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-rw-r--r--mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala6
-rw-r--r--mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala6
2 files changed, 6 insertions, 6 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala
index 88914fa875..1c858348bf 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala
@@ -179,12 +179,12 @@ private[spark] class MatrixUDT extends UserDefinedType[Matrix] {
val tpe = row.getByte(0)
val numRows = row.getInt(1)
val numCols = row.getInt(2)
- val values = row.getArray(5).toArray.map(_.asInstanceOf[Double])
+ val values = row.getArray(5).toDoubleArray()
val isTransposed = row.getBoolean(6)
tpe match {
case 0 =>
- val colPtrs = row.getArray(3).toArray.map(_.asInstanceOf[Int])
- val rowIndices = row.getArray(4).toArray.map(_.asInstanceOf[Int])
+ val colPtrs = row.getArray(3).toIntArray()
+ val rowIndices = row.getArray(4).toIntArray()
new SparseMatrix(numRows, numCols, colPtrs, rowIndices, values, isTransposed)
case 1 =>
new DenseMatrix(numRows, numCols, values, isTransposed)
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
index 89a1818db0..96d1f48ba2 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
@@ -209,11 +209,11 @@ private[spark] class VectorUDT extends UserDefinedType[Vector] {
tpe match {
case 0 =>
val size = row.getInt(1)
- val indices = row.getArray(2).toArray().map(_.asInstanceOf[Int])
- val values = row.getArray(3).toArray().map(_.asInstanceOf[Double])
+ val indices = row.getArray(2).toIntArray()
+ val values = row.getArray(3).toDoubleArray()
new SparseVector(size, indices, values)
case 1 =>
- val values = row.getArray(3).toArray().map(_.asInstanceOf[Double])
+ val values = row.getArray(3).toDoubleArray()
new DenseVector(values)
}
}