[ 
https://issues.apache.org/jira/browse/SPARK-17368?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15456966#comment-15456966
 ] 

Jakob Odersky commented on SPARK-17368:
---------------------------------------

FYI the issue also occurs for top-level value classes (i.e. {{FeatureId}} 
defined outside of {{object BreakSpark}})

> Scala value classes create encoder problems and break at runtime
> ----------------------------------------------------------------
>
>                 Key: SPARK-17368
>                 URL: https://issues.apache.org/jira/browse/SPARK-17368
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core, SQL
>    Affects Versions: 1.6.2, 2.0.0
>         Environment: JDK 8 on MacOS
> Scala 2.11.8
> Spark 2.0.0
>            Reporter: Aris Vlasakakis
>
> Using Scala value classes as the inner type for Datasets breaks in Spark 2.0 
> and 1.6.X.
> This simple Spark 2 application demonstrates that the code will compile, but 
> will break at runtime with the error. The value class is of course 
> *FeatureId*, as it extends AnyVal.
> {noformat}
> Exception in thread "main" java.lang.RuntimeException: Error while encoding: 
> java.lang.RuntimeException: Couldn't find v on int
> assertnotnull(input[0, int, true], top level non-flat input object).v AS v#0
> +- assertnotnull(input[0, int, true], top level non-flat input object).v
>    +- assertnotnull(input[0, int, true], top level non-flat input object)
>       +- input[0, int, true]".
>         at 
> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.toRow(ExpressionEncoder.scala:279)
>         at 
> org.apache.spark.sql.SparkSession$$anonfun$3.apply(SparkSession.scala:421)
>         at 
> org.apache.spark.sql.SparkSession$$anonfun$3.apply(SparkSession.scala:421)
> {noformat}
> Test code for Spark 2.0.0:
> {noformat}
> import org.apache.spark.sql.{Dataset, SparkSession}
> object BreakSpark {
>   case class FeatureId(v: Int) extends AnyVal
>   def main(args: Array[String]): Unit = {
>     val seq = Seq(FeatureId(1), FeatureId(2), FeatureId(3))
>     val spark = SparkSession.builder.getOrCreate()
>     import spark.implicits._
>     spark.sparkContext.setLogLevel("warn")
>     val ds: Dataset[FeatureId] = spark.createDataset(seq)
>     println(s"BREAK HERE: ${ds.count}")
>   }
> }
> {noformat}



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

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

Reply via email to