Hey Hemant,
Are you able to reconstruct the ordering of the event, for example based on
time or some sequence number?
If so, you could create as many Kafka partitions as you need (for proper
load distribution), disregarding any ordering at that point.
Then you keyBy your stream in Flink, and
Hi Arvid,
Thanks for your response. I think I did not word my question properly.
I wanted to confirm that if the data is distributed to more than one
partition then the ordering cannot be maintained (which is documented).
According to your response I understand if I set the parallelism to number
Hi Hemant,
Flink passes your configurations to the Kafka consumer, so you could check
if you can subscribe to only one partition there.
However, I would discourage that approach. I don't see the benefit to just
subscribing to the topic entirely and have dedicated processing for the
different
Hello Flink Users,
I have a use case where I am processing metrics from different type of
sources(one source will have multiple devices) and for aggregations as well
as build alerts order of messages is important. To maintain customer data
segregation I plan to have single topic for each customer
