class DenseVectorV
  extends Vector[V] {
  def this(data: Array[V]) = this(data, 0, 1, data.length)
  …
  }
  class LabeledPoint(var label: Double, var features: Vector[Double])

  val lines = sparkContext.textFile(inputPath)
  val points = lines.map(line => {
  val features = new ArrayDouble
  …
  new LabeledPoint(new DenseVector(features), label)
  }).cache()
  var weights = DenseVector.fill(D){2 rand.nextDouble - 1}
  for (i <- 1="" to="" iterations)="" {="" val="" gradient="points.map{p" =="">
  p.features (1 / (1 + exp(-p.label weights.dot(p.features))) - 1) p.label
  }.reduce(_ + _)
  weights -= gradient
  }