Practice Machine Learning (batch Training) (1.3.6) - Cloud Applications: MapReduce, Spark, and Apache Kafka
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Machine Learning (Batch Training)

Practice - Machine Learning (Batch Training)

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the purpose of the Map phase in MapReduce?

💡 Hint: Think about the first steps in data processing.

Question 2 Easy

What does the Reduce phase do?

💡 Hint: Consider what the goal of summarizing data is.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the first step of the Map phase in MapReduce?

Data Input Processing
Data Output Writing
Intermediate Data Scattering

💡 Hint: Think about the type of work done at the beginning.

Question 2

True or False: The Shuffle phase is responsible for aggregating results.

True
False

💡 Hint: Think about the specific duties of each phase.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Consider a scenario where a node fails during the Shuffle phase. Discuss how MapReduce handles this failure and what implications it has for data integrity.

💡 Hint: Think about the mechanisms that allow MapReduce to manage nodes.

Challenge 2 Hard

Design a small MapReduce workflow for processing a large dataset related to customer transaction logs. Describe the steps involved from Map through to Reduce.

💡 Hint: Focus on the flow of data from one phase to another.

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Reference links

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