[jira] [Created] (SPARK-17890) scala.ScalaReflectionException

["Khalid Reid (JIRA)" <ji...@apache.org>]

Khalid Reid created SPARK-17890:
-----------------------------------

             Summary: scala.ScalaReflectionException
                 Key: SPARK-17890
                 URL: https://issues.apache.org/jira/browse/SPARK-17890
             Project: Spark
          Issue Type: Bug
    Affects Versions: 2.0.1
         Environment: x86_64 GNU/Linux
Java(TM) SE Runtime Environment (build 1.8.0_60-b27)
            Reporter: Khalid Reid
            Priority: Minor


Hello,

I am seeing a very cryptic error message in spark-shell when I map a DataFrame to a Seq\[Foo\].  However, things work fine when I use flatMap.  

{noformat}
scala> case class Foo(value:String)
defined class Foo

scala> val df = sc.parallelize(List(1,2,3)).toDF
df: org.apache.spark.sql.DataFrame = [value: int]

scala> df.map{x => Seq.empty[Foo]}
scala.ScalaReflectionException: object $line14.$read not found.
  at scala.reflect.internal.Mirrors$RootsBase.staticModule(Mirrors.scala:162)
  at scala.reflect.internal.Mirrors$RootsBase.staticModule(Mirrors.scala:22)
  at $typecreator1$1.apply(<console>:29)
  at scala.reflect.api.TypeTags$WeakTypeTagImpl.tpe$lzycompute(TypeTags.scala:232)
  at scala.reflect.api.TypeTags$WeakTypeTagImpl.tpe(TypeTags.scala:232)
  at org.apache.spark.sql.SQLImplicits$$typecreator9$1.apply(SQLImplicits.scala:125)
  at scala.reflect.api.TypeTags$WeakTypeTagImpl.tpe$lzycompute(TypeTags.scala:232)
  at scala.reflect.api.TypeTags$WeakTypeTagImpl.tpe(TypeTags.scala:232)
  at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$.apply(ExpressionEncoder.scala:49)
  at org.apache.spark.sql.SQLImplicits.newProductSeqEncoder(SQLImplicits.scala:125)
  ... 48 elided

scala> df.flatMap{_ => Seq.empty[Foo]} //flatMap works
res2: org.apache.spark.sql.Dataset[Foo] = [value: string]

{noformat}

I am seeing the same error reported [here|https://issues.apache.org/jira/browse/SPARK-8465?jql=text%20~%20%22scala.ScalaReflectionException%22] when I use spark-submit.

I am new to Spark so if this an invalid code (though I don't see why it would be) then I'd expect to see a better error message.







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