[jira] [Resolved] (SPARK-14907) Use repartition in GLMRegressionModel.save

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

     [ https://issues.apache.org/jira/browse/SPARK-14907?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley resolved SPARK-14907.
---------------------------------------
       Resolution: Fixed
    Fix Version/s: 2.0.0

Issue resolved by pull request 12676
[https://github.com/apache/spark/pull/12676]

> Use repartition in GLMRegressionModel.save
> ------------------------------------------
>
>                 Key: SPARK-14907
>                 URL: https://issues.apache.org/jira/browse/SPARK-14907
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>            Reporter: Dongjoon Hyun
>            Assignee: Dongjoon Hyun
>            Priority: Trivial
>             Fix For: 2.0.0
>
>
> This issue changes `GLMRegressionModel.save` function like the following code that is similar to other algorithms' parquet write.
> {code}
> -      val dataRDD: DataFrame = sc.parallelize(Seq(data), 1).toDF()
> -      // TODO: repartition with 1 partition after SPARK-5532 gets fixed
> -      dataRDD.write.parquet(Loader.dataPath(path))
> +      sqlContext.createDataFrame(Seq(data)).repartition(1).write.parquet(Loader.dataPath(path))
> {code}



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