use weighted sum in combOp

Author: Liquan Pei

mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala

@@ -87,7 +87,7 @@ class Word2Vec(
   private var vocabHash = mutable.HashMap.empty[String, Int]
   private var alpha = startingAlpha
 
-  private def learnVocab(words:RDD[String]) {
+  private def learnVocab(words:RDD[String]){
     vocab = words.map(w => (w, 1))
       .reduceByKey(_ + _)
       .map(x => VocabWord(
@@ -110,6 +110,10 @@ class Word2Vec(
     logInfo("trainWordsCount = " + trainWordsCount)
   }
 
+  private def learnVocabPerPartition(words:RDD[String]) {
+    
+  }
+  
   private def createExpTable(): Array[Double] = {
     val expTable = new Array[Double](EXP_TABLE_SIZE)
     var i = 0
@@ -303,8 +307,12 @@ class Word2Vec(
           combOp = (c1, c2) => (c1, c2) match { 
             case ((syn0_1, syn1_1, lwc_1, wc_1), (syn0_2, syn1_2, lwc_2, wc_2)) =>
               val n = syn0_1.length
-              blas.daxpy(n, 1.0, syn0_2, 1, syn0_1, 1)
-              blas.daxpy(n, 1.0, syn1_2, 1, syn1_1, 1)
+              val weight1 = 1.0 * wc_1 / (wc_1 + wc_2)
+              val weight2 = 1.0 * wc_2 / (wc_1 + wc_2)
+              blas.dscal(n, weight1, syn0_1, 1)
+              blas.dscal(n, weight1, syn1_1, 1)
+              blas.daxpy(n, weight2, syn0_2, 1, syn0_1, 1)
+              blas.daxpy(n, weight2, syn1_2, 1, syn1_1, 1)
               (syn0_1, syn1_1, lwc_1 + lwc_2, wc_1 + wc_2)
           })
       syn0Global = aggSyn0