Github user MLnick commented on a diff in the pull request: https://github.com/apache/spark/pull/10152#discussion_r47767717 --- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala --- @@ -281,17 +295,28 @@ class Word2Vec extends Serializable with Logging { val expTable = sc.broadcast(createExpTable()) val bcVocab = sc.broadcast(vocab) val bcVocabHash = sc.broadcast(vocabHash) - - val sentences: RDD[Array[Int]] = words.mapPartitions { iter => + // each partition is a collection of sentences, will be translated into arrays of Index integer + val sentences: RDD[Array[Int]] = dataset.mapPartitions { sentenceIter => new Iterator[Array[Int]] { - def hasNext: Boolean = iter.hasNext + var wordIter: Iterator[String] = null + + def hasNext: Boolean = sentenceIter.hasNext || (wordIter != null && wordIter.hasNext) def next(): Array[Int] = { val sentence = ArrayBuilder.make[Int] var sentenceLength = 0 - while (iter.hasNext && sentenceLength < MAX_SENTENCE_LENGTH) { - val word = bcVocabHash.value.get(iter.next()) - word match { + // do translation of each word into its index in the vocabulary, + // do cutting only when the sentence is larger than maxSentenceLength + if ((wordIter == null || !wordIter.hasNext) && sentenceIter.hasNext) { + do { --- End diff -- is the `do ... while` block strictly necessary? Have you not already checked the preconditions for the while block in the if statement?
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