Hi group,
I wrote a simple kafka streams application with topology such as below:
builder.addStateStore(
> Stores.keyValueStoreBuilder(
> Stores.persistentKeyValueStore("STORE"),
> Serdes.String(), Serdes.String())
> .withLoggingEnabled(storeConfig))|
builder.stream("TOPIC_1", Consumed.with(...))
> .merge(builder.stream("TOPIC_2", Consumed.with(...))
> .merge(builder.stream("TOPIC_3", Consumed.with(...))
> .map(...) // stateless
> .transform(..., "STORE") // stateful
.to("TOPIC_4");
All input topics have 6 partitions, and for the purpose of testing, we are
producing data to partition number 5.
We are using kafka streams version 2.8.1, broker version 2.12-2.1.1
The application works as expected when it has caught up to the lag, eg.
when reset tool is used with --to-latest parameter.
However, when the application is processing the messages starting from the
earliest offset, the inputs are provided in batches such as:
- ~1000 messages from TOPIC_1
- ~1000 messages from TOPIC_2
- ~1000 messages from TOPIC_3
All of the messages have timestamps provided in headers, so I would expect
the application to interleave the messages from these three topics so that
their timestamps are in the ascending order.
However, this is not the case that I am observing. The messages are
processed in batches.
How do I configure my application so that it processes messages in order
when it is catching up to the lag?
