Practice Distributed (2.1.2) - Cloud Applications: MapReduce, Spark, and Apache Kafka
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Distributed

Practice - Distributed - 2.1.2

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What are the two main phases of MapReduce?

💡 Hint: Think about how data is processed step by step.

Question 2 Easy

What does RDD stand for in Apache Spark?

💡 Hint: What is the term for Spark's core data structure?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What programming model does MapReduce follow?

Sequential processing
Batch processing
Real-time processing

💡 Hint: Think about how MapReduce handles data over time.

Question 2

True or False: Apache Spark only processes data from HDFS.

True
False

💡 Hint: Consider the versatility of Spark's data sources.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design an example application that uses MapReduce for processing e-commerce transaction logs. Describe the steps involved.

💡 Hint: Focus on how you would structure and process the transaction logs.

Challenge 2 Hard

Discuss the trade-offs between using MapReduce and Spark for a machine learning application that requires iterative training.

💡 Hint: Compare their processing speeds and I/O operations.

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Reference links

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