Current state: Accepted
Discussion thread: here
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KStream.transform transforms each record of the input stream into zero or more records in the output stream. A
Transformer object is applied on each input record. The transformation is stateful, i.e., the transformer accesses state stores to compute output records. The signature of
KStream.transform specifies a single key-value pair as output record. However, the user can emit multiple records for each input record if she calls for each desired output record method
forward on the
ProcessorContext object that is given to the transformer. By calling
forward on the context, the user looses strong typing of the output records, i.e., if a user emits an output record that is not of the type specified in the transformer, the error is only thrown at run time and not at compile time. Furthermore, the public API misses a stateful transformation that transforms the value of each record of the input stream into zero or more records with same key but potentially different values in the output stream. Such a transformation would be the stateful equivalent of
Stateful transform operations that ensure strong typing and that are more consistent with the stateless map operations, would make the public API safer to use, better comprehensible, and more complete.
In org.apache.kafka.streams.kstream.KStream.java the following methods shall be added:
<K1, V1> KStream<K1, V1> flatTransform( final TransformerSupplier<? super K, ? super V, ? extends Iterable<? extends KeyValue<? extends K1, ? extends V1>>> transformerSupplier, final String... stateStoreNames); <VR> KStream<K, VR> flatTransformValues(final ValueTransformerSupplier<? super V, ? extends Iterable<? extends VR>> valueTransformerSupplier, final String... stateStoreNames); <VR> KStream<K, VR> flatTransformValues( final ValueTransformerWithKeySupplier<? super K, ? super V, ? extends Iterable<? extends VR>> valueTransformerSupplier, final String... stateStoreNames);
This KIP proposes the following changes:
KStream.flatTransformto the public API:
Iterable) as output records for each input record. The addition of the method comprises the implementation of the method in the streams internals and appropriate tests.
KStream.flatTransformValuesto the public API:
KStream.transformto emit zero or one output record:
KStream.flatTransformif multiple records should be emitted per input record. Disallowing the use of
ProcessorContext.forwardin the code would potentially break existing applications. However, for the next major release, it should be considered to disallow the use of
ProcessorContext.forward. A JIRA issue that requires to disallow the use of
KStream.transformwill be created for the next major release.
This change is compatible with existing Kafka Streams applications.
ProcessorContext.forwardin the code:
ProcessorContext.forwardin the code would break existing applications. However, it should be considered for the next major release.