Practice Transformations (lazy Execution) (2.2.1) - Cloud Applications: MapReduce, Spark, and Apache Kafka
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Transformations (Lazy Execution)

Practice - Transformations (Lazy Execution)

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is lazy evaluation in Spark?

💡 Hint: Think about when Spark decides to perform calculations.

Question 2 Easy

Give an example of a narrow transformation.

💡 Hint: How does map work with RDDs?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does lazy execution in Spark allow?

Immediate execution of transformations
Building an execution plan before computation
Only executing narrow transformations

💡 Hint: Think about when Spark actually runs the code.

Question 2

True or False: Narrow transformations require shuffling data across the network.

True
False

💡 Hint: Consider what happens to data with narrow transformations.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Consider a dataset with millions of records. Describe the potential impact on performance if multiple wide transformations are used successively.

💡 Hint: Think about the cost of data transfers.

Challenge 2 Hard

Given a sample RDD containing sales data, outline a sequence of transformations that include both narrow and wide transformations while optimizing for performance.

💡 Hint: Always filter before you apply wide transformations.

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Reference links

Supplementary resources to enhance your learning experience.