Confluent CCDAK Exam With Confidence Using Practice Dumps

unclean.leader.election.enable=false→ Prevents data loss by only considering in-sync replicas when rebalancing.

replication.factor→ Specifies how many redundant copies of partitions are distributed across brokers.

min.insync.replicas=2→ Sets the standard for the number of partition instances that must keep up with the latest committed message.

unclean.leader.election.enable=false ensures that onlyin-sync replicascan be elected as leaders. If disabled, an out-of-sync replica may become leader, potentially leading to data loss.

replication.factor defineshow many brokerswill maintain copies of each partition, directly impacting durability and availability.

min.insync.replicas determineshow many replicas must acknowledgea write when acks=all is used, enforcing write durability.

If a key isnot specified, thedefault Kafka partitioner uses round-robinlogic to assign partitions. This leads toeven distributionof messages across all partitions.

FromKafka Producer Design:

“If the key is null, the producer will assign the partition in a round-robin fashion to achieve load balancing.”

There isno error, and partition 0 isnot alwayschosen in this case.

In Kafka Streams,the number of stream tasks = number of input partitions × num.stream.threads × number of instances,but only as many as the number of partitions can actively consume at once.

However, in this case,Kafka Streams assigns one task per partition, and because there are 5 partitions and 15 threads (3 instances × 5 threads),15 tasks are created, andall 15 can be activedepending on processing topology.

FromKafka Streams Developer Guide:

"Kafka Streams creates one task per input partition. If you increase the number of stream threads, it runs multiple tasks in parallel within a single instance."

So,15 stream tasks will be created and 15 will be actively consuming.