Practice Advantages Of Spark (13.3.5) - Big Data Technologies (Hadoop, Spark)

Practice: Advantages of Spark

Lesson 13.3.5Big Data Technologies (Hadoop, Spark)

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10 questions

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5 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
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What does 'in-memory processing' mean in the context of Spark?
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Think about where the data is processed - is it on disk or memory?
Question 2.
What programming languages can Spark's API support?
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Remember the acronym 'P-SJR'.
3Question 3.
What key advantage does Spark offer with its processing method?
- Slower computation
- In-memory processing
- Disk-based processing
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Think about how processing data in memory vs on disk affects speed.
4Question 4.
True or False: Spark can only handle batch processing.
- True
- False
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Recall the versatility of Spark's capabilities.
Question 5.
Analyze a use case where in-memory processing could significantly reduce the time taken for data analytics compared to traditional disk-based systems.
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Think about sectors that require speed and flexibility in data handling.
Question 6.
Consider a scenario where a company needs both historical reports and real-time insights. How would Spark's capabilities facilitate this need effectively?
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Reflect on how different data regimes can coexist in Spark's environment.

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