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Confluent CCDAK (Confluent Certified Developer for Apache Kafka) Certification Exam is a globally recognized certification exam that tests the expertise of developers in Apache Kafka. Apache Kafka is an open-source distributed event streaming platform that is widely used by companies for building real-time data pipelines and streaming applications. The CCDAK exam is designed to test the knowledge and skills of developers in building and managing Kafka-based applications.

The CCDAK Certification Exam is conducted by Confluent, the company that provides a commercial distribution of Apache Kafka. CCDAK exam is designed to test the proficiency of developers in various aspects of Kafka, including installation and configuration, data ingestion and processing, stream processing, and security. CCDAK exam is designed to be challenging and comprehensive, and passing it requires a solid understanding of Kafka and its various components.

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q57-Q62):

NEW QUESTION # 57
A kafka topic has a replication factor of 3 and min.insync.replicas setting of 2. How many brokers can go down before a producer with acks=1 can't produce?

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

Answer: D

Explanation:
min.insync.replicas does not impact producers when acks=1 (only when acks=all)

NEW QUESTION # 58
What are two examples of performance metrics?
(Select two.)

A. Time of last failed login
B. Number of active users
C. Number of active user sessions
D. total-login-attempts
E. incoming-byte-rate
F. fetch-rate

Answer: E,F

Explanation:
* fetch-rate: Measures how frequently consumers fetch data - critical for monitoring throughput.
* incoming-byte-rate: Shows how much data is being written to the broker per second - a key producer-side metric.
FromKafka JMX Metrics Guide:
"fetch-rate, incoming-byte-rate, request-latency are key performance metrics for producers and consumers."
* B, C, E, and F areapplication-layer business metrics, not Kafka performance metrics.
Reference:Kafka Monitoring > JMX Metrics

NEW QUESTION # 59
If I produce to a topic that does not exist, and the broker setting auto.create.topic.enable=true, what will happen?

A. Kafka will automatically create the topic with num.partitions=#of brokers and replication.factor=3
B. Kafka will automatically create the topic with 1 partition and 1 replication factor
C. Kafka will automatically create the topic with the indicated producer settings num.partitions and default.replication.factor
D. Kafka will automatically create the topic with the broker settings num.partitions and default.replication.factor

Answer: D

Explanation:
The broker settings comes into play when a topic is auto created

NEW QUESTION # 60
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?

A. it will crash
B. offset 45
C. offset 0
D. offset 2311

Answer: D

Explanation:
Latest means that data retrievals will start from where the offsets currently end

NEW QUESTION # 61
We have a store selling shoes. What dataset is a great candidate to be modeled as a KTable in Kafka Streams?

A. The transaction stream
B. Items returned
C. Inventory contents right now
D. Money made until now

Answer: B,D

Explanation:
Aggregations of stream are stored in table, whereas Streams must be modeled as a KStream to avoid data explosion

NEW QUESTION # 62
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