I meant I have 7 topics and each has 12 partitions. Considering that I have 4 
streaming threads per node, I was expecting to see each thread process 1 
partition from each topics and 7 partitions total per streaming thread. But 
that’s not the case. Or perhaps you are saying the number of streaming threads 
should follow the total number of partitions across all 7 topics?!

Ara.

> On Jan 9, 2017, at 11:48 AM, Michael Noll <mich...@confluent.io> wrote:
>
> What does the processing topology of your Kafka Streams application look
> like, and what's the exact topic and partition configuration?  You say you
> have 12 partitions in your cluster, presumably across 7 topics -- that
> means that most topics have just a single partition.  Depending on your
> topology (e.g. if you have defined that single-partition topics A, B, C
> must be joined), Kafka Streams is forced to let one of your three Streams
> nodes process "more" topics/partitions than the other two nodes.
>
> -Michael
>
>
>
> On Mon, Jan 9, 2017 at 6:52 PM, Ara Ebrahimi <ara.ebrah...@argyledata.com>
> wrote:
>
>> Hi,
>>
>> I have 3 kafka brokers, each with 4 disks. I have 12 partitions. I have 3
>> kafka streams nodes. Each is configured to have 4 streaming threads. My
>> topology is quite complex and I have 7 topics and lots of joins and states.
>>
>> What I have noticed is that each of the 3 kafka streams nodes gets
>> configured to process variables number of partitions of a topic. One node
>> is assigned to process 2 partitions of topic a and another one gets
>> assigned 5. Hence I end up with nonuniform throughput across these nodes.
>> One node ends up processing more data than the other.
>>
>> What’s going on? How can I make sure partitions assignment to kafka
>> streams nodes is uniform?
>>
>> On a similar topic, is there a way to make sure partition assignment to
>> disks across kafka brokers is also uniform? Even if I use a round-robin one
>> to pin partitions to broker, but there doesn’t seem to be a way to
>> uniformly pin partitions to disks. Or maybe I’m missing something here? I
>> end up with 2 partitions of topic a on disk 1 and 3 partitions of topic a
>> on disk 2. It’s a bit variable. Not totally random, but it’s not uniformly
>> distributed either.
>>
>> Ara.
>>
>>
>>
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