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Posted to issues@spark.apache.org by "Sameer Agarwal (JIRA)" <ji...@apache.org> on 2018/01/08 20:15:00 UTC
[jira] [Updated] (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 ]
Sameer Agarwal updated SPARK-20007:
-----------------------------------
Target Version/s: 2.4.0 (was: 2.3.0)
> 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
>
> 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.
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