Mapr (HP) Hadoop Developer Certification Questions and Answers (Dumps and Practice Questions)

Question : Which of the following methods of the Mapper class is/are called?



1. setup()

2. map()

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4. 1,2

5. 1,2,3

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Explanation: The default run() method for the Mapper class invokes setup() once for each Mapper/split. The run() method then calls the map()
method once for each record.
You can override the default run() method if you wanted to do some debugging, or if you implement a multi-threaded Mapper.
The setup() method is called when the task starts (i.e. before the map() method is called).





Question : Map the following
A. setup()
B. map()
C. cleanup()

1. once for each record
2. once for each Mapper/split
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1. A-1, B-2, C-3
2. A-3, B-1, C-31
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4. A-2, B-3, C-1
5. A-3, B-2, C-1

Correct Answer : Get Lastest Questions and Answer :
Explanation: The default run() method for the Mapper class invokes setup() once for each Mapper/split. The run() method then calls the map()
method once for each record.
You can override the default run() method if you wanted to do some debugging, or if you implement a multi-threaded Mapper.
The setup() method is called when the task starts (i.e. before the map() method is called).





Question : You have written a MapReduce job. You open a connection to HBASE and read data from it. Which is the write place to close HBase connection?



1. IN setup() method of a Mapper class

2. At the end of map() method of a Mapper class

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4. 2 and 3 both are correct


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Explanation: : The cleanup() method is called when the mapper task finishes . One use case for using the setup() and cleanup() method is to open
and close a file, HBase, or JDBC connection.
This is a much more streamlined approach if I/O is performed during the task than to open and close a stream within the map() or reduce() method.

Related Questions

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Question :
You have the following key-value pairs as output from your Map task:
(HadoopExam, 1)
(Is, 1)
(the, 1)
(best, 1)
(material, 1)
(provider, 1)
(for, 1)
(the, 1)
(Hadoop, 1)
How many keys will be passed to the Reducer's reduce() method?



1. 9
2. 8
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4. 6
5. 5


Question : While processing the file using MapReduce framework, the output of the Mapper which we call as
intermediate key-value pairs, select the correct statement for this output of the mappers.

1. Intermediate key-value pairs are written to the HDFS of the machines running the map tasks, and then copied to the machines running the reduce tasks.
2. Intermediate key-value pairs are written to the local disks of the machines running the reduce tasks.
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4. Intermediate key-value pairs are written to the local disks of the machines running the map tasks, and then read by the machines running the reduce tasks.


Question : HadoopExam stores everyday, the users IP address+location as a string in the file as well as
number of total clicks as an Integer (Incremented for each click) and this is quite huge file,
where the keys are strings (address+location), and the values are integers (clicks).
For each unique key, you want to identify the largest integer. In writing a MapReduce program to accomplish this,
using the combine is advantageous ?

1. Yes
2. No
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4. Yes, if configured while cluster setup


Question : A MapReduce program has two components: one that implements the mapper, and another that implements the reducer. You have to implement
map() method for the Mapper and reduce() method for the reducer. When is the earliest that the reduce() method of any reduce task of your submitted
job will be called?

1. Not until all map tasks have completed
2. As soon as first map tasks have completed
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4. It can be started any time during the Job no particular time


Question : While processing Timeseries data of the QuickTechie Inc log file using MapReduce ETL batch job you have set up the number of reducers
to 1 (one) . Select the correct statement which applies.

1. A single reducer gathers and processes all the output from all the mappers. The output is written to a multiple file in HDFS.
2. Number of reducers can not be configured, it is determined by the NameNode during runtime.
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4. A single reducer will process all the output from all the mappers. The output is written to a single file in HDFS.


Question : You have created a MapReduce job to process TimeSeries Market Data file with the driver class called
HadoopDriver (in the default package) packaged into a jar called HadoopExam.jar, what is the appropriate way to submit this job to the cluster?

1. hadoop jar HadoopExam.jar HadoopDriver outputdir inputdir
2. hadoop inputdir outputdir jar HadoopExam.jar HadoopDriver
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4. hadoop jar HadoopExam.jar HadoopDriver inputdir outputdir