MCQs on Producing and Consuming Messages | Apache Kafka MCQs Questions

Mastering the intricacies of Apache Kafka requires a strong understanding of its message-producing and consuming mechanisms. These Apache Kafka MCQs Questions delve into essential topics like the Kafka Producer and Consumer APIs, group coordination, offsets management, and schema registry. This set of 30 multiple-choice questions covers key aspects such as asynchronous and synchronous messaging, commit strategies, and message serialization. Whether you’re preparing for a Kafka certification or aiming to enhance your expertise, these MCQs will test your knowledge and help solidify critical concepts required for managing Kafka-based distributed systems effectively.

MCQs

1. Kafka Producer API and Configuration

1. What is the primary role of a Kafka Producer?
   a) To consume messages from topics
   b) To produce messages and send them to Kafka topics
   c) To manage consumer offsets
   d) To create and delete topics
2. Which configuration in the Kafka Producer controls the acknowledgment of messages?
   a) acks
   b) key.serializer
   c) compression.type
   d) value.deserializer
3. What is the default partitioning strategy used by Kafka Producer?
   a) Round-robin
   b) Hashing
   c) Random selection
   d) Key-based partitioning
4. Which API method is used to send a message asynchronously in Kafka Producer?
   a) sendSync()
   b) send()
   c) produce()
   d) dispatch()
5. What does the linger.ms configuration control in Kafka Producer?
   a) The maximum time to wait before sending a batch
   b) The delay before a consumer starts reading
   c) The time for a producer to reattempt delivery
   d) The acknowledgment delay
6. Which Kafka Producer configuration affects message compression?
   a) compression.type
   b) max.request.size
   c) acks
   d) batch.size

2. Kafka Consumer API and Group Coordination

7. In Kafka, what is a consumer group?
   a) A group of producers sending messages to a single topic
   b) A set of consumers working together to consume messages
   c) A cluster of Kafka brokers
   d) A set of partitions within a topic
8. Which API method is used to poll messages from a Kafka topic?
   a) poll()
   b) consume()
   c) fetch()
   d) retrieve()
9. How does Kafka achieve high availability in consumer groups?
   a) By duplicating messages across topics
   b) By distributing partitions among group members
   c) By replicating offsets
   d) By using synchronous processing
10. What happens when a new consumer joins a consumer group?
    a) All existing consumers stop consuming
    b) Partitions are rebalanced among the group members
    c) The new consumer is assigned all partitions
    d) The consumer waits until the group is full
11. Which configuration specifies the consumer group ID?
    a) group.id
    b) auto.offset.reset
    c) max.poll.records
    d) fetch.max.bytes
12. What is the role of the Kafka group coordinator?
    a) Managing producer acknowledgments
    b) Managing topic creation
    c) Coordinating consumer group rebalancing
    d) Handling message serialization

3. Asynchronous vs Synchronous Messaging

13. What is an advantage of asynchronous messaging in Kafka?
    a) Lower latency
    b) Simpler message handling
    c) Guaranteed message delivery
    d) Fewer retries
14. How does synchronous messaging handle acknowledgments?
    a) Waits for acknowledgment before sending the next message
    b) Buffers acknowledgments for batch processing
    c) Ignores acknowledgments completely
    d) Sends acknowledgments asynchronously
15. What is a potential downside of synchronous messaging in Kafka?
    a) Increased latency
    b) Message duplication
    c) Reduced fault tolerance
    d) Inability to handle large batches
16. In which scenario is asynchronous messaging preferred in Kafka?
    a) When latency is critical
    b) When data consistency is required
    c) When high throughput is needed
    d) When minimal retries are allowed
17. Which API call enables asynchronous message production in Kafka?
    a) send()
    b) sendAsync()
    c) produce()
    d) poll()
18. Which messaging model is more efficient for batch processing in Kafka?
    a) Synchronous messaging
    b) Asynchronous messaging
    c) Sequential messaging
    d) Real-time messaging

4. Offsets, Commit Strategies, and Rebalancing

19. What is the role of an offset in Kafka?
    a) To track the progress of consumed messages
    b) To configure the topic replication factor
    c) To store producer acknowledgments
    d) To manage message serialization
20. Which offset reset policy starts consuming from the earliest message?
    a) auto.offset.reset=latest
    b) auto.offset.reset=earliest
    c) auto.offset.reset=default
    d) auto.offset.reset=none
21. What does committing an offset in Kafka indicate?
    a) The producer has sent a message
    b) The broker has acknowledged a message
    c) The consumer has processed the message
    d) The topic has been updated
22. What happens during a consumer group rebalance?
    a) Partitions are reassigned to consumers
    b) Brokers are added to the cluster
    c) Producers start producing duplicate messages
    d) Topics are deleted
23. Which method is used for manual offset commits in Kafka?
    a) commitSync()
    b) commitOffset()
    c) manualCommit()
    d) offsetCommit()
24. What is an advantage of committing offsets asynchronously?
    a) Higher throughput
    b) Reduced fault tolerance
    c) Increased message duplication
    d) Easier debugging

5. Schema Registry and Message Serialization

25. What is the purpose of a schema registry in Kafka?
    a) Managing schemas for topic partitions
    b) Enforcing data consistency and compatibility
    c) Storing offsets for consumer groups
    d) Handling producer acknowledgments
26. Which serialization format is commonly used with the Kafka schema registry?
    a) Avro
    b) JSON
    c) Parquet
    d) ORC
27. What is the role of a serializer in Kafka?
    a) Converting data into bytes for transmission
    b) Encrypting messages
    c) Managing topic replication
    d) Compressing data
28. Which Kafka configuration specifies the key serializer?
    a) key.serializer
    b) value.serializer
    c) compression.type
    d) producer.key
29. How does schema evolution work with the Kafka schema registry?
    a) By supporting schema changes without breaking compatibility
    b) By storing only the latest schema version
    c) By discarding older schemas
    d) By creating new topics for each schema version
30. Which component ensures compatibility between producers and consumers in Kafka?
    a) Schema registry
    b) Consumer group coordinator
    c) Topic manager
    d) Zookeeper

Answers