Practice Example for Word Count - 1.1.3.3 | Week 8: Cloud Applications: MapReduce, Spark, and Apache Kafka | Distributed and Cloud Systems Micro Specialization
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1.1.3.3 - 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 what happens first in the MapReduce process.

Question 2

Easy

What type of data does a reducer receive?

πŸ’‘ Hint: Consider what grouping occurs before this stage.

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 do mappers do in the Map phase?

  • Group key-value pairs
  • Transform input into key-value pairs
  • Aggregate results

πŸ’‘ Hint: Recall the first step of MapReduce.

Question 2

True or False: The reduce phase can produce intermediate outputs.

  • True
  • False

πŸ’‘ Hint: Consider the role of reducers.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Create a MapReduce function for counting unique items in a list of strings. Demonstrate how it processes data through each phase.

πŸ’‘ Hint: Think about how you would represent input and output at each stage.

Question 2

Explain how you would optimize the MapReduce process for performance when dealing with a video analytics use case involving viewer counts per segment.

πŸ’‘ Hint: Focus on methods that reduce workload or speed up processing times.

Challenge and get performance evaluation