should create your repartitioning topic you specify in
> through() before you start your Kafka Streams application.
>
>
> -Matthias
>
>
> On 08/31/2016 09:07 PM, Guozhang Wang wrote:
> > Hello Tommy,
> >
> > Which version of Kafka are you using?
> >
> >
gt; a 1
> b 1
> a 2
> b 2
> c 1
>
> ?
>
> On Wed, Aug 31, 2016 at 5:47 AM, Tommy Q wrote:
>
> > Tried the word count example as discussed, the result in wc-out is wrong:
> >
> > a 1
> > > b 1
> > > a 1
> > > b 1
> > >
Hi @Matthias & @Michael I pushed the WordCountDemo code to GitHub
https://github.com/deeplambda/kstream-debug, can you help to debug the demo
?
Thanks,
Tommy
On Wed, Aug 31, 2016 at 11:47 AM, Tommy Q wrote:
> Tried the word count example as discussed, the result in wc-out is wrong:
topics.
>
> The only explanation might be, that there is no repartitioning step. But
> than the question would be, if there is a bug in Kafka Streams, because
> between map() and countByKey() repartitioning is required.
>
> Can you verify that the result is correct?
>
> -Matth
Got it. Thanks Michael.
On Tue, Aug 30, 2016 at 2:31 AM, Michael Noll wrote:
> Most probably because, in your build.sbt, you didn't enable the
> -Xexperimental compiler flag for Scala. This is required when using Scala
> 2.11 (as you do) to enable SAM for Java 8 lambda support. Because this
>
tps://cwiki.apache.org/confluence/display/KAFKA/
> Kafka+Streams%3A+Internal+Data+Management
>
> and
>
> http://www.confluent.io/blog/data-reprocessing-with-kafka-
> streams-resetting-a-streams-application
>
>
> -Matthias
>
>
> On 08/30/2016 06:55 AM, Tommy Q wrote:
Michael, Thanks for your help.
Take the word count example, I am trying to walk through the code based on
your explanation:
val textLines: KStream[String, String] = builder.stream("input-topic")
val wordCounts: KStream[String, JLong] = textLines
.flatMapValues(_.toLowerCase.split("\
