[jira] [Reopened] (SPARK-17629) Should ml Word2Vec findSynonyms match the mllib implementation?

["Asher Krim (JIRA)" <ji...@apache.org>]

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

Asher Krim reopened SPARK-17629:
--------------------------------

[~josephkb] gave his blessing for adding local versions of the synonyms methods in the dev mailing list

> 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?



--
This message was sent by Atlassian JIRA
(v6.3.15#6346)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org