Practice Stream Processing with Apache Kafka and Spark Streaming - 5.2 | Chapter 5: IoT Data Engineering and Analytics — Detailed Explanation | IoT (Internet of Things) Advance
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5.2 - Stream Processing with Apache Kafka and Spark Streaming

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the primary purpose of Apache Kafka?

💡 Hint: Think about how data flows in IoT scenarios.

Question 2

Easy

What does Spark Streaming process?

💡 Hint: Consider the processing method in real-time analytics.

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 aspect of Apache Kafka ensures that data is never lost?

  • High Scalability
  • Durability
  • Micro-batching

💡 Hint: Think about the importance of data integrity.

Question 2

True or False: Spark Streaming processes data in large batches instead of micro-batches.

  • True
  • False

💡 Hint: Recall the definition of micro-batching.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a hypothetical IoT system that utilizes both Kafka and Spark Streaming to monitor and respond to environmental conditions. What would be the architecture, and how would data flow through the system?

💡 Hint: Sketch a flow diagram to visualize the data movement.

Question 2

Discuss the potential challenges when implementing Kafka and Spark Streaming in a critical real-time system. How would you mitigate these challenges?

💡 Hint: Consider real-world examples where these technologies faced issues.

Challenge and get performance evaluation