id" : ObjectId("57f4a0dd9cb74fc4d344a412"),
"userId" : 4,
"movieId" : 3,
"movie-categoryId" : 1,
"reviewId" : 2,
"movieRating" : 5,
"reviewDate" : "7/12/2000"
}
...

在mapreduce之后，预期的输出json是：

{
"_id" : ....,
"userId" : 4,
"movieList" : [ {
"movieId" : 2
"movieRating" : 5
},
{
"movieId" : 1
"movieRating" : 4
}
...
]
}
{
"_id" : ....,
"userId" : 5,
"movieList" : ...
}
...