You asked off-list, and provided a more detailed example there:
val random = new Random()
val testdata = (1 to 10000).map(_=>(random.nextInt(),random.nextInt()))
sc.parallelize(testdata).combineByKey[ArrayBuffer[Int]](
(instant:Int)=>{new ArrayBuffer[Int]()},
(bucket:ArrayBuffer[Int],instant:Int)=>{bucket+=instant},
(bucket1:ArrayBuffer[Int],bucket2:ArrayBuffer[Int])=>{bucket1++=bucket2}
).collect()
https://www.quora.com/Why-is-my-combinebykey-throw-classcastexception
I can't reproduce this with Spark 0.9.0 / CDH5 or Spark 1.0.0 RC9.
Your definition looks fine too. (Except that you are dropping the
first value, but that's a different problem.)
On Tue, May 20, 2014 at 2:05 AM, xiemeilong <xiemeilong...@gmail.com> wrote:
> I am using CDH5 on a three machines cluster. map data from hbase as (string,
> V) pair , then call combineByKey like this:
>
> .combineByKey[C](
> (v:V)=>new C(v), //this line throw java.lang.ClassCastException: C
> cannot be cast to V
> (v:C,v:V)=>C,
> (c1:C,c2:C)=>C)
>
>
> I am very confused of this, there isn't C to V casting at all. What's
> wrong?
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/combinebykey-throw-classcastexception-tp6059.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
