[SPARK-14850][.2][ML] use UnsafeArrayData.fromPrimitiveArray in ml.VectorUDT/MatrixUDT

## What changes were proposed in this pull request?

This PR uses `UnsafeArrayData.fromPrimitiveArray` to implement `ml.VectorUDT/MatrixUDT` to avoid boxing/unboxing.

## How was this patch tested?

Exiting unit tests.

cc: cloud-fan

Author: Xiangrui Meng <meng@databricks.com>

Closes #12805 from mengxr/SPARK-14850.

2 files changed, 9 insertions, 11 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/ml/linalg/MatrixUDT.scala b/mllib/src/main/scala/org/apache/spark/ml/linalg/MatrixUDT.scala
index 53f4d55971..521a216c67 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/linalg/MatrixUDT.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/linalg/MatrixUDT.scala
@@ -18,8 +18,7 @@
 package org.apache.spark.ml.linalg
 
 import org.apache.spark.sql.catalyst.InternalRow
-import org.apache.spark.sql.catalyst.expressions.GenericMutableRow
-import org.apache.spark.sql.catalyst.util.GenericArrayData
+import org.apache.spark.sql.catalyst.expressions.{GenericMutableRow, UnsafeArrayData}
 import org.apache.spark.sql.types._
 
 /**
@@ -53,9 +52,9 @@ private[ml] class MatrixUDT extends UserDefinedType[Matrix] {
         row.setByte(0, 0)
         row.setInt(1, sm.numRows)
         row.setInt(2, sm.numCols)
-        row.update(3, new GenericArrayData(sm.colPtrs.map(_.asInstanceOf[Any])))
-        row.update(4, new GenericArrayData(sm.rowIndices.map(_.asInstanceOf[Any])))
-        row.update(5, new GenericArrayData(sm.values.map(_.asInstanceOf[Any])))
+        row.update(3, UnsafeArrayData.fromPrimitiveArray(sm.colPtrs))
+        row.update(4, UnsafeArrayData.fromPrimitiveArray(sm.rowIndices))
+        row.update(5, UnsafeArrayData.fromPrimitiveArray(sm.values))
         row.setBoolean(6, sm.isTransposed)
 
       case dm: DenseMatrix =>
@@ -64,7 +63,7 @@ private[ml] class MatrixUDT extends UserDefinedType[Matrix] {
         row.setInt(2, dm.numCols)
         row.setNullAt(3)
         row.setNullAt(4)
-        row.update(5, new GenericArrayData(dm.values.map(_.asInstanceOf[Any])))
+        row.update(5, UnsafeArrayData.fromPrimitiveArray(dm.values))
         row.setBoolean(6, dm.isTransposed)
     }
     row
diff --git a/mllib/src/main/scala/org/apache/spark/ml/linalg/VectorUDT.scala b/mllib/src/main/scala/org/apache/spark/ml/linalg/VectorUDT.scala
index fe93a12d06..c29f7f86e9 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/linalg/VectorUDT.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/linalg/VectorUDT.scala
@@ -18,8 +18,7 @@
 package org.apache.spark.ml.linalg
 
 import org.apache.spark.sql.catalyst.InternalRow
-import org.apache.spark.sql.catalyst.expressions.GenericMutableRow
-import org.apache.spark.sql.catalyst.util.GenericArrayData
+import org.apache.spark.sql.catalyst.expressions.{GenericMutableRow, UnsafeArrayData}
 import org.apache.spark.sql.types._
 
 /**
@@ -46,15 +45,15 @@ private[ml] class VectorUDT extends UserDefinedType[Vector] {
         val row = new GenericMutableRow(4)
         row.setByte(0, 0)
         row.setInt(1, size)
-        row.update(2, new GenericArrayData(indices.map(_.asInstanceOf[Any])))
-        row.update(3, new GenericArrayData(values.map(_.asInstanceOf[Any])))
+        row.update(2, UnsafeArrayData.fromPrimitiveArray(indices))
+        row.update(3, UnsafeArrayData.fromPrimitiveArray(values))
         row
       case DenseVector(values) =>
         val row = new GenericMutableRow(4)
         row.setByte(0, 1)
         row.setNullAt(1)
         row.setNullAt(2)
-        row.update(3, new GenericArrayData(values.map(_.asInstanceOf[Any])))
+        row.update(3, UnsafeArrayData.fromPrimitiveArray(values))
         row
     }
   }