最新版的CCDAK考古题推薦，真實還原Confluent CCDAK考試內容

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Confluent CCDAK Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Apache Kafka Application Development28%- Producer API: configuration, serialization, partitioning, error handling
- Transactional messaging and idempotence
- Schema management: Confluent Schema Registry, compatibility rules, evolution
- Consumer API: configuration, offset management, consumer groups, rebalancing
Topic 2: Application Testing8%- Unit testing producers and consumers
- Integration testing and test clusters
- Mocking and test utilities
Topic 3: Apache Kafka Streams12%- Stream processing operations: map, filter, join, aggregation
- Streams API concepts: topology, processors, state stores
- Error handling and state management
- Windowing and time semantics
Topic 4: Kafka Connect15%- Data transformation and integration patterns
- Source and sink connectors configuration
- Connect architecture: workers, connectors, tasks, converters
Topic 5: Application Observability13%- Error diagnosis and troubleshooting
- Logging and monitoring metrics
- Tracing and performance tuning
Topic 6: Apache Kafka Fundamentals23%- Kafka architecture and data flow
- Delivery semantics: at-most-once, at-least-once, exactly-once
- Core concepts: brokers, topics, partitions, replicas, offsets
- Configuration basics and cluster setup

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CCDAK PDF - CCDAK證照信息

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最新的 Confluent Certified Developer CCDAK 免費考試真題 (Q29-Q34):

問題 #29
What's a Kafka partition made of?

答案：A

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


問題 #30
You have a Kafka cluster and all the topics have a replication factor of 3. One intern at your company stopped a broker, and accidentally deleted all the data of that broker on the disk. What will happen if the broker is restarted?

答案：D

解題說明：
Kafka replication mechanism makes it resilient to the scenarios where the broker lose data on disk, but can recover from replicating from other brokers. This makes Kafka amazing!


問題 #31
You have a topic with four partitions. The application reads from it using two consumers in a single consumer group.
Processing is CPU-bound, and lag is increasing.
What should you do?

答案：A

解題說明：
If the application isCPU-boundandlagging, addingmore consumersto the group will allow betterparallel processing, especially since the topic has4 partitions, allowing up to 4 active consumers.
FromKafka Consumer Group Docs:
"Kafka achieves parallelism by distributing partitions across consumers in a group. Adding consumers helps reduce lag if partitions are underutilized."
* B may help but requires repartitioning and coordination.
* C or D affects how much data is polled, not how fast it's processed.
Reference:Kafka Consumer Concepts > Parallelism and Scaling


問題 #32
(You have a Kafka Connect cluster with multiple connectors deployed.
One connector is not working as expected.
You need to find logs related to that specific connector to investigate the issue.
How can you find the connector's logs?)

答案：D

解題說明：
The official Apache Kafka Connect documentation explains that connectors run within the same worker JVM, and all logs are written through the worker's logging framework (Log4j or Log4j2). To isolate logs for a specific connector, Kafka Connect supports connector-specific logging contexts, which can be routed to separate log files using logging configuration.
By modifying the log4j.properties (or log4j2.xml) file to define a dedicated logger and appender for the connector's package or class name, you can direct logs from that connector to a separate file. This is the recommended and documented approach for debugging individual connectors in a shared Connect cluster.
Option A is incorrect because there is no generic "enable connector context" switch. Option B may increase verbosity but does not isolate logs per connector. Option D is false; Kafka Connect explicitly supports connector-level log separation through logging configuration.
Therefore, the correct approach is to configure a dedicated log appender for the specific connector.


問題 #33
By default, which replica will be elected as a partition leader? (select two)

答案：A,B

解題說明：
Preferred leader is a broker that was leader when topic was created. It is preferred because when partitions are first created, the leaders are balanced between brokers. Otherwise, any of the in-sync replicas (ISR) will be elected leader, as long as unclean.leader.election=false (by default)


問題 #34
......

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