Confluent CCAAK Exam With Confidence Using Practice Dumps

When sizing a ksqlDB cluster, the following factors are crucial:

A. Data Schema: Complex schemas may require more CPU/memory for serialization/deserialization.

B. Number of Queries: Each persistent query consumes system resources (CPU, memory).

C. Number of Partitions: Determines parallelism and state store scalability.

From Confluent documentation:

“Cluster capacity planning depends on schema complexity, query concurrency, and partition count.”

D → Incorrect: Encryption impacts producer/broker, not ksqlDB sizing directly.

E → Incorrect: Retention is managed by Kafka, not ksqlDB.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 7, p. 225–229

Confluent ksqlDB Documentation: Capacity Planning Guidelines

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For maximum throughput and lowest latency, the setting acks=0 allows the producer to send messages without waiting for any acknowledgment from the broker. This increases speed but at the cost of durability.

From Kafka documentation:

“acks=0: The producer does not wait for any acknowledgment from the broker. The message can be lost but offers the highest throughput.”

A → Correct: Maximizes throughput with no delivery guarantee.

B → Balanced option but not max throughput.

C → Offers strongest durability but lowest throughput.

D → Invalid configuration.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 5, p. 158–159

Apache Kafka Documentation: Producer Configs – acks

Kafka consumers in a consumer group consume partitions exclusively. With 4 partitions and only 2 consumers, each consumer is processing 2 partitions. To increase parallelism, more consumers can be added to the group (up to 4) so that each consumer handles fewer partitions, which reduces the lag.

From Kafka documentation:

“Increasing the number of consumers in a group increases parallelism and helps reduce lag, assuming there are enough partitions.”

A → Ineffective unless followed by rebalancing and consumer scaling.

B → Would create a separate group and not share load.

C → Not applicable; consumers don’t acknowledge messages like producers.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 4, p. 127–129

Apache Kafka Documentation: Consumer Group Behavior

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