Practice Programming Model: User-Defined Functions for Parallelism - 1.2 | Week 8: Cloud Applications: MapReduce, Spark, and Apache Kafka | Distributed and Cloud Systems Micro Specialization
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1.2 - Programming Model: User-Defined Functions for Parallelism

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does the Mapper function do?

πŸ’‘ Hint: Think about what happens at the start of data processing.

Question 2

Easy

In which phase do intermediate key-value pairs get sorted?

πŸ’‘ Hint: This phase occurs between the Map and Reduce 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 is the role of the Mapper function?

  • A. Aggregates values for a key
  • B. Transforms input records into intermediate pairs
  • C. Sorts pairs for the Reducer

πŸ’‘ Hint: Consider what the Mapper does to the input data.

Question 2

True or False: The Shuffle phase is managed by the user.

  • True
  • False

πŸ’‘ Hint: Think about who handles these operations.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a MapReduce job to analyze log files for user login counts, outlining the Mapper and Reducer functions.

πŸ’‘ Hint: Think about how you would collect and aggregate data.

Question 2

Discuss how fault tolerance is achieved in the MapReduce framework.

πŸ’‘ Hint: Consider the mechanisms in place for handling task failures.

Challenge and get performance evaluation