[SPARK-14734][ML][MLLIB] Added asML, fromML methods for all spark.mllib Vector, Matrix types

## What changes were proposed in this pull request?

For maintaining wrappers around spark.mllib algorithms in spark.ml, it will be useful to have ```private[spark]``` methods for converting from one linear algebra representation to another.
This PR adds toNew, fromNew methods for all spark.mllib Vector and Matrix types.

## How was this patch tested?

Unit tests for all conversions

Author: Joseph K. Bradley <joseph@databricks.com>

Closes #12504 from jkbradley/linalg-conversions.

2 files changed, 68 insertions, 1 deletions

diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
index e289724cda..b7df02e6c0 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
@@ -19,12 +19,14 @@ package org.apache.spark.mllib.linalg
 
 import java.util.Random
 
+import scala.collection.mutable.{Map => MutableMap}
+
 import breeze.linalg.{CSCMatrix, Matrix => BM}
 import org.mockito.Mockito.when
 import org.scalatest.mock.MockitoSugar._
-import scala.collection.mutable.{Map => MutableMap}
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.{linalg => newlinalg}
 import org.apache.spark.mllib.util.TestingUtils._
 
 class MatricesSuite extends SparkFunSuite {
@@ -523,4 +525,39 @@ class MatricesSuite extends SparkFunSuite {
       assert(m.transpose.colIter.toSeq === rows)
     }
   }
+
+  test("conversions between new local linalg and mllib linalg") {
+    val dm: DenseMatrix = new DenseMatrix(3, 2, Array(0.0, 0.0, 1.0, 0.0, 2.0, 3.5))
+    val sm: SparseMatrix = dm.toSparse
+    val sm0: Matrix = sm.asInstanceOf[Matrix]
+    val dm0: Matrix = dm.asInstanceOf[Matrix]
+
+    def compare(oldM: Matrix, newM: newlinalg.Matrix): Unit = {
+      assert(oldM.toArray === newM.toArray)
+      assert(oldM.numCols === newM.numCols)
+      assert(oldM.numRows === newM.numRows)
+    }
+
+    val newSM: newlinalg.SparseMatrix = sm.asML
+    val newDM: newlinalg.DenseMatrix = dm.asML
+    val newSM0: newlinalg.Matrix = sm0.asML
+    val newDM0: newlinalg.Matrix = dm0.asML
+    assert(newSM0.isInstanceOf[newlinalg.SparseMatrix])
+    assert(newDM0.isInstanceOf[newlinalg.DenseMatrix])
+    compare(sm, newSM)
+    compare(dm, newDM)
+    compare(sm0, newSM0)
+    compare(dm0, newDM0)
+
+    val oldSM: SparseMatrix = SparseMatrix.fromML(newSM)
+    val oldDM: DenseMatrix = DenseMatrix.fromML(newDM)
+    val oldSM0: Matrix = Matrices.fromML(newSM0)
+    val oldDM0: Matrix = Matrices.fromML(newDM0)
+    assert(oldSM0.isInstanceOf[SparseMatrix])
+    assert(oldDM0.isInstanceOf[DenseMatrix])
+    compare(oldSM, newSM)
+    compare(oldDM, newDM)
+    compare(oldSM0, newSM0)
+    compare(oldDM0, newDM0)
+  }
 }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala
index e5567492a2..a7c1a07604 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala
@@ -24,6 +24,7 @@ import org.json4s.jackson.JsonMethods.{parse => parseJson}
 
 import org.apache.spark.{SparkException, SparkFunSuite}
 import org.apache.spark.internal.Logging
+import org.apache.spark.ml.{linalg => newlinalg}
 import org.apache.spark.mllib.util.TestingUtils._
 
 class VectorsSuite extends SparkFunSuite with Logging {
@@ -392,4 +393,33 @@ class VectorsSuite extends SparkFunSuite with Logging {
       assert(u === v, "toJson/fromJson should preserve vector values.")
     }
   }
+
+  test("conversions between new local linalg and mllib linalg") {
+    val dv: DenseVector = new DenseVector(Array(1.0, 2.0, 3.5))
+    val sv: SparseVector = new SparseVector(5, Array(1, 2, 4), Array(1.1, 2.2, 4.4))
+    val sv0: Vector = sv.asInstanceOf[Vector]
+    val dv0: Vector = dv.asInstanceOf[Vector]
+
+    val newSV: newlinalg.SparseVector = sv.asML
+    val newDV: newlinalg.DenseVector = dv.asML
+    val newSV0: newlinalg.Vector = sv0.asML
+    val newDV0: newlinalg.Vector = dv0.asML
+    assert(newSV0.isInstanceOf[newlinalg.SparseVector])
+    assert(newDV0.isInstanceOf[newlinalg.DenseVector])
+    assert(sv.toArray === newSV.toArray)
+    assert(dv.toArray === newDV.toArray)
+    assert(sv0.toArray === newSV0.toArray)
+    assert(dv0.toArray === newDV0.toArray)
+
+    val oldSV: SparseVector = SparseVector.fromML(newSV)
+    val oldDV: DenseVector = DenseVector.fromML(newDV)
+    val oldSV0: Vector = Vectors.fromML(newSV0)
+    val oldDV0: Vector = Vectors.fromML(newDV0)
+    assert(oldSV0.isInstanceOf[SparseVector])
+    assert(oldDV0.isInstanceOf[DenseVector])
+    assert(oldSV.toArray === newSV.toArray)
+    assert(oldDV.toArray === newDV.toArray)
+    assert(oldSV0.toArray === newSV0.toArray)
+    assert(oldDV0.toArray === newDV0.toArray)
+  }
 }