Practice - Real-time Data Pipelines (ETL)
Practice Questions
Test your understanding with targeted questions
What does ETL stand for in data processing?
💡 Hint: Think about the process of moving data.
Name a key feature of Apache Kafka.
💡 Hint: Consider its performance in handling messages.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What is the primary purpose of MapReduce?
💡 Hint: Focus on its main application area.
True or False: Apache Kafka ensures message ordering across all partitions.
💡 Hint: Think about how Kafka organizes messages.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
Design an ETL pipeline using Apache Kafka as the core. Explain how you would handle fault tolerance and data durability.
💡 Hint: Consider how Kafka’s architecture supports multiple use cases.
Compare the performance implications of using MapReduce versus Spark for a real-time analytics task. What factors should be taken into account?
💡 Hint: Think about how speed and data retrieval methods affect performance.
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Reference links
Supplementary resources to enhance your learning experience.