diff --git a/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala b/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
index f4228fe5e7522..924ab43f26e06 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
@@ -20,8 +20,10 @@ package org.apache.spark.mllib.classification
 import scala.collection.mutable
 
 import org.jblas.DoubleMatrix
+import breeze.linalg.{Vector => BV}
 
 import org.apache.spark.{SparkContext, Logging}
+import org.apache.spark.SparkContext._
 import org.apache.spark.mllib.regression.LabeledPoint
 import org.apache.spark.rdd.RDD
 import org.apache.spark.mllib.util.MLUtils
@@ -76,7 +78,13 @@ class NaiveBayes private (var lambda: Double)
    * @param data RDD of [[org.apache.spark.mllib.regression.LabeledPoint]].
    */
   def run(data: RDD[LabeledPoint]) = {
-    runRaw(data.map(v => (v.label, v.features.toArray)))
+    val agg = data.map(p => (p.label, p.features)).combineByKey[(Long, BV[Double])](
+      createCombiner = (v: Vector) => (1L, v.toBreeze.toDenseVector),
+      mergeValue = (c: (Long, BV[Double]), v: Vector) => (c._1 + 1L, c._2 += v.toBreeze),
+      mergeCombiners = (c1: (Long, BV[Double]), c2: (Long, BV[Double])) =>
+        (c1._1 + c2._1, c1._2 += c2._2)
+    ).collect()
+    val numLabels = agg.size
   }
 
   /**