[jira] [Resolved] (SPARK-16215) Reduce runtime overhead of a program that writes an primitive array in Dataframe/Dataset

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-16215?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved SPARK-16215.
-------------------------------
    Resolution: Duplicate

> Reduce runtime overhead of a program that writes an primitive array in Dataframe/Dataset
> ----------------------------------------------------------------------------------------
>
>                 Key: SPARK-16215
>                 URL: https://issues.apache.org/jira/browse/SPARK-16215
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>            Reporter: Kazuaki Ishizaki
>
> When we run a program that writes an primitive array in Dataframe/Dataset, generated code for projection performs null check and element-based data copy. We can alleviate overhead of these operations by generating better code.
> A target program
> {code}
> val df = sparkContext.parallelize(Seq(0.0d, 1.0d), 1).toDF
> df.selectExpr("Array(value + 1.1d, value + 2.2d)").collect
> {code}



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