Confluent CCDAK認證題庫 & CCDAK最新題庫

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Confluent CCDAK Exam Syllabus Topics:

SectionObjectives
Topic 1: Kafka Fundamentals- Data flow in Kafka
  • 1. Producer and consumer model
    • 2. Offset management
      - Kafka architecture and core concepts
      • 1. Brokers, topics, partitions
        • 2. Replication and fault tolerance
          Topic 2: Kafka Ecosystem and Confluent Platform- ksqlDB and connectors
          • 1. Kafka Connect basics
            • 2. Stream querying concepts
              - Schema Registry
              • 1. Avro, Protobuf, JSON Schema usage
                Topic 3: Kafka Streams and Processing- Event processing patterns
                • 1. Windowing and aggregation
                  • 2. Exactly-once semantics
                    - Kafka Streams API
                    • 1. Stateful vs stateless processing
                      • 2. Stream processing fundamentals
                        Topic 4: 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

                                >> Confluent CCDAK認證題庫 <<

                                CCDAK最新題庫 - CCDAK資料

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                                最新的 Confluent Certified Developer CCDAK 免費考試真題 (Q67-Q72):

                                問題 #67
                                (You deploy a Kafka Streams application with five application instances.
                                Kafka Streams stores application metadata using internal topics.
                                Auto-topic creation is disabled in the Kafka cluster.
                                Which statement about this scenario is true?)

                                答案：B

                                解題說明：
                                According to the official Apache Kafka Streams documentation, Kafka Streams relies on internal topics (such as changelog topics and repartition topics) to store state, task assignments, and application metadata. These topics are essential for fault tolerance, rebalancing, and state recovery.
                                When auto-topic creation is disabled, Kafka Streams cannot automatically create the required internal topics unless they already exist. In this situation, the Streams application will fail during startup with a fatal, non- retriable exception, indicating that the necessary internal topics could not be created.
                                Kafka Streams does not pause or wait for manual topic creation, nor does it operate without storing metadata.
                                Instead, it explicitly requires these topics to exist or be creatable. While administrators can manually pre- create the required internal topics with the correct configuration, failure to do so causes the application to terminate.
                                Therefore, the correct and documented behavior is that the Kafka Streams application terminates with a non- retriable exception when auto-topic creation is disabled and required internal topics are missing.


                                問題 #68
                                The rule "same key goes to the same partition" is true unless...

                                答案：A

                                解題說明：
                                Increasing the number of partition causes new messages keys to get hashed differently, and breaks the guarantee "same keys goes to the same partition". Kafka logs are immutable and the previous messages are not re-shuffled.


                                問題 #69
                                If I want to have an extremely high confidence that leaders and replicas have my data, I should use

                                答案：B

                                解題說明：
                                acks=all means the leader will wait for all in-sync replicas to acknowledge the record. Also the min in-sync replica setting specifies the minimum number of replicas that need to be in-sync for the partition to remain available for writes.


                                問題 #70
                                In Kafka Streams, by what value are internal topics prefixed by?

                                答案：D

                                解題說明：
                                In Kafka Streams, the application.id is also the underlying group.id for your consumers, and the prefix for all internal topics (repartition and state)


                                問題 #71
                                How will you find out all the partitions where one or more of the replicas for the partition are not in-sync with the leader?

                                答案：A


                                問題 #72
                                ......

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