Practice Using Hadoop And Spark Together (13.5.3) - Big Data Technologies (Hadoop, Spark)

Practice: Using Hadoop and Spark Together

Lesson 13.5.3Big Data Technologies (Hadoop, Spark)

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9 questions

Flashcard drill
4 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is HDFS used for?
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Think about how data is stored in a distributed manner.
Question 2.
What role does YARN play in Hadoop?
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Consider what happens when multiple jobs run at the same time.
3Question 3.
What does HDFS stand for?
- Hadoop Data File System
- Hadoop Distributed File System
- Hadoop Dynamic File System
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Think about the role of Hadoop in data storage.
4Question 4.
True or False: Spark can process data faster than Hadoop MapReduce.
- True
- False
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Consider the difference in how each system handles data.
Question 5.
Design a big data architecture for a retail business needing real-time analytics on sales data. Describe how Hadoop and Spark would work together in this architecture.
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Think about how data flows from collection to analysis.
Question 6.
Discuss the potential challenges a company might face when integrating Hadoop and Spark, and propose solutions.
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Consider both technical and operational challenges.

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