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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Stream Processing with Apache Kafka and Spark Streaming

5.2 - Stream Processing with Apache Kafka and Spark Streaming

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Practice Questions

Test your understanding with targeted questions

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.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

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.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

Challenge 2 Hard

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.

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