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
index ab57a7bf0aa6a..2c8891cef93ab 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
@@ -736,9 +736,9 @@ class SparseVector(
       }
 
       // look for inactive values in case all active node values are negative
-      if (size != values.size && maxValue <= 0){
+      if (size != values.size && maxValue <= 0) {
         val firstInactiveIdx = calcFirstInactiveIdx(0)
-        if (!(maxValue == 0 && firstInactiveIdx >= maxIdx)){
+        if (!(maxValue == 0 && firstInactiveIdx >= maxIdx)) {
           maxIdx = firstInactiveIdx
         }
         maxValue = 0
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 0eb20d8f3f269..dced71a63a3ac 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
@@ -63,7 +63,7 @@ class VectorsSuite extends FunSuite {
     assert(vec.toArray.eq(arr))
   }
 
-  test("dense argmax"){
+  test("dense argmax") {
     val vec = Vectors.dense(Array.empty[Double]).asInstanceOf[DenseVector]
     assert(vec.argmax === -1)
 
@@ -81,7 +81,7 @@ class VectorsSuite extends FunSuite {
     assert(vec.toArray === arr)
   }
 
-  test("sparse argmax"){
+  test("sparse argmax") {
     val vec = Vectors.sparse(0,Array.empty[Int],Array.empty[Double]).asInstanceOf[SparseVector]
     val noMax = vec.argmax
     assert(noMax === -1)