callicon +1 210 504 8191
whatsAppIcon +1 210 415 9856
emailIcon info@koenig-solutions.com
koenig-logo
Login
whatsAppIcon +1 210 415 9856
phoneIcon +1 210 504 8191
koenig-logo
All Courses

Apache Kafka Quiz Questions and Answers

Answer :
  • 5

Explanation :

If a single broker can store 2 TB of data, then the minimum cluster size required to retain 10 TB of data is 5 brokers. With a replication factor of 2, the same cluster needs to contain at least 10 brokers.2. < 2 > Which of the following factors should be considered while determining the appropriate size for a Kafka cluster?A) Disk capacityB) CPU capacityC) Network capacityD) All of the aboveAnswer: D) All of the aboveExplanation: The appropriate size for a Kafka cluster is determined by several factors, including disk capacity, replica capacity per broker, CPU capacity, and network capacity.3. < 3 > What is the purpose of Apache ZooKeeper in a Kafka cluster?A) To store metadata for the brokersB) To store messages in the clusterC) To manage the replication of dataD) To handle requests from clientsAnswer: A) To store metadata for the brokersExplanation: Apache ZooKeeper is used by Kafka for storing metadata for the brokers.4. < 4 > Which of the following is a practical matter covered in the book "Kafka: The Definitive Guide "?A) Kafka's design principlesB) Kafka's reliability guaranteesC) How to install and configure KafkaD) Kafka's delightful architecture detailsAnswer: C) How to install and configure KafkaExplanation: The book "Kafka: The Definitive Guide " covers practical matters such as how to install and configure Kafka.5. < 5 > What is the replication factor in a Kafka cluster?A) The number of different brokers a single partition is copied toB) The number of partitions in a topicC) The number of messages produced by a producerD) The number of consumers in a consumer groupAnswer: A) The number of different brokers a single partition is copied toExplanation: The replication factor in a Kafka cluster refers to the number of different brokers a single partition is copied to.6. < 6 > Why is it important to understand Kafka's design and internals?A) It is a fun read for those interested in distributed systemsB) It is incredibly useful for those
Answer :
  • At-least-once delivery may result in duplicate messages, while exactly-once delivery ensures that each message is processed only once.

Explanation :

At-least-once delivery guarantees that each message will be delivered at least once, but may result in duplicate messages in case of failures. Exactly-once delivery ensures that each message is processed only once, but requires additional coordination between the producer and consumer.
Answer :
  • <p>4000</p>

Explanation :

While there is no hard limit on the number of partitions per broker in a Kafka cluster, it is generally recommended to keep the number of partitions per broker below 1000. This is because having too many partitions per broker can lead to increased overhead and decreased performance.
Answer :
  • Decreasing the replication factor of the topic

Explanation :

Decreasing the replication factor of the topic does not directly improve producer performance. It is recommended to increase the batch size of messages produced, use compression for messages produced, or increase the number of producer instances to improve producer performance.
Answer :
  • Memory capacity

Explanation :

While memory capacity is important for the performance of Kafka brokers, it is not a factor to consider when determining the appropriate size for a Kafka cluster. The key factors to consider are disk capacity, replica capacity per broker, CPU capacity, and network capacity.
Answer :
  • To keep track of the last consumed message by a consumer

Explanation :

The offset is a unique identifier assigned to each message in a partition. It is used to keep track of the last consumed message by a consumer in a consumer group, so that the consumer can resume consuming from where it left off in case of failure or rebalancing.
Answer :
  • Enabling compression

Explanation :

Enabling compression can significantly reduce Kafka's disk usage by compressing messages before they are stored on disk. Increasing the retention period, decreasing the number of partitions, and increasing the replication factor can all increase disk usage.
Answer :
  • To control the minimum number of bytes that must be available for a fetch request to be made

Explanation :

The fetch.min.bytes configuration in Kafka consumer is used to control the minimum number of bytes that must be available for a fetch request to be made. This helps in reducing the number of small fetch requests and improving the efficiency of the consumer.
Answer :
  • To distribute messages within a topic across multiple Kafka brokers

Explanation :

Partitioning is the process of dividing a topic into multiple partitions, each of which can be stored on a different Kafka broker. This allows for parallel processing of messages within a topic, and also provides fault tolerance in case of broker failures.
Answer :
  • Increasing the batch size of messages fetched by the consumer

Explanation :

Increasing the batch size of messages fetched by the consumer is a recommended approach for improving Kafka consumer performance. This allows the consumer to fetch more messages in a single request, reducing the overhead of network communication.