[
https://issues.apache.org/jira/browse/SPARK-17629?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Joseph K. Bradley reassigned SPARK-17629:
-----------------------------------------
Shepherd: Joseph K. Bradley
Assignee: Asher Krim
Affects Version/s: 2.2.0
Target Version/s: 2.2.0
Component/s: ML
Issue Type: New Feature (was: Question)
Summary: Add local version of Word2Vec findSynonyms for spark.ml
(was: Should ml Word2Vec findSynonyms match the mllib implementation?)
> 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
>
> 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-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
