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| Certification Vendor: | Confluent |
|---|---|
| Exam Name: | Confluent Certified Developer for Apache Kafka Certification Examination |
| Exam Number: | CCDAK |
| Related Certifications: | Confluent Certified Administrator for Apache Kafka (CCAAK) |
| Exam Price: | $150 USD |
| Real Exam Qty: | 60 |
| Exam Format: | Multiple Choice (Single Answer), Multiple Choice (Multiple Answers) |
| Available Languages: | English |
| Exam Duration: | 90 minutes |
| Passing Score: | Approximately 60% |
| Certificate Validity Period: | 3 years |
| 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/ |
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The Confluent Certified Developer for Apache Kafka Certification Examination certification is an opportunity for developers to demonstrate their understanding of Kafka and its ecosystem components, as well as their hands-on experience in building Kafka-based applications. Confluent Certified Developer for Apache Kafka Certification Examination certification exam validates the candidate's Kafka knowledge, skillset, and ability to develop solutions that solve real-world Kafka use cases. Moreover, the CCDAK certification is recognized worldwide, making it a valuable credential that can help software developers secure their next Kafka development role.
The CCDAK Certification Exam is a comprehensive and globally recognized certification program that validates an individual's knowledge and skills in Apache Kafka technology. It is designed for developers who work with Kafka and want to demonstrate their expertise in the field. Achieving the certification is a valuable asset for both individuals and organizations, as it ensures that developers have the necessary skills to develop and maintain Kafka-based applications.
NEW QUESTION # 49
You have a Kafka client application that has real-time processing requirements.
Which Kafka metric should you monitor?
Answer: C
Explanation:
For real-time applications, the key metric to monitor is consumer lag - the difference between the latest offset on the broker and the last committed offset by the consumer.
From Kafka Monitoring Guide:
"Consumer lag is the most important metric for real-time applications. It tells you how far behind the consumer is from the latest data in Kafka." B relates to replication, not client responsiveness.
C tracks group membership stability, not data delay.
D tracks input throughput, not processing latency.
Reference: Kafka Operations > Monitoring > Consumer Lag
NEW QUESTION # 50
(You create a topic with five partitions.
What can you assume about messages read from that topic by a single consumer group?)
Answer: C
Explanation:
The Apache Kafka documentation explains that Kafka's parallelism model is based on topic partitions and consumer groups. Within a single consumer group, each partition can be assigned to at most one consumer at a time. As a result, the maximum level of parallelism for a consumer group is equal to the number of partitions in the topic.
In this scenario, the topic has five partitions, which means that up to five consumers in the same consumer group can actively consume data in parallel. If more than five consumers are added, the extra consumers will remain idle because there are no additional partitions to assign.
Option B is incorrect because Kafka does not enforce equal message consumption across partitions; message distribution depends on producers and partitioning strategy. Option C is false because partitions may be hosted on different brokers, and consumers fetch data from multiple brokers. Option D is incorrect because a single partition cannot be consumed by multiple consumers within the same group simultaneously.
Therefore, the only valid assumption is that a maximum of five consumers can actively consume messages in the same consumer group.
NEW QUESTION # 51
A consumer has auto.offset.reset=latest, and the topic partition currently has data for offsets going from 45 to 2311. The consumer group never committed offsets for the topic before. Where will the consumer read from?
Answer: A
Explanation:
Latest means that data retrievals will start from where the offsets currently end
NEW QUESTION # 52
A consumer wants to read messages from partitions 0 and 1 of a topic topic1. Code snippet is shown below.
consumer.subscribe(Arrays.asList("topic1"));
List<TopicPartition> pc = new ArrayList<>();
pc.add(new PartitionTopic("topic1", 0));
pc.add(new PartitionTopic("topic1", 1));
consumer.assign(pc);
Answer: A
Explanation:
subscribe() and assign() cannot be called by the same consumer, subscribe() is used to leverage the consumer group mechanism, while assign() is used to manually control partition assignment and reads assignment
NEW QUESTION # 53
You want to perform table lookups against a KTable everytime a new record is received from the KStream.
What is the output of KStream-KTable join?
Answer: D
Explanation:
Here KStream is being processed to create another KStream.
NEW QUESTION # 54
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