CCDAK Exam Dumps : Confluent Certified Developer for Apache Kafka Certification Examination

If the consumer fails to send heartbeats in time (due to being slow under load), it is considered dead, causing a rebalance. Increasing session.timeout.ms gives the consumer more time to process messages and send heartbeats, preventing premature removal.

From Kafka Docs > Heartbeats and Failures:

“If the consumer does not send a heartbeat in session.timeout.ms, it is considered dead and the group coordinator will trigger a rebalance.”

Reducing max.poll.records might slow consumption further. More consumers won’t help since each partition already has a dedicated consumer.

The offset in the RecordMetadata object returned by the producer represents the position of the record in the partition — i.e., the sequential ID assigned by Kafka once the message is committed.

From Kafka Producer API Documentation:

“The offset is the position of the record in the partition. This is a unique, sequential number assigned by the broker.”

D refers to metadata.partition(), not offset().

B and C are unrelated to how Kafka handles committed offsets.

Low I/O thread activity with blocked throughput often indicates that producer callbacks are consuming too much time, causing the sender thread to block while waiting for onCompletion() to finish.

From Kafka Producer Performance Guide:

“Expensive logic in callbacks (e.g., I/O or complex computation) can block the sender thread, reducing throughput.”

Compression (A) may slightly impact CPU but not I/O thread usage.

Large batches (B) improve throughput if managed correctly.

A Layer 2 network issue (C) would lead to packet loss, not specifically low callback metrics.