Practice Examples of MapReduce Workflow (Detailed) - 1.7 | Week 8: Cloud Applications: MapReduce, Spark, and Apache Kafka | Distributed and Cloud Systems Micro Specialization
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1.7 - Examples of MapReduce Workflow (Detailed)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does the Map phase do in MapReduce?

πŸ’‘ Hint: Think about what the first step of MapReduce is responsible for.

Question 2

Easy

What do reducers do in MapReduce?

πŸ’‘ Hint: Focus on how we combine data at the end.

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 phase follows the Map phase in MapReduce?

  • Reduce
  • Shuffle and Sort
  • Input

πŸ’‘ Hint: It's all about organizing your data before the final step.

Question 2

True or False: MapReduce can only be used for real-time data processing.

  • True
  • False

πŸ’‘ Hint: Consider the main characteristic of the MapReduce workflow.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a MapReduce job to process large volumes of log files, counting unique IP addresses visiting a site.

πŸ’‘ Hint: Think about how to structure logs and what to emit.

Question 2

How would you alter your approach if you need real-time processing instead of batch processing?

πŸ’‘ Hint: Explore tools designed for real-time analytics.

Challenge and get performance evaluation