[Enhancement request] SpringWolf to be compatible with Reactor Kafka

[KafkaProServerless]

Hello team,

Came into this project from this talk: https://www.youtube.com/watch?v=DylvTW_ia4Y

If nothing else, this project seems to be very cool, very interesting.

We are using Kafka, and want to integrate with SpringWolf.

However, we are not using a regular Spring Kafka, but using reactor kafka https://github.com/reactor/reactor-kafka

Same question as in the talk around minute 33, can this project support reactor kafka?

Thank you

[github-actions[bot]]

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[sam0r040]

Hi @KafkaProServerless, thanks a lot for your interest in Springwolf and watching the video. Springwolf heavily relies on Spring Framework and therefore we do not plan nor have the capacity to support other frameworks.

[KafkaProServerless]

Hello @sam0r040, thank you for the answer. But reactor kafka is also relying on Spring Framework. It is not like reactor kafka is something that has nothing to do with spring kafka, it is just the reactor version of it.

[sam0r040]

Hi @KafkaProServerless, if you have Spring ecosystem available, then you can use Springwolf. We can imagine that the following could work for you:

Given the example consumer from ractor-kafka, you can use Springwolfs generic annotations like this:

    @AsyncListener(
            operation = @AsyncOperation(
                    channelName = "kafka-topic-name"
            )
    )
    private void receiveRecord(CountDownLatch latch, @Payload ReceiverRecord<Integer, PayloadDto> record) {
    }

    record PayloadDto(String myProperty) {
    }

We extracted the lambda into a method so that you can make use of the @Payload annotation so that Springwolf can automatically detect payload type.

Don not forget to configure extractable classes for ReceiverRecord to that the payload is extracted correctly from the second generic type: springwolf.payload.extractable-classes.reactor.kafka.receiver.ReceiverRecord=1

See https://www.springwolf.dev/docs/configuration/documenting-consumers#asynclistener for more details.

[KafkaProServerless]

Let me try that!