使用scala中的RDD和集合

我有下面的函数,它采用类似类型的方法数组( type Likes=Int ) 以及一个类似类型数量的RDD(像矢量)。对于likesVector RDD中的每个数字,它计算平均数数组中每个平均数的距离,并选择距离最小的平均数。( val distance = (mean-number).abs )而我期望的结果是 Map[Likes,Array[Likes]] ,我得到一张空地图。 地图[喜欢,数组[喜欢]] 表示 (mean->Array of number-nearest numbers) . 实现这一目标的最佳方法是什么?我怀疑这与scala集合的可变性有很大关系。

def assignDataPoints(means:Array[Likes],likesVector:RDD[Likes]): Map[Likes,Array[Likes]] ={         
        var likes_Mean = IntMap(1->1)
        var likes_mean_final = mutable.Map.empty[Likes,Array[Likes]]
        likesVector.map(dataPoint => {
          means.foldLeft(Array.empty[Likes])( (accumulator, mean)=> {
            val dist= computeDistance(dataPoint,mean)
            val nearestMean = if (dist < accumulator(0)) {
              accumulator(0)=dist
              accumulator(0)
            } else{
              accumulator(0)
            }
            val b= IntMap(nearestMean.toInt -> dataPoint)
            println("b:"+ b)
            likes_mean_final ++ likes_Mean.intersectionWith(b,(_, av, bv: Likes) => Array(av, bv))
            accumulator
          })})        
        likes_mean_final.toMap
      }