[jira] [Resolved] (SPARK-17629) Add local version of Word2Vec findSynonyms for spark.ml

["Joseph K. Bradley (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-17629?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley resolved SPARK-17629.
---------------------------------------
       Resolution: Fixed
    Fix Version/s: 2.2.0

Issue resolved by pull request 16811
[https://github.com/apache/spark/pull/16811]

> Add local version of Word2Vec findSynonyms for spark.ml
> -------------------------------------------------------
>
>                 Key: SPARK-17629
>                 URL: https://issues.apache.org/jira/browse/SPARK-17629
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>    Affects Versions: 2.2.0
>            Reporter: Asher Krim
>            Assignee: Asher Krim
>            Priority: Minor
>             Fix For: 2.2.0
>
>
> 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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