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From Artur Mrozowski <art...@gmail.com>
Subject Re: Joins in Kafka Streams and partitioning of the topics
Date Thu, 30 Nov 2017 18:16:19 GMT
Thank you Damian, it was very helpful.
I have implemented my solution in version but there is one thing I
still wonder.
So what I try to do is what is described in KIP 150. Since it didn't make
to the release for 1.0 I do it the old fashioned way.
KTable<K, V1> table1 =
aggregator1, aggValueSerde1, storeName1);

for all the four topics and then I join the results.
And here is the thing, the topics are partitioned and I don't used global
tables, nor keyed messages and it seems to work fine.

>From Confluents documentation one could get impression that when reading
from partitoned topics you need to use global tables. But is it really
necessary in this case?
And if not then why?

Thanks again

Here is the link to my implementation


On Wed, Nov 22, 2017 at 12:10 PM, Damian Guy <damian.guy@gmail.com> wrote:

> Hi Artur,
> KafkaStreams is quite old and a lot has changed and been fixed
> since then. If possible i'd recommend upgrading to at least or
> 1.0.
> For joins you need to ensure that the topics have the same number of
> partitions (which they do) and that they are keyed the same.
> Thanks,
> Damian
> On Wed, 22 Nov 2017 at 11:02 Artur Mrozowski <artmro@gmail.com> wrote:
> > Hi,
> > I am joining 4 different topic with 4 partitions each using
> > version of Kafka Streams.  The joins are KTable to KTable. Is there
> > anything I should be aware of considering partitions or version of Kafka
> > Streams? In other words should I be expecting consistent results or do I
> > need to for example use Global tables.
> >
> > I'd like to run that application on Kubernetes later on. Should I think
> of
> > anything or do different instances of the same Kafka Streams application
> > take care of management of the state?
> >
> > Grateful for any thoughts or a piece of advice
> >
> > Best Regards
> > /Artur
> >

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