Practice Message Passing (2.5.2.2.3) - Cloud Applications: MapReduce, Spark, and Apache Kafka
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Message Passing

Practice - Message Passing

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Practice Questions

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Question 1 Easy

What does MapReduce primarily allow for in distributed systems?

💡 Hint: Think about the two main phases.

Question 2 Easy

Define what Kafka is used for.

💡 Hint: Consider its role in message consumption.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main purpose of MapReduce?

Real-time data processing
Batch processing of large datasets
Data visualization

💡 Hint: Consider the nature of the processing.

Question 2

True or False: Spark performs all data processing on disk.

True
False

💡 Hint: Think about how data storage differs in Spark.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a system using MapReduce to analyze user logs from a web server. Describe each phase and how you would structure your Mapper and Reducer.

💡 Hint: Break it down by processing phases.

Challenge 2 Hard

How would you set up a Kafka cluster for a financial application that requires real-time transaction monitoring? Discuss strategies for partitioning and replication.

💡 Hint: Focus on scalability and reliability.

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