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Confluent CCDAK Exam Syllabus Topics:

SectionObjectives
Kafka Fundamentals- Kafka architecture and core concepts
  • 1. Replication and fault tolerance
    • 2. Brokers, topics, partitions
      - Data flow in Kafka
      • 1. Producer and consumer model
        • 2. Offset management
          Kafka Ecosystem and Confluent Platform- Schema Registry
          • 1. Avro, Protobuf, JSON Schema usage
            - ksqlDB and connectors
            • 1. Kafka Connect basics
              • 2. Stream querying concepts
                Kafka Producers and Consumers- Consumer API
                • 1. Consumer groups
                  • 2. Rebalancing and offset commits
                    - Producer API
                    • 1. Serialization and partitioning strategies
                      • 2. Reliability and acknowledgments
                        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

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                                Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q33-Q38):

                                NEW QUESTION # 33
                                Select the Kafka Streams joins that are always windowed joins.

                                Answer: D

                                Explanation:
                                Seehttps://docs.confluent.io/current/streams/developer-guide/dsl-api.html#joining


                                NEW QUESTION # 34
                                You want to sink data from a Kafka topic to S3 using Kafka Connect. There are 10 brokers in the cluster, the topic has 2 partitions with replication factor of 3. How many tasks will you configure for the S3 connector?

                                Answer: D

                                Explanation:
                                You cannot have more sink tasks (= consumers) than the number of partitions, so 2.


                                NEW QUESTION # 35
                                Which two statements are correct when assigning partitions to the consumers in a consumer group using the assign() API?
                                (Select two.)

                                Answer: B,D

                                Explanation:
                                Using assign() givesmanual controlover partition assignment. In this mode:
                                * B is true: The applicationchooses partitionsdirectly without involving the group coordinator.
                                * C is true: Since no group coordination occurs,no rebalancinghappens if a consumer dies.
                                FromKafka Consumer API Docs:
                                "assign() manually assigns a list of partitions to this consumer. No coordination takes place and no rebalancing is triggered."
                                * A is false: subscribe() and assign() aremutually exclusive.
                                * D is incorrect: Partitions don't need to be equal across topics.
                                Reference:Kafka Consumer Java API > assign() and subscribe()


                                NEW QUESTION # 36
                                Which two producer exceptions are examples of the class RetriableException? (Select two.)

                                Answer: A,C

                                Explanation:
                                BothLeaderNotAvailableExceptionandNotEnoughReplicasExceptionare subclasses of RetriableException, which representstransient issuesthat may succeed upon retry.
                                FromApache Kafka Java Client Documentation:
                                "RetriableException indicates that the request can be retried. This includes network errors and certain broker- side failures like leader not available or not enough replicas."
                                * RecordTooLargeException and AuthorizationException arenon-retriablebecause they represent client misconfigurations or access issues.
                                Reference:Kafka Error Handling Guide > Retriable vs. Non-Retriable Exceptions


                                NEW QUESTION # 37
                                You are creating a Kafka Streams application to process retail data.
                                Match the input data streams with the appropriate Kafka Streams object.

                                Answer:

                                Explanation:

                                Explanation:
                                * Table# Product, Customers
                                * Stream# Orders_Placed, Shipment_Of_Orders
                                * Tablesrepresent slowly changing,reference data- e.g., customer profiles, product info.
                                * Streamsrepresentreal-time event data- e.g., orders placed, shipments processed.
                                FromKafka Streams Documentation:
                                "Use KTable for reference datasets, and KStream for event-based processing such as orders or logs." Reference:Kafka Streams API Concepts


                                NEW QUESTION # 38
                                ......

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