Practice Data Model: Topics, Partitions, and Offsets - 3.3 | Week 8: Cloud Applications: MapReduce, Spark, and Apache Kafka | Distributed and Cloud Systems Micro Specialization
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3.3 - Data Model: Topics, Partitions, and Offsets

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is a topic in Kafka?

πŸ’‘ Hint: Think about how information gets organized.

Question 2

Easy

What is the purpose of partitions in Kafka?

πŸ’‘ Hint: Consider how messages can be managed efficiently.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What defines a Kafka topic?

  • A unique identifier for messages
  • A logical grouping of messages
  • A method of data compression

πŸ’‘ Hint: Think about how messages are organized.

Question 2

True or False: The ordering of messages in Kafka is guaranteed across all partitions of a topic.

  • True
  • False

πŸ’‘ Hint: Consider how data is handled in separate segments.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a Kafka messaging structure for a news application that includes breaking news updates and comment threads.

πŸ’‘ Hint: Consider dynamic user engagement and the need for timely updates.

Question 2

Analyze the impact of a partition becoming unavailable due to a server failure. How does Kafka handle this situation?

πŸ’‘ Hint: Think about how redundancy functions in distributed systems.

Challenge and get performance evaluation