[SPARK-23085][ML] API parity for mllib.linalg.Vectors.sparse

## What changes were proposed in this pull request? `ML.Vectors#sparse(size: Int, elements: Seq[(Int, Double)])` support zero-length ## How was this patch tested? existing tests Author: Zheng RuiFeng <[email protected]> Closes apache#20275 from zhengruifeng/SparseVector_size.
hejiefang · Jan 19, 2018 · 606a748 · 606a748
1 parent 6c39654
commit 606a748
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diff --git a/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala b/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala
@@ -565,7 +565,7 @@ class SparseVector @Since("2.0.0") (
 
   // validate the data
   {
-    require(size >= 0, "The size of the requested sparse vector must be greater than 0.")
+    require(size >= 0, "The size of the requested sparse vector must be no less than 0.")
     require(indices.length == values.length, "Sparse vectors require that the dimension of the" +
       s" indices match the dimension of the values. You provided ${indices.length} indices and " +
       s" ${values.length} values.")

diff --git a/mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala b/mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala
@@ -366,4 +366,18 @@ class VectorsSuite extends SparkMLFunSuite {
     assert(v.slice(Array(2, 0)) === new SparseVector(2, Array(0), Array(2.2)))
     assert(v.slice(Array(2, 0, 3, 4)) === new SparseVector(4, Array(0, 3), Array(2.2, 4.4)))
   }
+
+  test("sparse vector only support non-negative length") {
+    val v1 = Vectors.sparse(0, Array.emptyIntArray, Array.emptyDoubleArray)
+    val v2 = Vectors.sparse(0, Array.empty[(Int, Double)])
+    assert(v1.size === 0)
+    assert(v2.size === 0)
+
+    intercept[IllegalArgumentException] {
+      Vectors.sparse(-1, Array(1), Array(2.0))
+    }
+    intercept[IllegalArgumentException] {
+      Vectors.sparse(-1, Array((1, 2.0)))
+    }
+  }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
@@ -326,8 +326,6 @@ object Vectors {
    */
   @Since("1.0.0")
   def sparse(size: Int, elements: Seq[(Int, Double)]): Vector = {
-    require(size > 0, "The size of the requested sparse vector must be greater than 0.")
-
     val (indices, values) = elements.sortBy(_._1).unzip
     var prev = -1
     indices.foreach { i =>
@@ -758,6 +756,7 @@ class SparseVector @Since("1.0.0") (
     @Since("1.0.0") val indices: Array[Int],
     @Since("1.0.0") val values: Array[Double]) extends Vector {
 
+  require(size >= 0, "The size of the requested sparse vector must be no less than 0.")
   require(indices.length == values.length, "Sparse vectors require that the dimension of the" +
     s" indices match the dimension of the values. You provided ${indices.length} indices and " +
     s" ${values.length} values.")

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
@@ -495,4 +495,18 @@ class VectorsSuite extends SparkFunSuite with Logging {
     assert(mlDenseVectorToArray(dv) === mlDenseVectorToArray(newDV))
     assert(mlSparseVectorToArray(sv) === mlSparseVectorToArray(newSV))
   }
+
+  test("sparse vector only support non-negative length") {
+    val v1 = Vectors.sparse(0, Array.emptyIntArray, Array.emptyDoubleArray)
+    val v2 = Vectors.sparse(0, Array.empty[(Int, Double)])
+    assert(v1.size === 0)
+    assert(v2.size === 0)
+
+    intercept[IllegalArgumentException] {
+      Vectors.sparse(-1, Array(1), Array(2.0))
+    }
+    intercept[IllegalArgumentException] {
+      Vectors.sparse(-1, Array((1, 2.0)))
+    }
+  }
 }