Practice Limitations Of Spark (13.3.6) - Big Data Technologies (Hadoop, Spark)

Practice: Limitations of Spark

Lesson 13.3.6Big Data Technologies (Hadoop, Spark)

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9 questions

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3 cards from this section. Quick, good the night before a test.
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6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
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6 sample questions

Question 1.
What is one downside of Spark regarding its memory usage?
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Think about in-memory processing.
Question 2.
Why might cluster tuning be necessary in Spark?
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Consider how tasks are handled in Spark.
3Question 3.
What is a primary limitation of Apache Spark related to memory?
- Lower memory demand
- Higher memory demand
- No memory requirement
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Think about how Spark processes data.
4Question 4.
True or False: Spark has extensive built-in features for data governance.
- True
- False
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Consider the role of governance in data processing.
Question 5.
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.
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Reflect on the principles of data security and compliance.
Question 6.
If a research lab experiences performance issues due to Spark’s high memory usage, what strategies could they employ to mitigate these issues?
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Consider what settings might affect performance and efficiency.

5 more questions in this section. Enroll free to practise them all.