use extractor for vectors in Vectors.scala

Author: coderxiang

mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala

@@ -108,16 +108,16 @@ private[spark] class VectorUDT extends UserDefinedType[Vector] {
   override def serialize(obj: Any): Row = {
     val row = new GenericMutableRow(4)
     obj match {
-      case sv: SparseVector =>
+      case SparseVector(size, indices, values) =>
         row.setByte(0, 0)
-        row.setInt(1, sv.size)
-        row.update(2, sv.indices.toSeq)
-        row.update(3, sv.values.toSeq)
-      case dv: DenseVector =>
+        row.setInt(1, size)
+        row.update(2, indices.toSeq)
+        row.update(3, values.toSeq)
+      case DenseVector(values) =>
         row.setByte(0, 1)
         row.setNullAt(1)
         row.setNullAt(2)
-        row.update(3, dv.values.toSeq)
+        row.update(3, values.toSeq)
     }
     row
   }
@@ -271,8 +271,8 @@ object Vectors {
   def norm(vector: Vector, p: Double): Double = {
     require(p >= 1.0)
     val values = vector match {
-      case dv: DenseVector => dv.values
-      case sv: SparseVector => sv.values
+      case DenseVector(vs) => vs
+      case SparseVector(n, ids, vs) => vs
       case v => throw new IllegalArgumentException("Do not support vector type " + v.getClass)
     }
     val size = values.size