You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2019/10/08 05:45:10 UTC
[jira] [Resolved] (SPARK-20007) Make SparkR apply() functions
robust to workers that return empty data.frame
[ https://issues.apache.org/jira/browse/SPARK-20007?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-20007.
----------------------------------
Resolution: Incomplete
> Make SparkR apply() functions robust to workers that return empty data.frame
> ----------------------------------------------------------------------------
>
> Key: SPARK-20007
> URL: https://issues.apache.org/jira/browse/SPARK-20007
> Project: Spark
> Issue Type: Bug
> Components: SparkR
> Affects Versions: 2.2.0
> Reporter: Hossein Falaki
> Priority: Major
> Labels: bulk-closed
>
> When using {{gapply()}} (or other members of {{apply()}} family) with a schema, Spark will try to parse data returned form the R process on each worker as Spark DataFrame Rows based on the schema. In this case our provided schema suggests that we have six column. When an R worker returns results to JVM, SparkSQL will try to access its columns one by one and cast them to proper types. If R worker returns nothing, JVM will throw {{ArrayIndexOutOfBoundsException}} exception.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org