Practice Limitations of Spark - 13.3.6 | 13. Big Data Technologies (Hadoop, Spark) | Data Science Advance
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Limitations of Spark

13.3.6 - Limitations of Spark

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is one downside of Spark regarding its memory usage?

💡 Hint: Think about in-memory processing.

Question 2 Easy

Why might cluster tuning be necessary in Spark?

💡 Hint: Consider how tasks are handled in Spark.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is a primary limitation of Apache Spark related to memory?

Lower memory demand
Higher memory demand
No memory requirement

💡 Hint: Think about how Spark processes data.

Question 2

True or False: Spark has extensive built-in features for data governance.

True
False

💡 Hint: Consider the role of governance in data processing.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a scenario where a healthcare company uses Spark for patient data analysis but struggles with compliance, outline steps they could take to enhance data governance.

💡 Hint: Reflect on the principles of data security and compliance.

Challenge 2 Hard

If a research lab experiences performance issues due to Spark’s high memory usage, what strategies could they employ to mitigate these issues?

💡 Hint: Consider what settings might affect performance and efficiency.

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