Fix double caching in KMeans/BiKMeans

@Since("0.8.0")
def run(data: RDD[Vector]): KMeansModel = {
  val instances = data.map(point => (point, 1.0))
  runWithWeight(instances, None)
}
 

private[spark] def runWithWeight(
    data: RDD[(Vector, Double)],
    instr: Option[Instrumentation]): KMeansModel = {

  // Compute squared norms and cache them.
  val norms = data.map { case (v, _) =>
    Vectors.norm(v, 2.0)
  }

  val zippedData = data.zip(norms).map { case ((v, w), norm) =>
    new VectorWithNorm(v, norm, w)
  }

  if (data.getStorageLevel == StorageLevel.NONE) {
    zippedData.persist(StorageLevel.MEMORY_AND_DISK)
  }
  val model = runAlgorithmWithWeight(zippedData, instr)
  zippedData.unpersist()

  model
}