Hadoop MapReduce MCQs

This section focuses on "MapReduce" in Hadoop. These Multiple Choice Questions (MCQ) should be practiced to improve the hadoop skills required for various interviews (campus interviews, walk-in interviews, company interviews), placements, entrance exams and other competitive examinations.

1. The MapReduce algorithm contains two important tasks, namely __________.

A. mapped, reduce
B. mapping, Reduction
C. Map, Reduction
D. Map, Reduce

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2. _____ takes a set of data and converts it into another set of data, where individual elements are broken down into tuples (key/value pairs).

A. Map
B. Reduce
C. Both A and B
D. Node

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3. ______ task, which takes the output from a map as an input and combines those data tuples into a smaller set of tuples.

A. Map
B. Reduce
C. Node
D. Both A and B

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4. In how many stages the MapReduce program executes?

A. 2
B. 3
C. 4
D. 5

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5. Which of the following is used to schedules jobs and tracks the assign jobs to Task tracker?

A. SlaveNode
B. MasterNode
C. JobTracker
D. Task Tracker

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6. Which of the following is used for an execution of a Mapper or a Reducer on a slice of data?

A. Task
B. Job
C. Mapper
D. PayLoad

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7. Which of the following commnd runs a DFS admin client?

A. secondaryadminnode
B. nameadmin
C. dfsadmin
D. adminsck

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8. Point out the correct statement.

A. MapReduce tries to place the data and the compute as close as possible
B. Map Task in MapReduce is performed using the Mapper() function
C. Reduce Task in MapReduce is performed using the Map() function
D. None of the above

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9. Although the Hadoop framework is implemented in Java, MapReduce applications need not be written in ____________

A. C
B. C#
C. Java
D. None of the above

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10. The number of maps is usually driven by the total size of ____________

A. Inputs
B. Output
C. Task
D. None of the above

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