[jira] (SPARK-18131) Support returning Vector/Dense Vector from backend

["Miao Wang (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-18131?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15847390#comment-15847390 ] 

Miao Wang commented on SPARK-18131:
-----------------------------------

[~felixcheung][~yanboliang][~shivaram] I am trying to add the serialization utility to SerDe.scala. 

Inside def writeObject(dos: DataOutputStream, obj: Object, jvmObjectTracker: JVMObjectTracker): Unit, one case should be added:

case v: org.apache.spark.ml.linalg.DenseVector => 

This file is in spark-core. So I can't import org.apache.spark.ml.linalg._ in this file, because of dependency issue. Do you have any suggestions?

One possibility is to move `Vectors` from mllib-local to core folder. I am not sure whether there are other options.

Thanks! 

> 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`.



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