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From "Guozhang Wang (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (KAFKA-3429) Remove Serdes needed for repartitioning in KTable stateful operations
Date Wed, 23 Aug 2017 00:39:00 GMT

     [ https://issues.apache.org/jira/browse/KAFKA-3429?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Guozhang Wang updated KAFKA-3429:
---------------------------------
    Labels: api  (was: api newbie++)

> Remove Serdes needed for repartitioning in KTable stateful operations
> ---------------------------------------------------------------------
>
>                 Key: KAFKA-3429
>                 URL: https://issues.apache.org/jira/browse/KAFKA-3429
>             Project: Kafka
>          Issue Type: Sub-task
>          Components: streams
>            Reporter: Guozhang Wang
>              Labels: api
>
> Currently in KTable aggregate operations where a repartition is possibly needed since
the aggregation key may not be the same as the original primary key, we require the users
to provide serdes (default to configured ones) for read / write to the internally created
re-partition topic. However, these are not necessary since for all KTable instances either
generated from the topics directly:
> {code}table = builder.table(...){code}
> or from aggregation operations:
> {code}table = stream.aggregate(...){code}
> There are already serde provided for materializing the data, and hence the same serde
can be re-used when the resulted KTable is involved in future aggregation operations. For
example:
> {code}
> table1 = stream.aggregateByKey(serde);
> table2 = table1.aggregate(aggregator, selector, originalSerde, aggregateSerde);
> {code}
> We would not need to require users to specify the "originalSerde" in table1.aggregate
since it could always reuse the "serde" from stream.aggregateByKey, which is used to materialize
the table1 object.
> In order to get ride of it, implementation-wise we need to carry the serde information
along with the KTableImpl instance in order to re-use it in a future operation that requires
repartitioning.



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