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From Boyang Chen <reluctanthero...@gmail.com>
Subject Re: How do I tell Kafka Streams not to repartition?
Date Fri, 09 Aug 2019 22:31:04 GMT
In case I'm not making myself clear, any operation that changes the record
key will result in repartition. Since you don't want that, you shall choose
to call groupByKey afterwards and aggregation will happen on `parent id`
level.

On Fri, Aug 9, 2019 at 3:27 PM Boyang Chen <reluctanthero104@gmail.com>
wrote:

> Hey Tim,
>
> I think the functionality you need is groupByKey() which avoids
> repartitioning, feel free to check it out here:
> https://docs.confluent.io/current/streams/developer-guide/dsl-api.html#aggregating.
> Recommend you to read the whole thing but feel free just to search
> `groupByKey`.
>
> On Fri, Aug 9, 2019 at 7:14 AM Tim Ward <tim.ward@origamienergy.com>
> wrote:
>
>> I've got an input topic which is keyed by "parent ID". Each message
>> contains multiple items of data, each for a different "child ID".
>>
>> To process these items separately I flatMapValues() the stream to make a
>> new stream of the inner items of data, keyed by "child ID".
>>
>> Now, because I've changed the key, Kafka Streams thinks a repartition is
>> needed. But in fact it isn't, because all the inner items for a particular
>> "child ID" will be contained within messages keyed with the same "parent
>> ID".
>>
>> How do I tell Kafka Streams that there is no need to repartition in this
>> case, because all the data that should remain together in the same instance
>> of the application will do so without repartitioning? (I appreciate that
>> Streams can't know about the parent-child relationship unless I *do* tell
>> it in some way.)
>>
>> Tim Ward
>>
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>

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