Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/10152#discussion_r46806131
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -281,16 +280,17 @@ 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 { 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())
+ //do translation of each word into its index in the vocabulary,
not constraint by fixed length anymore
+ for (wd <- iter.next()) {
--- End diff --
If making the `maxSentenceLength` a configurable parameter, this doesn't
need to change - and the `while` loop is preferable
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