I agree with Sean's answer, you can check out the relevant serializer
here
https://github.com/twitter/chill/blob/develop/chill-scala/src/main/scala/com/twitter/chill/Traversable.scala
On Wed, Sep 28, 2016 at 3:11 AM, Sean Owen <so...@cloudera.com> wrote:
> My guess is that Kryo specially handles Maps generically or relies on
> some mechanism that does, and it happens to iterate over all
> key/values as part of that and of course there aren't actually any
> key/values in the map. The Java serialization is a much more literal
> (expensive) field-by-field serialization which works here because
> there's no special treatment. I think you could register a custom
> serializer that handles this case. Or work around it in your client
> code. I know there have been other issues with Kryo and Map because,
> for example, sometimes a Map in an application is actually some
> non-serializable wrapper view.
>
> On Wed, Sep 28, 2016 at 3:18 AM, Maciej Szymkiewicz
> <mszymkiew...@gmail.com> wrote:
>> Hi everyone,
>>
>> I suspect there is no point in submitting a JIRA to fix this (not a Spark
>> issue?) but I would like to know if this problem is documented anywhere.
>> Somehow Kryo is loosing default value during serialization:
>>
>> scala> import org.apache.spark.{SparkContext, SparkConf}
>> import org.apache.spark.{SparkContext, SparkConf}
>>
>> scala> val aMap = Map[String, Long]().withDefaultValue(0L)
>> aMap: scala.collection.immutable.Map[String,Long] = Map()
>>
>> scala> aMap("a")
>> res6: Long = 0
>>
>> scala> val sc = new SparkContext(new
>> SparkConf().setAppName("bar").set("spark.serializer",
>> "org.apache.spark.serializer.KryoSerializer"))
>>
>> scala> sc.parallelize(Seq(aMap)).map(_("a")).first
>> 16/09/28 09:13:47 ERROR Executor: Exception in task 2.0 in stage 2.0 (TID 7)
>> java.util.NoSuchElementException: key not found: a
>>
>> while Java serializer works just fine:
>>
>> scala> val sc = new SparkContext(new
>> SparkConf().setAppName("bar").set("spark.serializer",
>> "org.apache.spark.serializer.JavaSerializer"))
>>
>> scala> sc.parallelize(Seq(aMap)).map(_("a")).first
>> res9: Long = 0
>>
>> --
>> Best regards,
>> Maciej
>
> ---------------------------------------------------------------------
> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org
>
---------------------------------------------------------------------
To unsubscribe e-mail: dev-unsubscr...@spark.apache.org
