[SPARK-8563] [MLLIB] Fixed a bug so that IndexedRowMatrix.computeSVD().U.numCols = k

I'm sorry that I made #6949 closed by mistake.
I pushed codes again.

And, I added a test code.

>
There is a bug that `U.numCols() = self.nCols` in `IndexedRowMatrix.computeSVD()`
It should have been `U.numCols() = k = svd.U.numCols()`

>
```
self = U * sigma * V.transpose
(m x n) = (m x n) * (k x k) * (k x n) //ASIS
-->
(m x n) = (m x k) * (k x k) * (k x n) //TOBE
```

Author: lee19 <[email protected]>

Closes #6953 from lee19/MLlibBugfix and squashes the following commits:

c1812a0 [lee19] [SPARK-8563] [MLlib] Used nRows instead of numRows() to reduce a burden.
4b9803b [lee19] [SPARK-8563] [MLlib] Fixed a build error.
c2ccd89 [lee19] Added a unit test that validates matrix sizes of svd for [SPARK-8563][MLlib]
8373424 [lee19] [SPARK-8563][MLlib] Fixed a bug so that IndexedRowMatrix.computeSVD().U.numCols = k

(cherry picked from commit e725262)
Signed-off-by: Xiangrui Meng <[email protected]>

Author: lee19

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

@@ -108,7 +108,7 @@ class IndexedRowMatrix(
       val indexedRows = indices.zip(svd.U.rows).map { case (i, v) =>
         IndexedRow(i, v)
       }
-      new IndexedRowMatrix(indexedRows, nRows, nCols)
+      new IndexedRowMatrix(indexedRows, nRows, svd.U.numCols().toInt)
     } else {
       null
     }

mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrixSuite.scala

@@ -113,6 +113,17 @@ class IndexedRowMatrixSuite extends FunSuite with MLlibTestSparkContext {
     assert(closeToZero(U * brzDiag(s) * V.t - localA))
   }
 
+  test("validate matrix sizes of svd") {
+    val k = 2
+    val A = new IndexedRowMatrix(indexedRows)
+    val svd = A.computeSVD(k, computeU = true)
+    assert(svd.U.numRows() === m)
+    assert(svd.U.numCols() === k)
+    assert(svd.s.size === k)
+    assert(svd.V.numRows === n)
+    assert(svd.V.numCols === k)
+  }
+
   def closeToZero(G: BDM[Double]): Boolean = {
     G.valuesIterator.map(math.abs).sum < 1e-6
   }