HI Kafka Dev Team,
We have to aggregate events (count) per DC and across DCs for one of topic. We have standard Linked-in data pipe line producers --> Local Brokers --> MM --> Center Brokers. So I would like to know How MM handles messages when custom partitioning logic is used as below and number of partition in target DC is SAME vs different than the source DC ? If we have key based messages and custom partitioning logic ( hash(key) % number of partition per topic source topic) we want to count event similar event by hashing to same partition and count events, and but when same event is MM to target DC will it go to same partition even though number of partition is different in target DC (meaning does MM will use hash(key message) % number of partition) ? According to this reference, I do not have way to configure this or to control which partitioning logic to use when MM data ? https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=27846330 Thanks, Bhavesh
