it works in 2.0.0-SNAPSHOT
On Mon, Feb 22, 2016 at 6:24 PM, Michael Armbrust <mich...@databricks.com>
wrote:
> I think this will be fixed in 1.6.1. Can you test when we post the first
> RC? (hopefully later today)
>
> On Mon, Feb 22, 2016 at 1:51 PM, Daniel Siegmann <
> daniel.siegm...@teamaol.com> wrote:
>
>> Experimenting with datasets in Spark 1.6.0 I ran into a serialization
>> error when using case classes containing a Seq member. There is no
>> problem when using Array instead. Nor is there a problem using RDD or
>> DataFrame (even if converting the DF to a DS later).
>>
>> Here's an example you can test in the Spark shell:
>>
>> import sqlContext.implicits._
>>
>> case class SeqThing(id: String, stuff: Seq[Int])
>> val seqThings = Seq(SeqThing("A", Seq()))
>> val seqData = sc.parallelize(seqThings)
>>
>> case class ArrayThing(id: String, stuff: Array[Int])
>> val arrayThings = Seq(ArrayThing("A", Array()))
>> val arrayData = sc.parallelize(arrayThings)
>>
>>
>> // Array works fine
>> arrayData.collect()
>> arrayData.toDF.as[ArrayThing]
>> arrayData.toDS
>>
>> // Seq can't convert directly to DS
>> seqData.collect()
>> seqData.toDF.as[SeqThing]
>> seqData.toDS // Serialization exception
>>
>> Is this working as intended? Are there plans to support serializing
>> arbitrary Seq values in datasets, or must everything be converted to
>> Array?
>>
>> ~Daniel Siegmann
>>
>
>
