Practice Example for Word Count - 1.1.2.5 | Week 8: Cloud Applications: MapReduce, Spark, and Apache Kafka | Distributed and Cloud Systems Micro Specialization
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1.1.2.5 - Example for Word Count

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What are the three main phases of MapReduce?

πŸ’‘ Hint: Think about the process used to handle data in big data applications.

Question 2

Easy

What does a mapper produce in the Map phase?

πŸ’‘ Hint: What does the mapper do with its input data?

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 Map phase do?

  • It groups intermediate values
  • It processes input data into key-value pairs
  • It summarizes final results

πŸ’‘ Hint: Think about the first step in the MapReduce process.

Question 2

Is the Shuffle and Sort phase necessary for MapReduce?

  • True
  • False

πŸ’‘ Hint: Consider if each phase serves a purpose in the overall process.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a MapReduce job to analyze sales data for a company. How would you structure the Map and Reduce phases?

πŸ’‘ Hint: Think about how to break down sales records into manageable pieces.

Question 2

Explain how MapReduce can handle millions of records effectively. What are its strengths?

πŸ’‘ Hint: Consider the distributed nature of the model and what that implies.

Challenge and get performance evaluation