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

According to the Apache Kafka producer documentation, serialization is configured independently for message keys and values. The key and value can use different serializers depending on their data types.

In this scenario, the message key is a string, so the producer must be configured with org.apache.kafka.common.serialization.StringSerializer for the key. The value contains JSON, so a suitable JSON serializer must be configured for the value, such as a custom JSON serializer, a library-based serializer, or a byte-array serializer after converting the JSON to bytes.

Option B correctly reflects this separation by specifying a string serializer for the key and a JSON serializer for the value. Kafka does not automatically infer serializers, and setting a serializer to null is invalid. Additionally, there is no built-in “JSON” serializer for keys, making Option D incorrect.

Therefore, the correct approach—fully aligned with Kafka’s producer configuration model—is to explicitly configure a StringSerializer for the key and a JSON-capable serializer for the value.

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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.

Comprehensive and Detailed Explanation From Exact Extract:

✅ C. Consumers can consume both committed and uncommitted transactions.By default, Kafka consumers only read committed messages if they are configured with isolation.level=read_committed. However, if configured as read_uncommitted, they can also consume uncommitted (potentially aborted) transactional messages.

From Kafka Documentation:

"The isolation.level setting controls whether the consumer will read only committed messages or all messages, including uncommitted messages from ongoing or aborted transactions."

✅ D. Information about producers and their transactions is stored in the _transaction_state topic.Kafka uses an internal topic named __transaction_state to maintain metadata about producer transactions. This topic is essential for tracking the transaction lifecycle, fencing, and recovery.

From Kafka Internals:

“Kafka stores the state of active and completed transactions in an internal topic called __transaction_state.”