[SPARK-16965][MLLIB][PYSPARK] Fix bound checking for SparseVector.

## What changes were proposed in this pull request?

1. In scala, add negative low bound checking and put all the low/upper bound checking in one place
2. In python, add low/upper bound checking of indices.

## How was this patch tested?

unit test added

Author: Jeff Zhang <zjffdu@apache.org>

Closes #14555 from zjffdu/SPARK-16965.

mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala

@@ -208,17 +208,7 @@ object Vectors {
    */
   @Since("2.0.0")
   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 =>
-      require(prev < i, s"Found duplicate indices: $i.")
-      prev = i
-    }
-    require(prev < size, s"You may not write an element to index $prev because the declared " +
-      s"size of your vector is $size")
-
     new SparseVector(size, indices.toArray, values.toArray)
   }
 
@@ -560,11 +550,25 @@ class SparseVector @Since("2.0.0") (
     @Since("2.0.0") val indices: Array[Int],
     @Since("2.0.0") val values: Array[Double]) extends Vector {
 
-  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.")
-  require(indices.length <= size, s"You provided ${indices.length} indices and values, " +
-    s"which exceeds the specified vector size ${size}.")
+  // validate the data
+  {
+    require(size >= 0, "The size of the requested sparse vector must be greater 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.")
+    require(indices.length <= size, s"You provided ${indices.length} indices and values, " +
+      s"which exceeds the specified vector size ${size}.")
+
+    if (indices.nonEmpty) {
+      require(indices(0) >= 0, s"Found negative index: ${indices(0)}.")
+    }
+    var prev = -1
+    indices.foreach { i =>
+      require(prev < i, s"Index $i follows $prev and is not strictly increasing")
+      prev = i
+    }
+    require(prev < size, s"Index $prev out of bounds for vector of size $size")
+  }
 
   override def toString: String =
     s"($size,${indices.mkString("[", ",", "]")},${values.mkString("[", ",", "]")})"

mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala

@@ -72,6 +72,12 @@ class VectorsSuite extends SparkMLFunSuite {
     }
   }
 
+  test("sparse vector construction with negative indices") {
+    intercept[IllegalArgumentException] {
+      Vectors.sparse(3, Array(-1, 1), Array(3.0, 5.0))
+    }
+  }
+
   test("dense to array") {
     val vec = Vectors.dense(arr).asInstanceOf[DenseVector]
     assert(vec.toArray.eq(arr))

python/pyspark/ml/linalg/__init__.py

@@ -478,6 +478,14 @@ def __init__(self, size, *args):
         SparseVector(4, {1: 1.0, 3: 5.5})
         >>> SparseVector(4, [1, 3], [1.0, 5.5])
         SparseVector(4, {1: 1.0, 3: 5.5})
+        >>> SparseVector(4, {1:1.0, 6:2.0})
+        Traceback (most recent call last):
+        ...
+        AssertionError: Index 6 is out of the the size of vector with size=4
+        >>> SparseVector(4, {-1:1.0})
+        Traceback (most recent call last):
+        ...
+        AssertionError: Contains negative index -1
         """
         self.size = int(size)
         """ Size of the vector. """
@@ -511,6 +519,13 @@ def __init__(self, size, *args):
                         "Indices %s and %s are not strictly increasing"
                         % (self.indices[i], self.indices[i + 1]))
 
+        if self.indices.size > 0:
+            assert np.max(self.indices) < self.size, \
+                "Index %d is out of the the size of vector with size=%d" \
+                % (np.max(self.indices), self.size)
+            assert np.min(self.indices) >= 0, \
+                "Contains negative index %d" % (np.min(self.indices))
+
     def numNonzeros(self):
         """
         Number of nonzero elements. This scans all active values and count non zeros.