I think what happened in your use case was that the following implicit
from ImplicitConversions.scala kept wrapping the resultant KTable from
filter():
implicit def wrapKTable[K, V](inner: KTableJ[K, V]): KTable[K, V] =
leading to stack overflow.
Cheers
On Mon, Aug 20, 2018 at 12:50 PM Druhin Sagar Goel <dru...@arrcus.com>
wrote:
> Hi,
>
> I’m using the org.kafka.streams.scala that was released with version
> 2.0.0. I’m getting a StackOverflowError as follows:
>
> java.lang.StackOverflowError
> at org.apache.kafka.streams.scala.kstream.KTable.filter(KTable.scala:49)
> at org.apache.kafka.streams.scala.kstream.KTable.filter(KTable.scala:49)
> at org.apache.kafka.streams.scala.kstream.KTable.filter(KTable.scala:49)
> at org.apache.kafka.streams.scala.kstream.KTable.filter(KTable.scala:49)
> .
> .
> .
> at org.apache.kafka.streams.scala.kstream.KTable.filter(KTable.scala:49)
>
> The Scala version I’m using is 2.11.11 and the code leading to the error
> is as follows (particularly the .filter).
>
> val builder = new StreamsBuilder
>
> val stream = builder.stream[Array[Byte], CaseClassA](args.topic)
>
> val customers = args.config.keys
>
> val predicates = customers.map { customerId =>
> (_: Array[Byte], message: CaseClassA) => message.customerId == customerId
> }.toSeq
>
> val customerIdToStream = customers.zip(stream(predicates: _*)).toMap
>
> val y = Printed.toSysOut[Windowed[Key], Long]
>
> customerIdToStream.foreach { case (customerId, customerStream) =>
> val customerConfig = args.config(customerId)
> customerStream
> .flatMap { case (_, message) =>
> message.objects.map {
> case CaseClassB(c, _) => Key(message.id, c.prefix) -> 1
> }
> }
> .groupByKey
>
> .windowedBy(TimeWindows.of(customerConfig.windowSize).advanceBy(customerConfig.sliderSize))
> .count()
> .filter { case (_, count) => count >=
> customerConfig.frequencyThreshold }
> .toStream
> .print(y)
> }
>
> Is this a bug with the new scala module related to:
> https://github.com/lightbend/kafka-streams-scala/issues/63 ?
> Or am I doing something wrong?
>
> Thanks,
> Druhin
>
