Practice Task Re-execution (1.5.1) - Cloud Applications: MapReduce, Spark, and Apache Kafka
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Task Re-execution

Practice - Task Re-execution

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What happens if a Map task fails during execution?

💡 Hint: Think about the role of the ApplicationMaster!

Question 2 Easy

Why is intermediate data durability important?

💡 Hint: Consider what happens to data when tasks fail.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What happens to a Map task that fails during execution?

It is removed from the job queue
It causes the job to fail
It is re-scheduled on another node

💡 Hint: Recall the role of the ApplicationMaster!

Question 2

True or False: If a node fails, the other tasks on it are automatically killed.

True
False

💡 Hint: Think about how fault tolerance aids task recovery.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You are tasked with designing a distributed processing system. Explain how you would incorporate fault tolerance mechanisms similar to MapReduce.

💡 Hint: Consider how existing systems deal with failures.

Challenge 2 Hard

Evaluate the trade-offs of implementing a robust fault tolerance system over a simpler, less reliable system for a big data project.

💡 Hint: Think about the long-term benefits versus initial implementation costs.

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Reference links

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