Make random seed an argument

mllib/src/main/scala/org/apache/spark/mllib/clustering/StreamingKMeans.scala

@@ -183,10 +183,19 @@ class StreamingKMeans(
     this
   }
 
-  /** Initialize random centers, requiring only the number of dimensions. */
-  def setRandomCenters(d: Int): this.type = {
-    val initialCenters = (0 until k).map(_ => Vectors.dense(Array.fill(d)(nextGaussian()))).toArray
-    val clusterCounts = Array.fill(this.k)(0).map(_.toLong)
+  /** Initialize random centers, requiring only the number of dimensions.
+    *
+    * @param dim Number of dimensions
+    * @param seed Random seed
+    * */
+  def setRandomCenters(dim: Int, seed: Long = Utils.random.nextLong): this.type = {
+
+    val random = Utils.random
+    random.setSeed(seed)
+
+    val initialCenters = (0 until k)
+      .map(_ => Vectors.dense(Array.fill(dim)(random.nextGaussian()))).toArray
+    val clusterCounts = new Array[Long](this.k)
     this.model = new StreamingKMeansModel(initialCenters, clusterCounts)
     this
   }