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Confluent CCDAK Exam Syllabus Topics:

SectionObjectives
Kafka Producers and Consumers- Producer API
  • 1. Serialization and partitioning strategies
    • 2. Reliability and acknowledgments
      - Consumer API
      • 1. Rebalancing and offset commits
        • 2. Consumer groups
          Kafka Fundamentals- Data flow in Kafka
          • 1. Producer and consumer model
            • 2. Offset management
              - Kafka architecture and core concepts
              • 1. Replication and fault tolerance
                • 2. Brokers, topics, partitions
                  Kafka Streams and Processing- Kafka Streams API
                  • 1. Stateful vs stateless processing
                    • 2. Stream processing fundamentals
                      - Event processing patterns
                      • 1. Exactly-once semantics
                        • 2. Windowing and aggregation
                          Kafka Ecosystem and Confluent Platform- ksqlDB and connectors
                          • 1. Stream querying concepts
                            • 2. Kafka Connect basics
                              - Schema Registry
                              • 1. Avro, Protobuf, JSON Schema usage

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                                Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q53-Q58):

                                NEW QUESTION # 53
                                What's a Kafka partition made of?

                                Answer: A

                                Explanation:
                                Kafka partitions are made of segments (usually each segment is 1GB), and each segment has two corresponding indexes (offset index and time index)


                                NEW QUESTION # 54
                                How would you describe a connector in ksqlDB?

                                Answer: D


                                NEW QUESTION # 55
                                Two consumers share the same group.id (consumer group id). Each consumer will

                                Answer: C

                                Explanation:
                                Each consumer is assigned a different partition of the topic to consume.


                                NEW QUESTION # 56
                                (You are configuring a source connector that writes records to an Orders topic.
                                You need to send some of the records to a different topic.
                                Which Single Message Transform (SMT) is best suited for this requirement?)

                                Answer: B

                                Explanation:
                                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.


                                NEW QUESTION # 57
                                You are writing to a topic with acks=all.
                                The producer receives acknowledgments but you notice duplicate messages.
                                You find that timeouts due to network delay are causing resends.
                                Which configuration should you use to prevent duplicates?

                                Answer: C

                                Explanation:
                                To ensure exactly-once delivery and avoid duplicates even during retries:
                                enable.idempotence=true ensures deduplication on the broker
                                retries=2147483647 allows unlimited retries on retriable errors
                                max.in.flight.requests.per.connection=5 is the maximum value that preserves message order with idempotence From Kafka Producer Config Docs:
                                "To achieve exactly-once semantics, set enable.idempotence=true, and max.in.flight.requests.per.connection #
                                5."
                                A is unrelated (consumer-side)
                                C disables retries
                                D disables idempotence, leading to duplicates
                                Reference: Kafka Producer Configs > enable.idempotence, retries


                                NEW QUESTION # 58
                                ......

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