Sean Owen resolved SPARK-17629.
    Resolution: Not A Problem

This is probably best as a question on dev@, not a JIRA. You can easily collect 
the DataFrame locally. I suppose this gives you the option.

> Should ml Word2Vec findSynonyms match the mllib implementation?
> ---------------------------------------------------------------
>                 Key: SPARK-17629
>                 URL: https://issues.apache.org/jira/browse/SPARK-17629
>             Project: Spark
>          Issue Type: Question
>            Reporter: Asher Krim
>            Priority: Minor
> ml Word2Vec's findSynonyms methods depart from mllib in that they return 
> distributed results, rather than the results directly:
> {code}
>   def findSynonyms(word: String, num: Int): DataFrame = {
>     val spark = SparkSession.builder().getOrCreate()
>     spark.createDataFrame(wordVectors.findSynonyms(word, num)).toDF("word", 
> "similarity")
>   }
> {code}
> What was the reason for this decision? I would think that most users would 
> request a reasonably small number of results back, and want to use them 
> directly on the driver, similar to the _take_ method on dataframes. Returning 
> parallelized results creates a costly round trip for the data that doesn't 
> seem necessary.
> The original PR: https://github.com/apache/spark/pull/7263
> [~MechCoder] - do you perhaps recall the reason?

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