Apache Kafka MCQs with answers Page - 5

Here, you will find a collection of MCQ questions on Apache Kafka. Go through these questions to enhance your preparation for upcoming examinations and interviews.

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A

Admin • 802.91K Points
Coach

Q. What type of storage does Kafka use to persist data?

  • (A) RAM
  • (B) MySQL database
  • (C) Log files on disk
  • (D) Cloud storage

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Admin • 802.91K Points
Coach

Q. Which property controls the maximum number of records returned in one poll?

  • (A) max.poll.records
  • (B) max.partition.fetch.bytes
  • (C) batch.size
  • (D) fetch.min.bytes

A

Admin • 802.91K Points
Coach

Q. How does Kafka handle backpressure?

  • (A) By slowing down producers
  • (B) By buffering messages in memory
  • (C) By using message compression
  • (D) By rejecting new producers

A

Admin • 802.91K Points
Coach

Q. Kafka messages are assigned which type of identifier?

  • (A) UUID
  • (B) Offset
  • (C) Index
  • (D) Label

A

Admin • 802.91K Points
Coach

Q. What happens if Kafka’s disk becomes full?

  • (A) Messages are stored in memory
  • (B) Kafka stops accepting new messages
  • (C) Old messages are deleted immediately
  • (D) Consumers are blocked

A

Admin • 802.91K Points
Coach

Q. How does Kafka scale horizontally?

  • (A) By increasing consumer buffer size
  • (B) By adding more partitions and brokers
  • (C) By upgrading JVM
  • (D) By compressing log files

A

Admin • 802.91K Points
Coach

Q. Kafka topic replication improves:

  • (A) Data redundancy and fault tolerance
  • (B) Producer speed
  • (C) Consumer load
  • (D) ZooKeeper performance

A

Admin • 802.91K Points
Coach

Q. Kafka can be used as a replacement for:

  • (A) File system
  • (B) Database
  • (C) Message queue system
  • (D) FTP server

A

Admin • 802.91K Points
Coach

Q. Which command lists all available Kafka topics?

  • (A) kafka-run-class.sh
  • (B) kafka-topics.sh --list
  • (C) kafka-console-consumer.sh --describe
  • (D) kafka-log-dirs.sh --status

A

Admin • 802.91K Points
Coach

Q. Kafka’s primary design goal is:

  • (A) Low latency and file compression
  • (B) High throughput and fault tolerance
  • (C) Database indexing
  • (D) Static content serving

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