Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/10152#discussion_r47542276
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -281,17 +294,28 @@ 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
=>
--- End diff --
I think we can simply do:
```scala
val sentences: RDD[Array[Int]] = dataset.mapPartitions { iter =>
new Iterator[Array[Int]] {
def hasNext: Boolean = iter.hasNext
def next(): Array[Int] = {
val sentence = ArrayBuilder.make[Int]
var sentenceLength = 0
val wordIter = iter.next().iterator
while (wordIter.hasNext && sentenceLength < MAX_SENTENCE_LENGTH) {
val word = bcVocabHash.value.get(wordIter.next())
word match {
case Some(w) =>
sentence += w
sentenceLength += 1
case None =>
}
}
sentence.result()
}
}
}
```
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