Practice Intermediate Output (1.1.1.3) - Cloud Applications: MapReduce, Spark, and Apache Kafka
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Intermediate Output

Practice - Intermediate Output

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does the Map phase in MapReduce do?

💡 Hint: Think about how data is split and transformed.

Question 2 Easy

What is an RDD?

💡 Hint: Consider what RDDs provide in terms of failure resilience.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does MapReduce primarily deal with?

Real-time data
Batch data
Streaming data

💡 Hint: Consider the nature of the processing being done.

Question 2

Apache Spark improves over MapReduce by using:

In-memory processing
Disk-based processing

💡 Hint: Think about the efficiency of data retrieval.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a MapReduce job for analyzing sales records. Outline the mapping and reducing logic.

💡 Hint: Think about how you can structure your keys and values effectively.

Challenge 2 Hard

How would you implement a data pipeline using Kafka to stream event logs from a web application to a storage solution?

💡 Hint: Consider the flow of data from producers to consumers.

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Reference links

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