Practice Spark Applications: A Unified Ecosystem For Diverse Workloads (2.3)
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Spark Applications: A Unified Ecosystem for Diverse Workloads

Practice - Spark Applications: A Unified Ecosystem for Diverse Workloads

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does RDD stand for, and what is its primary purpose in Spark?

💡 Hint: Think about what RDD helps maintain in the face of failures.

Question 2 Easy

Name one library in Spark that allows working with structured data.

💡 Hint: Remember the SQL concept related to databases.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does RDD stand for?

A) Random Data Distribution
B) Resilient Distributed Dataset
C) Rapid Data Deployment

💡 Hint: Focus on resilience and distribution concepts.

Question 2

True or False: Spark Streaming processes data in real-time using a micro-batching approach.

True
False

💡 Hint: Consider how streaming versus traditional processing works.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a small Spark application that uses at least two libraries (e.g., Spark SQL and MLlib) to process data and derive insights.

💡 Hint: Think about how you would extract insights from a dataset while leveraging SQL queries to transform data and machine learning models to predict outcomes.

Challenge 2 Hard

In a scenario where data may not fit into memory, explain how you would manage RDDs to optimize performance.

💡 Hint: Consider Spark's flexibility in handling large datasets and how to balance memory usage and computational efficiency.

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Reference links

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