[SPARK-7681][MLlib] Add SparseVector support for gemv

mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala

@@ -463,7 +463,7 @@ private[spark] object BLAS extends Serializable with Logging {
   def gemv(
       alpha: Double,
       A: Matrix,
-      x: DenseVector,
+      x: Vector,
       beta: Double,
       y: DenseVector): Unit = {
     require(A.numCols == x.size,
@@ -473,13 +473,16 @@ private[spark] object BLAS extends Serializable with Logging {
     if (alpha == 0.0) {
       logDebug("gemv: alpha is equal to 0. Returning y.")
     } else {
-      A match {
-        case sparse: SparseMatrix =>
-          gemv(alpha, sparse, x, beta, y)
-        case dense: DenseMatrix =>
-          gemv(alpha, dense, x, beta, y)
+      (A, x) match {
+        case (sparse: SparseMatrix, dx: DenseVector) =>
+          gemv(alpha, sparse, dx, beta, y)
+        case (dense: DenseMatrix, dx: DenseVector) =>
+          gemv(alpha, dense, dx, beta, y)
+        case (dense: DenseMatrix, sx: SparseVector) =>
+          gemv(alpha, dense, sx, beta, y)
         case _ =>
-          throw new IllegalArgumentException(s"gemv doesn't support matrix type ${A.getClass}.")
+          throw new IllegalArgumentException(s"gemv doesn't support running on matrix type " +
+            s"${A.getClass} and vector type ${x.getClass}.")
       }
     }
   }
@@ -500,6 +503,55 @@ private[spark] object BLAS extends Serializable with Logging {
     nativeBLAS.dgemv(tStrA, mA, nA, alpha, A.values, mA, x.values, 1, beta,
       y.values, 1)
   }
+
+  /**
+   * y := alpha * A * x + beta * y
+   * For `DenseMatrix` A and SparseVector x.
+   */
+  private def gemv(
+      alpha: Double,
+      A: DenseMatrix,
+      x: SparseVector,
+      beta: Double,
+      y: DenseVector): Unit =  {
+    val mA: Int = A.numRows
+    val nA: Int = A.numCols
+
+    val Avals = A.values
+    var colCounterForA = 0
+
+    var xIndices = x.indices
+    var xNnz = xIndices.size
+    var xValues = x.values
+
+    scal(beta, y)
+
+    if (!A.isTransposed) {
+      var rowCounterForA = 0
+      while (rowCounterForA < mA) {
+        var sum = 0.0
+        var k = 0
+        while (k < xNnz) {
+          sum += xValues(k) * Avals(xIndices(k) * mA + rowCounterForA)
+          k += 1
+        }
+        y.values(rowCounterForA) += sum * alpha
+        rowCounterForA += 1
+      }
+    } else {
+      var rowCounterForA = 0
+      while (rowCounterForA < mA) {
+        var sum = 0.0
+        var k = 0
+        while (k < xNnz) {
+          sum += xValues(k) * Avals(xIndices(k) + rowCounterForA * nA)
+          k += 1
+        }
+        y.values(rowCounterForA) += sum * alpha
+        rowCounterForA += 1
+      }
+    }
+  }
 
   /**
    * y := alpha * A * x + beta * y

mllib/src/test/scala/org/apache/spark/mllib/linalg/BLASSuite.scala

@@ -257,11 +257,12 @@ class BLASSuite extends FunSuite {
       new DenseMatrix(4, 3, Array(0.0, 1.0, 0.0, 0.0, 2.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 3.0))
     val sA = new SparseMatrix(4, 3, Array(0, 1, 3, 4), Array(1, 0, 2, 3), Array(1.0, 2.0, 1.0, 3.0))
 
-    val x = new DenseVector(Array(1.0, 2.0, 3.0))
+    val dx = new DenseVector(Array(1.0, 2.0, 3.0))
+    val sx = dx.toSparse
     val expected = new DenseVector(Array(4.0, 1.0, 2.0, 9.0))
 
-    assert(dA.multiply(x) ~== expected absTol 1e-15)
-    assert(sA.multiply(x) ~== expected absTol 1e-15)
+    assert(dA.multiply(dx) ~== expected absTol 1e-15)
+    assert(sA.multiply(dx) ~== expected absTol 1e-15)
 
     val y1 = new DenseVector(Array(1.0, 3.0, 1.0, 0.0))
     val y2 = y1.copy
@@ -270,17 +271,26 @@ class BLASSuite extends FunSuite {
     val expected2 = new DenseVector(Array(6.0, 7.0, 4.0, 9.0))
     val expected3 = new DenseVector(Array(10.0, 8.0, 6.0, 18.0))
 
-    gemv(1.0, dA, x, 2.0, y1)
-    gemv(1.0, sA, x, 2.0, y2)
-    gemv(2.0, dA, x, 2.0, y3)
-    gemv(2.0, sA, x, 2.0, y4)
+    gemv(1.0, dA, dx, 2.0, y1)
+    gemv(1.0, sA, dx, 2.0, y2)
+    gemv(2.0, dA, dx, 2.0, y3)
+    gemv(2.0, sA, dx, 2.0, y4)
     assert(y1 ~== expected2 absTol 1e-15)
     assert(y2 ~== expected2 absTol 1e-15)
     assert(y3 ~== expected3 absTol 1e-15)
     assert(y4 ~== expected3 absTol 1e-15)
+
+    val y1_copy = new DenseVector(Array(1.0, 3.0, 1.0, 0.0))
+    val y3_copy = y1_copy.copy
+
+    gemv(1.0, dA, sx, 2.0, y1_copy)
+    gemv(2.0, dA, sx, 2.0, y3_copy)
+    assert(y1_copy ~== expected2 absTol 1e-15)
+    assert(y3_copy ~== expected3 absTol 1e-15)
+
     withClue("columns of A don't match the rows of B") {
       intercept[Exception] {
-        gemv(1.0, dA.transpose, x, 2.0, y1)
+        gemv(1.0, dA.transpose, dx, 2.0, y1)
       }
     }
     val dAT =
@@ -291,7 +301,7 @@ class BLASSuite extends FunSuite {
     val dATT = dAT.transpose
     val sATT = sAT.transpose
 
-    assert(dATT.multiply(x) ~== expected absTol 1e-15)
-    assert(sATT.multiply(x) ~== expected absTol 1e-15)
+    assert(dATT.multiply(dx) ~== expected absTol 1e-15)
+    assert(sATT.multiply(dx) ~== expected absTol 1e-15)
   }
 }