Practice Scalable - 3.1.7 | Week 8: Cloud Applications: MapReduce, Spark, and Apache Kafka | Distributed and Cloud Systems Micro Specialization
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3.1.7 - Scalable

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 key steps involved in processing data.

Question 2

Easy

What does RDD stand for in Apache Spark?

πŸ’‘ Hint: Focus on the fault tolerance characteristic of datasets.

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 are the main phases of the MapReduce process?

  • Map
  • Shuffle
  • Reduce
  • Map
  • Shuffle and Sort
  • Reduce
  • Map
  • Combine
  • Reduce

πŸ’‘ Hint: Recall the steps we discussed in class.

Question 2

True or False: Apache Spark processes data exclusively on disk.

  • True
  • False

πŸ’‘ Hint: Think about the difference between Spark and traditional data processing methods.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a Kafka-based application scenario to collect clickstream data from a web application. Describe the components involved.

πŸ’‘ Hint: Consider the roles of producers and consumers in your design.

Question 2

Implement an RDD processing pipeline in Spark that reads a large dataset and performs the following operations: filter, map, and reduce. Detail each step.

πŸ’‘ Hint: Think about how each operation alters the RDD at each step.

Challenge and get performance evaluation