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Confluent CCDAK Exam Syllabus Topics:

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:

1. What is accomplished by producing data to a topic with a message key?

A) Kafka brokers allow you to add more partitions to a given topic, without impacting the data flow for existing keys.
B) Consumers can filter messages in real time based on the message key without processing unrelated messages.
C) Messages with the same key are routed to a deterministically selected partition, enabling order guarantees within that partition.
D) It provides a mechanism for encrypting messages at the partition level to ensure secure data transmission.

2. (You create an Orders topic with 10 partitions.
The topic receives data at high velocity.
Your Kafka Streams application initially runs on a server with four CPU threads.
You move the application to another server with 10 CPU threads to improve performance.
What does this example describe?)

A) Vertical Scaling
B) Plain Scaling
C) Horizontal Scaling
D) Scaling Out

3. You need to set alerts on key broker metrics to trigger notifications when the cluster is unhealthy.
Which are three minimum broker metrics to monitor?
(Select three.)

A) kafka.controller:type=KafkaController,name=LastCommittedRecordOffset
B) kafka.controller:type=KafkaController,name=ActiveControllerCount
C) kafka.controller:type=KafkaController,name=TopicsToDeleteCount
D) kafka.controller:type=ControllerStats,name=UncleanLeaderElectionsPerSec
E) kafka.controller:type=KafkaController,name=OfflinePartitionsCount

4. (You want to enrich the content of a topic by joining it with key records from a second topic.
The two topics have a different number of partitions.
Which two solutions can you use?
Select two.)

A) Use a KStream-KTable join; Kafka Streams will automatically repartition the topics to satisfy the co- partitioning constraint.
B) Use a GlobalKTable for one of the topics where data does not change frequently and use a KStream- GlobalKTable join.
C) Create as many Kafka Streams application instances as the maximum number of partitions of the two topics and use a KStream-KTable join.
D) Repartition one topic to a new topic with the same number of partitions as the other topic (co- partitioning constraint) and use a KStream-KTable join.

5. (You are experiencing low throughput from a Java producer.
Kafka producer metrics show a low I/O thread ratio and low I/O thread wait ratio.
What is the most likely cause of the slow producer performance?)

A) There is a bad data link layer (Layer 2) connection from the producer to the cluster.
B) Compression is enabled.
C) The producer code has an expensive callback function.
D) The producer is sending large batches of messages.

Solutions: