Practice Scalable (3.1.7) - Cloud Applications: MapReduce, Spark, and Apache Kafka
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Practice Questions

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Question 1 Easy

What are the three main phases of MapReduce?

💡 Hint: Think about the key steps involved in processing data.

Question 2 Easy

What does RDD stand for in Apache Spark?

💡 Hint: Focus on the fault tolerance characteristic of datasets.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What are the main phases of the MapReduce process?

Map
Shuffle
Reduce
Map
Shuffle and Sort
Reduce
Map
Combine
Reduce

💡 Hint: Recall the steps we discussed in class.

Question 2

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

True
False

💡 Hint: Think about the difference between Spark and traditional data processing methods.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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

💡 Hint: Consider the roles of producers and consumers in your design.

Challenge 2 Hard

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

💡 Hint: Think about how each operation alters the RDD at each step.

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