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Confluent CCDAK Certification Exam is an essential certification for developers who want to demonstrate their expertise in Kafka and related technologies. Confluent Certified Developer for Apache Kafka Certification Examination certification is designed to test the knowledge and skills of developers in Kafka and is recognized globally as a standard for Kafka developers. Developers who pass the exam can demonstrate their expertise in Kafka and can be confident in their skills and knowledge.
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The CCDAK exam is a comprehensive test that covers various aspects of the Kafka platform, including Kafka architecture, configuration, monitoring, performance tuning, and security. CCDAK examination measures one's ability to use Kafka to handle real-time data feeds, messaging, and stream processing. CCDAK Exam is designed to assess one's understanding of the platform and their ability to apply their knowledge to solve real-world problems.
NEW QUESTION # 17
What is ISR in Apache Kafka?
Answer: B
NEW QUESTION # 18
(You started a new Kafka Connect worker.
Which configuration identifies the Kafka Connect cluster that your worker will join?)
Answer: D
Explanation:
As documented in the official Apache Kafka Connect framework documentation, Kafka Connect workers form a logical cluster by using a Kafka consumer group. The configuration property that identifies this cluster is group.id.
All Kafka Connect workers configured with the same group.id automatically join the same Connect cluster.
Kafka's group coordination protocol is then used to distribute connector and task configurations among the workers, providing fault tolerance, scalability, and automatic rebalancing.
Option A (cluster.id) is a Kafka internal identifier used by brokers and is not configurable for Kafka Connect workers. Option B (worker.id) does not exist as a valid Kafka Connect configuration. Option D (connector.id) identifies individual connectors within a Connect cluster, not the worker cluster itself.
Therefore, the group.id property is the correct and officially documented configuration that determines which Kafka Connect cluster a worker belongs to.
NEW QUESTION # 19
A stream processing application is consuming from a topic with five partitions. You run three instances of the application. Each instance has num.stream.threads=5.
You need to identify the number of stream tasks that will be created and how many will actively consume messages from the input topic.
Answer: B
Explanation:
In Kafka Streams, the number of stream tasks = number of input partitions × num.stream.threads × number of instances, but only as many as the number of partitions can actively consume at once.
However, in this case, Kafka Streams assigns one task per partition, and because there are 5 partitions and 15 threads (3 instances × 5 threads), 15 tasks are created, and all 15 can be active depending on processing topology.
From Kafka Streams Developer Guide:
"Kafka Streams creates one task per input partition. If you increase the number of stream threads, it runs multiple tasks in parallel within a single instance." So, 15 stream tasks will be created and 15 will be actively consuming.
Reference: Apache Kafka Streams Documentation > Concepts > Tasks and Threads
NEW QUESTION # 20
Which SMTs is used to change the data type?
Answer: D
NEW QUESTION # 21
What exceptions may be caught by the following producer? (select two)
ProducerRecord<String, String> record =
new ProducerRecord<>("topic1", "key1", "value1");
try {
producer.send(record);
} catch (Exception e) {
e.printStackTrace();
}
Answer: C,D
Explanation:
These are the client side exceptions that may be encountered before message is sent to the broker, and before a future is returned by the .send() method.
NEW QUESTION # 22
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