Practice Map Phase (1.1.1) - Cloud Applications: MapReduce, Spark, and Apache Kafka
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Map Phase

Practice - Map Phase

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the primary purpose of the Mapper function in MapReduce?

💡 Hint: Think about what happens in the first phase of MapReduce.

Question 2 Easy

What is an input split in the context of MapReduce?

💡 Hint: Consider how data is prepared for the Map Phase.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does the Mapper function do?

Generates final output
Processes input to generate intermediate output
Manages distributed task scheduling

💡 Hint: Consider the role of the Mapper in the Map Phase.

Question 2

True or False: The output of the Mapper is directly written to a database.

True
False

💡 Hint: Think about where the intermediate output goes.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a Mapper function for a dataset containing user reviews where you need to count the number of occurrences of various words. What output does your Mapper produce for the input 'Great product, great quality!'?

💡 Hint: Remember to handle punctuation and case sensitivity.

Challenge 2 Hard

Explain how changing the input split size affects the performance of the Map Phase in a large dataset. What could be the ideal practices for input splitting?

💡 Hint: Consider the trade-off between task management overhead and parallel processing efficiency.

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