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 2020/05/11 23:22:00 UTC
[jira] [Commented] (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:comment-tabpanel&focusedCommentId=17104967#comment-17104967 ]
Apache Spark commented on SPARK-20007:
--------------------------------------
User 'liangz1' has created a pull request for this issue:
https://github.com/apache/spark/pull/28504
> 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