我使用spark和scala来实现一个问题。我使用的是movielens数据集，其中包含ratings.csv文件、movie.csv和tag.csv。我想用基于域的方法来计算标签之间的余弦相似度，我把两个文件转换成一个字符串，然后计算相似度。
代码：

val lines=Source.fromURL(Source.getClass().getResource("file:///usr/loca/spark/dataset/algorithm3/comedy")).mkString("\n")

      val lines2=Source.fromURL(Source.getClass().getResource("file:///usr/local/spark/dataset/algorithm3/funny")).mkString("\n")

   val result=textCosine(lines,lines2)
   println("The cosine similarity score: "+result)
  }

  def module(vec:Vector[Double]): Double ={
    math.sqrt(vec.map(math.pow(_,2)).sum)
  }

  def innerProduct(v1:Vector[Double],v2:Vector[Double]): Double ={
    val listBuffer=ListBuffer[Double]()
    for(i<- 0 until v1.length; j<- 0 until v2.length;if i==j){
      if(i==j){
        listBuffer.append( v1(i)*v2(j) )
      }
    }
    listBuffer.sum
  }

  def cosvec(v1:Vector[Double],v2:Vector[Double]):Double ={
    val cos=innerProduct(v1,v2) / (module(v1)* module(v2))
    if (cos <= 1) cos else 1.0
  }

  def textCosine(lines:String,lines2:String):Double={
         val set=mutable.Set[Char]() 
    lines.foreach(set +=_)
    lines2.foreach(set +=_)
    println(set)
    val ints1: Vector[Double] = set.toList.sorted.map(ch => {
      lines.count(s => s == ch).toDouble
    }).toVector
    println("===ints1: "+ints1)
    val ints2: Vector[Double] = set.toList.sorted.map(ch => {
      lines2.count(s => s == ch).toDouble
    }).toVector
    println("===ints2: "+ints2)
    cosvec(ints1,ints2)
  }

}

但是输出给我错误：

Exception in thread "main" java.lang.NullPointerException
    at scala.io.Source$.fromURL(Source.scala:141)
    at com.algorithm.similarity$.main(similarity.scala:18)
    at com.algorithm.similarity.main(similarity.scala)

怎么了？