[SPARK-16372][MLLIB] Retag RDD to tallSkinnyQR of RowMatrix

## What changes were proposed in this pull request?

The following Java code because of type erasing:

```Java
JavaRDD<Vector> rows = jsc.parallelize(...);
RowMatrix mat = new RowMatrix(rows.rdd());
QRDecomposition<RowMatrix, Matrix> result = mat.tallSkinnyQR(true);
```

We should use retag to restore the type to prevent the following exception:

```Java
java.lang.ClassCastException: [Ljava.lang.Object; cannot be cast to [Lorg.apache.spark.mllib.linalg.Vector;
```

## How was this patch tested?

Java unit test

Author: Xusen Yin <[email protected]>

Closes #14051 from yinxusen/SPARK-16372.

(cherry picked from commit 4c6f00d)
Signed-off-by: Sean Owen <[email protected]>

Author: yinxusen

mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala

@@ -1127,7 +1127,7 @@ private[python] class PythonMLLibAPI extends Serializable {
    * Wrapper around RowMatrix constructor.
    */
   def createRowMatrix(rows: JavaRDD[Vector], numRows: Long, numCols: Int): RowMatrix = {
-    new RowMatrix(rows.rdd.retag(classOf[Vector]), numRows, numCols)
+    new RowMatrix(rows.rdd, numRows, numCols)
   }
 
   /**

mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala

@@ -537,7 +537,7 @@ class RowMatrix @Since("1.0.0") (
   def tallSkinnyQR(computeQ: Boolean = false): QRDecomposition[RowMatrix, Matrix] = {
     val col = numCols().toInt
     // split rows horizontally into smaller matrices, and compute QR for each of them
-    val blockQRs = rows.glom().map { partRows =>
+    val blockQRs = rows.retag(classOf[Vector]).glom().map { partRows =>
       val bdm = BDM.zeros[Double](partRows.length, col)
       var i = 0
       partRows.foreach { row =>

mllib/src/test/java/org/apache/spark/mllib/linalg/distributed/JavaRowMatrixSuite.java

@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.mllib.linalg.distributed;
+
+import java.util.Arrays;
+
+import org.junit.Test;
+
+import org.apache.spark.SharedSparkSession;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.mllib.linalg.Matrix;
+import org.apache.spark.mllib.linalg.QRDecomposition;
+import org.apache.spark.mllib.linalg.Vector;
+import org.apache.spark.mllib.linalg.Vectors;
+
+public class JavaRowMatrixSuite extends SharedSparkSession {
+
+  @Test
+  public void rowMatrixQRDecomposition() {
+    Vector v1 = Vectors.dense(1.0, 10.0, 100.0);
+    Vector v2 = Vectors.dense(2.0, 20.0, 200.0);
+    Vector v3 = Vectors.dense(3.0, 30.0, 300.0);
+
+    JavaRDD<Vector> rows = jsc.parallelize(Arrays.asList(v1, v2, v3), 1);
+    RowMatrix mat = new RowMatrix(rows.rdd());
+
+    QRDecomposition<RowMatrix, Matrix> result = mat.tallSkinnyQR(true);
+  }
+}