熱門的CCDAK學習指南，由Confluent權威專家撰寫

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Confluent CCDAK Exam Overview:

Certification Vendor:	Confluent
Exam Name:	Confluent Certified Developer for Apache Kafka Certification Examination
Exam Number:	CCDAK
Certificate Validity Period:	3 years
Exam Format:	Multiple Choice (Multiple Answers), Multiple Choice (Single Answer)
Exam Price:	$150 USD
Available Languages:	English
Passing Score:	Approximately 60%
Real Exam Qty:	60
Exam Duration:	90 minutes
Related Certifications:	Confluent Certified Administrator for Apache Kafka (CCAAK)
Sample Questions:	Confluent CCDAK Sample Questions
Exam Way:	Online proctored exam (Pearson VUE) or in-person testing center
Pre Condition:	Recommended: 6+ months of hands-on experience with Apache Kafka and Confluent Platform. Familiarity with distributed systems concepts is strongly recommended.
Official Syllabus URL:	https://www.confluent.io/certification/

>> CCDAK學習指南 <<

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Confluent CCDAK 認證考試面向的是想要展示自己在 Kafka 開發和 Confluent 平台方面專業知識的開發人員。該認證考試專為具有堅實的 Java 編程語言、Kafka 架構和使用 Confluent 平台進行 Kafka 開發的開發人員而設計。這對於希望通過展示自己在 Kafka 開發方面的技能和知識來提高職業前景的開發人員來說是理想的認證考試。

最新的 Confluent Certified Developer CCDAK 免費考試真題 (Q86-Q91):

問題 #86
A Zookeeper ensemble contains 5 servers. What is the maximum number of servers that can go missing and the ensemble still run?

A. 0
B. 1
C. 2
D. 3

答案：B

解題說明：
majority consists of 3 zk nodes for 5 nodes zk cluster, so 2 can fail

問題 #87
What's is true about Kafka brokers and clients from version 0.10.2 onwards?

A. A newer client can't talk to a newer broker, but an older client can talk to a newer broker
B. Clients and brokers must have the exact same version to be able to communicate
C. A newer client can talk to a newer broker, but an older client cannot talk to a newer broker
D. A newer client can talk to a newer broker, and an older client can talk to a newer broker

答案：D

解題說明：
Kafka's new bidirectional client compatibility introduced in 0.10.2 allows this. Read more herehttps://www.
confluent.io/blog/upgrading-apache-kafka-clients-just-got-easier/

問題 #88
Which statement is true about how exactly-once semantics (EOS) work in Kafka Streams?

A. Kafka Streams disables log compaction on internal changelog topics to preserve all state changes for potential recovery.
B. EOS in Kafka Streams is implemented by creating a separate Kafka topic for deduplication of all messages processed by the application.
C. EOS in Kafka Streams relies on transactional producers to atomically commit state updates to changelog topics and output records to Kafka.
D. Kafka Streams provides EOS by periodically checkpointing state stores and replaying changelogs to recover only unprocessed messages during failure.

答案：C

解題說明：
Kafka Streams uses transactional producers to guarantee exactly-once semantics (EOS). This ensures that both the output records and state store updates are committed atomically, avoiding duplication or partial writes.
From Kafka Streams Documentation > Processing Guarantees:
"Kafka Streams leverages Kafka's transactional APIs to commit the output records and internal state updates as a single atomic unit, thereby providing exactly-once semantics." Option A is incorrect because log compaction is not disabled for EOS.
Option C incorrectly describes a checkpointing system Kafka Streams does not use.
Option D refers to deduplication, which is not how EOS is achieved in Streams.
Reference: Kafka Streams Processing Guarantees

問題 #89
(You are building real-time streaming applications using Kafka Streams.
Your application has a custom transformation.
You need to define custom processors in Kafka Streams.
Which tool should you use?)

A. Kafka Streams Domain Specific Language (DSL)
B. TopologyTestDriver
C. Kafka Streams Custom Transformation Language
D. Processor API

答案：D

解題說明：
The Apache Kafka Streams documentation clearly distinguishes between the Kafka Streams DSL and the Processor API. While the DSL is designed for common stream processing operations such as filtering, mapping, joining, and aggregations, it does not support fully custom processing logic.
For use cases that require custom transformations, fine-grained control over record processing, access to headers, timestamps, state stores, and punctuation, Kafka Streams provides the Processor API. This API allows developers to implement custom Processor, Transformer, or ValueTransformer classes and explicitly define the processing topology.
Option A (TopologyTestDriver) is a testing utility, not a development API. Option C (DSL) is higher-level and not suitable for advanced custom logic. Option D does not exist in Kafka.
Therefore, the correct and officially supported approach for defining custom processors in Kafka Streams is to use the Processor API.

問題 #90
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?

A. Increase the max.poll.records property of consumers.
B. Add more partitions to the topic to increase the level of parallelism of the processing.
C. Add more consumers to increase the level of parallelism of the processing.
D. Decrease the max.poll.records property of consumers.

答案：C

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 #91
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