CCDAK Reliable Exam Syllabus - Valid CCDAK Test Review

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Confluent CCDAK Exam Syllabus Topics:

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

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                                Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q75-Q80):

                                NEW QUESTION # 75
                                You want to send a message of size 3 MB to a topic with default message size configuration. How does KafkaProducer handle large messages?

                                Answer: D

                                Explanation:
                                MessageSizeTooLarge is not a retryable exception.


                                NEW QUESTION # 76
                                There are five brokers in a cluster, a topic with 10 partitions and replication factor of 3, and a quota of producer_bytes_rate of 1 MB/sec has been specified for the client. What is the maximum throughput allowed for the client?

                                Answer: D

                                Explanation:
                                Each producer is allowed to produce @ 1MB/s to a broker. Max throughput 5 * 1MB, because we have 5 brokers.


                                NEW QUESTION # 77
                                You are working on a Kafka cluster with three nodes. You create a topic named orders with:
                                replication.factor = 3
                                min.insync.replicas = 2
                                acks = allWhat exception will be generated if two brokers are down due to network delay?

                                Answer: D

                                Explanation:
                                With acks=all and min.insync.replicas=2, Kafka requires at least two in-sync replicas to acknowledge a write.
                                If only one broker is alive, the condition fails, and NotEnoughReplicasException is thrown by the producer.
                                From Kafka Producer Exception Docs:
                                "NotEnoughReplicasException is thrown when the number of in-sync replicas is insufficient to satisfy acks=all with min.insync.replicas." NetworkException is generic and not raised here.
                                NotCoordinatorException is related to consumer group coordination.
                                NotLeaderForPartitionException is unrelated unless accessing an unassigned leader.
                                Reference: Kafka Producer Error Handling


                                NEW QUESTION # 78
                                What is accomplished by producing data to a topic with a message key?

                                Answer: A

                                Explanation:
                                When amessage keyis specified in Kafka, the producer uses apartitioner(typically the default hash-based partitioner) todeterministically map all records with the same key to the same partition. Kafka guarantees order within a partition, so this enables per-key ordering.
                                FromKafka Producer Concepts:
                                "If a key is present, the producer will always route records with the same key to the same partition. Kafka preserves the order of records within a partition." This is essential for ordered processing and join semantics.
                                Reference:Kafka Producer Design > Partitions and Keys


                                NEW QUESTION # 79
                                What is true about replicas ?

                                Answer: A

                                Explanation:
                                Replicas are passive - they don't handle produce or consume request. Produce and consume requests get sent to the node hosting partition leader.


                                NEW QUESTION # 80
                                ......

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