Have you tried declaring RDD[ChildTypeOne] and writing separate functions
for each sub-type ?
Cheers
On Sun, Dec 27, 2015 at 10:08 AM, pkhamutou <p.khamu...@gmail.com> wrote:
> Hello,
>
> I have a such situation:
>
> abstract class SuperType {...}
> case class ChildTypeOne(x: String) extends SuperType {.....}
> case class ChildTypeTwo(x: String) extends SuperType {....}
>
> than I have:
>
> val rdd1: RDD[SuperType] = sc./*some code*/.map(r => ChildTypeOne(r))
> val rdd2: RDD[SuperType] = sc./*some code*/.map(r => ChildTypeTwo(r))
>
> but when i try to:
> def someFunction(rdd: RDD[SuperType]) = rdd match {
> case rdd: RDD[ChildTypeOne] => println("ChildTypeOne")
> case rdd: RDD[ChildTypeTwo] => println("ChildTypeTwo")
> }
>
>
> i get:
>
> Error:(60, 15) pattern type is incompatible with expected type;
> found : org.apache.spark.rdd.RDD[ChildTypeOne]
> required: org.apache.spark.rdd.RDD[SuperType]
> Note: ChildTypeOne <: SuperType, but class RDD is invariant in type T.
> You may wish to define T as +T instead. (SLS 4.5)
> case rdd: RDD[ChildTypeOne] => println("ChildTypeOne")
> ^
>
> So how to work around it? Because in some situations I need to distinguish
> them.
>
> Best regards,
> Pavel Khamutou
>
>
>
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