Hadoop Questions and Answers – Introduction to Mapreduce

This set of Multiple Choice Questions & Answers (MCQs) focuses on “Introduction to Mapreduce”.

1. A ________ node acts as the Slave and is responsible for executing a Task assigned to it by the JobTracker.
a) MapReduce
b) Mapper
c) TaskTracker
d) JobTracker
View Answer

Answer: c
Explanation: TaskTracker receives the information necessary for the execution of a Task from JobTracker, Executes the Task, and Sends the Results back to JobTracker.

2. 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) All of the mentioned
View Answer

Answer: a
Explanation: This feature of MapReduce is “Data Locality”.

3. ___________ part of the MapReduce is responsible for processing one or more chunks of data and producing the output results.
a) Maptask
b) Mapper
c) Task execution
d) All of the mentioned
View Answer

Answer: a
Explanation: Map Task in MapReduce is performed using the Map() function.

4. _________ function is responsible for consolidating the results produced by each of the Map() functions/tasks.
a) Reduce
b) Map
c) Reducer
d) All of the mentioned
View Answer

Answer: a
Explanation: Reduce function collates the work and resolves the results.

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5. Point out the wrong statement.
a) A MapReduce job usually splits the input data-set into independent chunks which are processed by the map tasks in a completely parallel manner
b) The MapReduce framework operates exclusively on <key, value> pairs
c) Applications typically implement the Mapper and Reducer interfaces to provide the map and reduce methods
d) None of the mentioned
View Answer

Answer: d
Explanation: The MapReduce framework takes care of scheduling tasks, monitoring them and re-executes the failed tasks.

6. Although the Hadoop framework is implemented in Java, MapReduce applications need not be written in ____________
a) Java
b) C
c) C#
d) None of the mentioned
View Answer

Answer: a
Explanation: Hadoop Pipes is a SWIG- compatible C++ API to implement MapReduce applications (non JNITM based).

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7. ________ is a utility which allows users to create and run jobs with any executables as the mapper and/or the reducer.
a) Hadoop Strdata
b) Hadoop Streaming
c) Hadoop Stream
d) None of the mentioned
View Answer

Answer: b
Explanation: Hadoop streaming is one of the most important utilities in the Apache Hadoop distribution.

8. __________ maps input key/value pairs to a set of intermediate key/value pairs.
a) Mapper
b) Reducer
c) Both Mapper and Reducer
d) None of the mentioned
View Answer

Answer: a
Explanation: Maps are the individual tasks that transform input records into intermediate records.

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9. The number of maps is usually driven by the total size of ____________
a) inputs
b) outputs
c) tasks
d) None of the mentioned
View Answer

Answer: a
Explanation: Total size of inputs means the total number of blocks of the input files.

10. _________ is the default Partitioner for partitioning key space.
a) HashPar
b) Partitioner
c) HashPartitioner
d) None of the mentioned
View Answer

Answer: c
Explanation: The default partitioner in Hadoop is the HashPartitioner which has a method called getPartition to partition.

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11. Running a ___________ program involves running mapping tasks on many or all of the nodes in our cluster.
a) MapReduce
b) Map
c) Reducer
d) All of the mentioned
View Answer

Answer: a
Explanation: In some applications, component tasks need to create and/or write to side-files, which differ from the actual job-output files.

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If you find a mistake in question / option / answer, kindly take a screenshot and email to [email protected]

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Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He lives in Bangalore, and focuses on development of Linux Kernel, SAN Technologies, Advanced C, Data Structures & Alogrithms. Stay connected with him at LinkedIn.

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