Practice Limitations of Hadoop - 13.2.5 | 13. Big Data Technologies (Hadoop, Spark) | Data Science Advance
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does high latency mean in the context of Hadoop?

💡 Hint: Think about how quickly data needs to be processed in real-time applications.

Question 2

Easy

Why is configuration complexity a limitation for Hadoop?

💡 Hint: Consider the implications of needing specialized skills.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is a major disadvantage of using Hadoop for real-time processing?

  • High latency
  • Low cost
  • Easy to maintain

💡 Hint: Consider the definition of latency in the context of data processing.

Question 2

True or False: Hadoop is known for its real-time processing capabilities.

  • True
  • False

💡 Hint: Recall the focus of Hadoop on batch versus real-time processing.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Analyze a scenario where a financial institution needs timely fraud detection. Explain why Hadoop might not be suitable for this application.

💡 Hint: Consider the implications of delayed data processing in finance.

Question 2

A data scientist needs to implement a machine learning model using Hadoop. Discuss the challenges they might encounter due to Hadoop's limitations.

💡 Hint: Reflect on how those challenges impact machine learning.

Challenge and get performance evaluation