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  1. Kafka
  2. KAFKA-7250

Kafka-Streams-Scala DSL transform shares transformer instance



    • Type: Bug
    • Status: Resolved
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: 2.0.0
    • Fix Version/s: 2.0.1, 2.1.0
    • Component/s: streams
    • Labels:


      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) = {




      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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              • Assignee:
                mdziemianko Michal Dziemianko
                michald Michal
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