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
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
Which configuration in the Kafka Producer controls the acknowledgment of messages? a) acks b) key.serializer c) compression.type d) value.deserializer
What is the default partitioning strategy used by Kafka Producer? a) Round-robin b) Hashing c) Random selection d) Key-based partitioning
Which API method is used to send a message asynchronously in Kafka Producer? a) sendSync() b) send() c) produce() d) dispatch()
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
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
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
Which API method is used to poll messages from a Kafka topic? a) poll() b) consume() c) fetch() d) retrieve()
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
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
Which configuration specifies the consumer group ID? a) group.id b) auto.offset.reset c) max.poll.records d) fetch.max.bytes
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
What is an advantage of asynchronous messaging in Kafka? a) Lower latency b) Simpler message handling c) Guaranteed message delivery d) Fewer retries
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
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
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
Which API call enables asynchronous message production in Kafka? a) send() b) sendAsync() c) produce() d) poll()
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
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
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
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
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
Which method is used for manual offset commits in Kafka? a) commitSync() b) commitOffset() c) manualCommit() d) offsetCommit()
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
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
Which serialization format is commonly used with the Kafka schema registry? a) Avro b) JSON c) Parquet d) ORC
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
Which Kafka configuration specifies the key serializer? a) key.serializer b) value.serializer c) compression.type d) producer.key
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
Which component ensures compatibility between producers and consumers in Kafka? a) Schema registry b) Consumer group coordinator c) Topic manager d) Zookeeper
Answers
QNo
Answer (Option with the text)
1
b) To produce messages and send them to Kafka topics
2
a) acks
3
d) Key-based partitioning
4
b) send()
5
a) The maximum time to wait before sending a batch
6
a) compression.type
7
b) A set of consumers working together to consume messages
8
a) poll()
9
b) By distributing partitions among group members
10
b) Partitions are rebalanced among the group members
11
a) group.id
12
c) Coordinating consumer group rebalancing
13
a) Lower latency
14
a) Waits for acknowledgment before sending the next message
15
a) Increased latency
16
c) When high throughput is needed
17
a) send()
18
b) Asynchronous messaging
19
a) To track the progress of consumed messages
20
b) auto.offset.reset=earliest
21
c) The consumer has processed the message
22
a) Partitions are reassigned to consumers
23
a) commitSync()
24
a) Higher throughput
25
b) Enforcing data consistency and compatibility
26
a) Avro
27
a) Converting data into bytes for transmission
28
a) key.serializer
29
a) By supporting schema changes without breaking compatibility