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Date: Sun, 26 Jun 2016 05:57:33 +0000 (UTC)
From: "Apache Spark (JIRA)" <jira@apache.org>
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Message-ID: <JIRA.12983230.1466920359000.25.1466920653389@Atlassian.JIRA>
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Subject: [jira] [Assigned] (SPARK-16215) Reduce runtime overhead of a
 program that writes an primitive array in Dataframe/Dataset
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archived-at: Sun, 26 Jun 2016 05:57:35 -0000


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

Apache Spark reassigned SPARK-16215:
------------------------------------

    Assignee:     (was: Apache Spark)

> 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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