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[General] Correct Sample CCAAK Exam & Leader in Qualification Exams & Pass-Sure CC

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【General】 Correct Sample CCAAK Exam & Leader in Qualification Exams & Pass-Sure CC

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Confluent Certified Administrator for Apache Kafka Sample Questions (Q26-Q31):NEW QUESTION # 26
You are managing a cluster with a large number of topics, and each topic has a lot of partitions. A team wants to significantly increase the number of partitions for some topics.
Which parameters should you check before increasing the partitions?
  • A. Check the producer batch size and buffer size.
  • B. Check if acks=all is beina used.
  • C. Check if compression is being used.
  • D. Check the max open file count on brokers.
Answer: D
Explanation:
Each Kafka partition maps to multiple log segment files, and each segment results in open file descriptors on the broker. When the number of partitions increases significantly, it can exceed the OS-level limit for open files per broker process, leading to failures or degraded performance. Therefore, it is essential to check and possibly increase the ulimit -n (max open files) setting on the broker machines.

NEW QUESTION # 27
The Consumer property 'auto offset reset' determines what to do if there is no valid offset for a Consumer Group.
Which scenario is an example of a valid offset and therefore the 'auto.offset.reset' does NOT apply?
  • A. The Consumer offset is greater than the last offset in the partition (log end offset).
  • B. The Consumer offset is less than the smallest offset in the partition (log start offset).
  • C. When an offset points to a message that has been removed by compaction but is still within the current partition.offset range.
  • D. The Consumer Group started for the first time.
Answer: C
Explanation:
In this scenario, the offset itself is still valid, even though the record at that offset was compacted away. The consumer can continue consuming from the next available record. Therefore, auto.offset.reset does NOT apply, because there is a valid offset present.

NEW QUESTION # 28
You are managing a Kafka cluster with five brokers (broker id '0', '1','2','3','4') and three ZooKeepers. There are 100 topics, five partitions for each topic, and replication factor three on the cluster. Broker id '0' is currently the Controller, and this broker suddenly fails.
Which statements are correct? (Choose three.)
  • A. The Controller uses the epoch number to prevent a split brain scenario.
  • B. The Controller is responsible for reassigning partitions to the consumers in a Consumer Group.
  • C. The number of Controllers should always be equal to the number of brokers alive in the cluster.
  • D. Kafka uses ZooKeeper's ephemeral node feature to elect a controller.
  • E. The broker id is used as the epoch number to prevent a split brain scenario.
  • F. The Controller is responsible for electing Leaders among the partitions and replicas.
Answer: A,D,F
Explanation:
Kafka relies on ZooKeeper's ephemeral nodes to detect if a broker (controller) goes down and to elect a new controller.
The controller manages partition leadership assignments and handles leader election when a broker fails.
The epoch number ensures coordination and avoids outdated controllers acting on stale data.

NEW QUESTION # 29
A Kafka administrator notices that their consumers of Topic X are starting to fall behind. The administrator sees that Topic X has four partitions, and the consumer group has two consumers.
Which change can increase the performance of the Consumer Group?
  • A. Decrease the consumer acknowledgment property to increase throughput.
  • B. Increase the number of consumers in the consumer group.
  • C. Create a new consumer group for Topic X containing two (2) consumers.
  • D. Increase the partitions in Topic X.
Answer: B
Explanation:
With 4 partitions and only 2 consumers, some consumers are handling multiple partitions, which may cause lag if processing is slow. By increasing the number of consumers in the group (up to 4), Kafka can assign one partition per consumer, improving parallelism and throughput.

NEW QUESTION # 30
How can load balancing of Kafka clients across multiple brokers be accomplished?
  • A. Replicas
  • B. Connectors
  • C. Offsets
  • D. Partitions
Answer: D
Explanation:
Partitions are the primary mechanism for achieving load balancing in Kafka. When a topic has multiple partitions, Kafka clients (producers and consumers) can distribute the load across brokers hosting these partitions.

NEW QUESTION # 31
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