Practice Example For Word Count (1.1.1.4) - Cloud Applications: MapReduce, Spark, and Apache Kafka
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Example for Word Count

Practice - Example for Word Count - 1.1.1.4

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the purpose of the Map phase in MapReduce?

💡 Hint: Think about how data is divided.

Question 2 Easy

In which phase does data get sorted by keys?

💡 Hint: This phase comes after the Map phase.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does the MapReduce framework primarily handle?

Real-time data processing
Batch data processing
Both real-time and batch processing

💡 Hint: Think about the nature of the operations it performs.

Question 2

True or False: The Reduce phase is responsible for emitting intermediate key-value pairs.

True
False

💡 Hint: Consider what each phase's operations achieve.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

How would you design a MapReduce job that processes sentiment analysis data from customer reviews?

💡 Hint: Consider the input data types and how they relate to sentiments.

Challenge 2 Hard

Can you implement a MapReduce job that not only counts words but also tracks their position in a document?

💡 Hint: Think about how you can structure the emitted key-value pairs.

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