[
https://issues.apache.org/jira/browse/SPARK-18131?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15651711#comment-15651711
]
Shivaram Venkataraman commented on SPARK-18131:
-----------------------------------------------
Yeah this could work. The main thing is to keep the representations lightweight
so that we don't implement various operations like addition / multiplication on
them.
> Support returning Vector/Dense Vector from backend
> --------------------------------------------------
>
> Key: SPARK-18131
> URL: https://issues.apache.org/jira/browse/SPARK-18131
> Project: Spark
> Issue Type: New Feature
> Components: SparkR
> Reporter: Miao Wang
>
> For `spark.logit`, there is a `probabilityCol`, which is a vector in the
> backend (scala side). When we do collect(select(df, "probabilityCol")),
> backend returns the java object handle (memory address). We need to implement
> a method to convert a Vector/Dense Vector column as R vector, which can be
> read in SparkR. It is a followup JIRA of adding `spark.logit`.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
