Practice Example For Word Count (1.1.3.2) - Cloud Applications: MapReduce, Spark, and Apache Kafka
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Example for Word Count

Practice - Example for Word Count - 1.1.3.2

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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 what happens first in the MapReduce process.

Question 2 Easy

What type of data does a reducer receive?

💡 Hint: Consider what grouping occurs before this stage.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What do mappers do in the Map phase?

Group key-value pairs
Transform input into key-value pairs
Aggregate results

💡 Hint: Recall the first step of MapReduce.

Question 2

True or False: The reduce phase can produce intermediate outputs.

True
False

💡 Hint: Consider the role of reducers.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Create a MapReduce function for counting unique items in a list of strings. Demonstrate how it processes data through each phase.

💡 Hint: Think about how you would represent input and output at each stage.

Challenge 2 Hard

Explain how you would optimize the MapReduce process for performance when dealing with a video analytics use case involving viewer counts per segment.

💡 Hint: Focus on methods that reduce workload or speed up processing times.

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