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https://issues.apache.org/jira/browse/KAFKA-7250?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16570551#comment-16570551
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Guozhang Wang commented on KAFKA-7250:
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[~michald] Do you want to submit a PR to fix this issue?

> Kafka-Streams-Scala DSL transform shares transformer instance
> -------------------------------------------------------------
>
>                 Key: KAFKA-7250
>                 URL: https://issues.apache.org/jira/browse/KAFKA-7250
>             Project: Kafka
>          Issue Type: Bug
>            Reporter: Michal
>            Priority: Major
>
> The new Kafka Streams Scala DSL provides transform function with following 
> signature
> {{def transform[K1, V1](transformer: Transformer[K, V, (K1, V1)], 
> stateStoreNames: String*): KStream[K1, V1]}}
> the provided 'transformer' (will refer to it as scala-transformer)  instance 
> is than used to derive java Transformer instance and in turn a 
> TransformerSupplier that is passed to the underlying java DSL. However that 
> causes all the tasks to share the same instance of the scala-transformer. 
> This introduce all sort of issues. The simplest way to reproduce is to 
> implement simplest transformer of the following shape:
> {{.transform(new Transformer[String, String, (String, String)] {}}
>     var context: ProcessorContext = _
> {{  def init(pc: ProcessorContext) = \{ context = pc}}}
> {{  def transform(k: String, v: String): (String, String) = {}}
>         context.timestamp() 
>         ...
> {{  }}}{{})}}
> the call to timestmap will die with exception "This should not happen as 
> timestamp() should only be called while a record is processed" due to record 
> context not being set - while the update of record context was actually 
> performed, but due to shared nature of the scala-transformer the local 
> reference to the processor context is pointing to the one of the last 
> initialized task rather than the current task. 
> The solution is to accept a function in following manner: 
> def transform[K1, V1](getTransformer: () => Transformer[K, V, (K1, V1)], 
> stateStoreNames: String*): KStream[K1, V1]
>  or TransformerSupplier - like the transformValues DSL function does.



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