1 files changed, 4 insertions, 4 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala
index a7beb81980..8ff0b83e8b 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala
@@ -253,16 +253,14 @@ class KMeans private (
     }
 
     val centers = initialModel match {
-      case Some(kMeansCenters) => {
+      case Some(kMeansCenters) =>
         Array(kMeansCenters.clusterCenters.map(s => new VectorWithNorm(s)))
-      }
-      case None => {
+      case None =>
         if (initializationMode == KMeans.RANDOM) {
           initRandom(data)
         } else {
           initKMeansParallel(data)
         }
-      }
     }
     val initTimeInSeconds = (System.nanoTime() - initStartTime) / 1e9
     logInfo(s"Initialization with $initializationMode took " + "%.3f".format(initTimeInSeconds) +
@@ -390,6 +388,8 @@ class KMeans private (
     // Initialize each run's first center to a random point.
     val seed = new XORShiftRandom(this.seed).nextInt()
     val sample = data.takeSample(true, runs, seed).toSeq
+    // Could be empty if data is empty; fail with a better message early:
+    require(sample.size >= runs, s"Required $runs samples but got ${sample.size} from $data")
     val newCenters = Array.tabulate(runs)(r => ArrayBuffer(sample(r).toDense))
 
     /** Merges new centers to centers. */