Practice Map Phase - 1.1.1 | Week 8: Cloud Applications: MapReduce, Spark, and Apache Kafka | Distributed and Cloud Systems Micro Specialization
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1.1.1 - Map Phase

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the primary purpose of the Mapper function in MapReduce?

πŸ’‘ Hint: Think about what happens in the first phase of MapReduce.

Question 2

Easy

What is an input split in the context of MapReduce?

πŸ’‘ Hint: Consider how data is prepared for 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 Mapper function do?

  • Generates final output
  • Processes input to generate intermediate output
  • Manages distributed task scheduling

πŸ’‘ Hint: Consider the role of the Mapper in the Map Phase.

Question 2

True or False: The output of the Mapper is directly written to a database.

  • True
  • False

πŸ’‘ Hint: Think about where the intermediate output goes.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a Mapper function for a dataset containing user reviews where you need to count the number of occurrences of various words. What output does your Mapper produce for the input 'Great product, great quality!'?

πŸ’‘ Hint: Remember to handle punctuation and case sensitivity.

Question 2

Explain how changing the input split size affects the performance of the Map Phase in a large dataset. What could be the ideal practices for input splitting?

πŸ’‘ Hint: Consider the trade-off between task management overhead and parallel processing efficiency.

Challenge and get performance evaluation