Github user ygcao commented on a diff in the pull request:
https://github.com/apache/spark/pull/10152#discussion_r52773573
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -289,24 +301,20 @@ 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 =>
- new Iterator[Array[Int]] {
- def hasNext: Boolean = iter.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 {
- case Some(w) =>
- sentence += w
- sentenceLength += 1
- case None =>
- }
+ // each partition is a collection of sentences,
+ // will be translated into arrays of Index integer
+ val sentences: RDD[Array[Int]] = dataset.mapPartitions { sentenceIter
=>
+ // Each sentence will map to 0 or more Array[Int]
+ sentenceIter.flatMap { sentence => {
+ // Sentence of words, some of which map to a word index
+ val wordIndexes = sentence.flatMap(bcVocabHash.value.get)
+ if (wordIndexes.nonEmpty) {
--- End diff --
The ppurpose for if statement is that an empty sentence(after lookup)
should not result in an empty element. Whether we use grouped or not won't
change the fact that it could generate empty element which could be harmful and
wasteful for late steps.
My test proves the if statement is needed for get rid of empty element.
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