You are viewing a plain text version of this content. The canonical link for it is here.

Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2019/05/01 14:41:00 UTC

[jira] [Assigned] (SPARK-27607) Improve performance of Row.toString()

     [ https://issues.apache.org/jira/browse/SPARK-27607?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-27607:
------------------------------------

    Assignee: Apache Spark

> Improve performance of Row.toString()
> -------------------------------------
>
>                 Key: SPARK-27607
>                 URL: https://issues.apache.org/jira/browse/SPARK-27607
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.4.0
>            Reporter: Josh Rosen
>            Assignee: Apache Spark
>            Priority: Minor
>
> I have a job which ends up calling {{org.apache.spark.sql.Row.toString}} on every row in a massive dataset (the reasons for this are slightly odd and it's a bit non-trivial to change the job to avoid this step). 
> {{Row.toString}} is implemented by first constructing a WrappedArray containing the Row's values (by calling {{toSeq}}) and then turning that array into a string with {{mkString}}. We might be able to get a small performance win by pipelining these steps, using an imperative loop to append fields to a StringBuilder as soon as they're retrieved (thereby cutting out a few layers of Scala collections indirection).



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org