Batch Consumer with a given period doesn't work with multiple partition in Spring Cloud Stream(StreamListener)?

Question

    @StreamListener(value = PersonStream.INPUT)
    private void personBulkReceiver(List<Person> person) {
    //....
    }

spring:
  cloud:
    stream:
      kafka:
      binders:
        bulkKafka:
          type: kafka
          environment:
            spring:
              cloud:
                stream:
                  kafka:
                    binder:
                      brokers: localhost:9092
                      configuration:
                        max.poll.records: 1500
                        fetch.min.bytes: 10000000
                        fetch.max.wait.ms: 10000
                        value.deserializer: tr.cloud.stream.examples.PersonDeserializer
      bindings:
        person-topic-in:
          binder: bulkKafka
          destination: person-topic
          contentType: application/person
          group : person-group
          consumer:
            batch-mode: true

I'am using Spring Cloud Stream with Kafka. In a StreamListener when partition count is 1 I can consume records in batch mode in every 5000 ms.

My .yml configuration is fetch.min.bytes = 10000000 && fetch.max.wait.ms = 50000 && max.poll.records = 1500 as stated above.

I can receive batch records in every 5000 ms. since batch record size doesn't exceed 10000000 bytes.

But when partition count is more than 1 StreamListener consumes records earlier than 5000 ms.

Is there any configuration for this case?

Or is this case is the natural result of independent threads working for each partition?

When partition count is more than 1 what is the difference in working logic ?

Answer 1

According to your readme...

And there is always a lot of data on the topic.

So that doesn't match your question where you said...

I can receive batch records in every 5000 ms. since batch record size doesn't exceed 10000000 bytes.

When there is more data than that, it will always be pushed to the client.

Consider using a Polled Consumer instead, to receive data at your desired rate.