Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/7263#discussion_r34094649
--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/Word2Vec.scala
---
@@ -146,6 +151,55 @@ class Word2VecModel private[ml] (
wordVectors: feature.Word2VecModel)
extends Model[Word2VecModel] with Word2VecBase {
+
+ /**
+ * Return a map of every word to its Vector representation.
+ */
+ val getVectors: Map[String, Array[Float]] = wordVectors.getVectors
--- End diff --
So its my understanding, from my reading of the code, it isn't possible to
access the Spark context here. If we look at similar methods in other models
(like predict in classifier), they can't access the Spark Context, its only
when we are applying fit/transform and we have a dataframe passed into us that
we can access the SparkContext.
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