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

According to the official Apache Kafka Connect documentation, RegexRouter is the SMT specifically designed to dynamically change the destination topic name of records produced by a connector. It works by applying a regular expression to the original topic name and rewriting it to a new topic name.

This makes RegexRouter the correct choice when some records must be routed to a different topic, typically in combination with connector-level logic, predicates, or multiple connectors. It is commonly used for topic renaming, topic versioning, or routing records to alternate topics.

InsertField (Option B) only adds metadata fields (such as topic, partition, or timestamp) to the record payload and does not affect routing. TombstoneHandler (Option C) is used to manage null-value records, especially with compacted topics. HeaderFrom (Option D) copies fields into headers but does not change the target topic.

Therefore, RegexRouter is the only SMT that directly supports changing the output topic, as documented in the Kafka Connect SMT reference.

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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, and all 15 can be active depending on processing topology.

From Kafka 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.

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.