Practice Example for Word Count - 1.1.1.4 | Week 8: Cloud Applications: MapReduce, Spark, and Apache Kafka | Distributed and Cloud Systems Micro Specialization
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1.1.1.4 - Example for Word Count

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the purpose of the Map phase in MapReduce?

πŸ’‘ Hint: Think about how data is divided.

Question 2

Easy

In which phase does data get sorted by keys?

πŸ’‘ Hint: This phase comes after the Map phase.

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 does the MapReduce framework primarily handle?

  • Real-time data processing
  • Batch data processing
  • Both real-time and batch processing

πŸ’‘ Hint: Think about the nature of the operations it performs.

Question 2

True or False: The Reduce phase is responsible for emitting intermediate key-value pairs.

  • True
  • False

πŸ’‘ Hint: Consider what each phase's operations achieve.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

How would you design a MapReduce job that processes sentiment analysis data from customer reviews?

πŸ’‘ Hint: Consider the input data types and how they relate to sentiments.

Question 2

Can you implement a MapReduce job that not only counts words but also tracks their position in a document?

πŸ’‘ Hint: Think about how you can structure the emitted key-value pairs.

Challenge and get performance evaluation