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

Question : You have below code for Hadoop Streaming

hadoop jar $THEJARFILE \
-input file:///etc/passwd
-output streamOut0 \
-mapper '/bin/cat' \
-reducer '/bin/cat'

In above Job



1. /bin/cat command as a Mapper

2. /et/passwd is a input file

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4. 1,2

5. 1,2,3


Correct Answer : Get Lastest Questions and Answer :
Explanation: we are simply using the /bin/cat command as a mapper to cat the local /etc/passwd file to the reducer (also the /bin/cat command).
The output from this job is being sent to the "./streamOut0" directory




Question : In Streaming process reducer will



1. received keys in sorted order along with their associated values, one value at a time

2. received keys in sorted order along with their associated values, all associated values at once

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4. 1,2
5. 1,3

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Explanation: In a MapReduce streaming job, the mapper will continue to get records (key-value pairs) on the standard input stream until the OS
closes the stream (end-of-file).
Your mapper code will generate key-value pairs and emit them in the format (key \t value \n).

When there are multiple mappers (e.g. multiple input splits), then the intermediate results are hashed based on the key and partitioned. Your reduce program
will received keys in sorted order along with their associated values, one value at a time. This is a different model than in the Java reducer paradigm in
which the reducer method is called with a single key and the associated list of values at once. Your reducer code will need to account for this by checking
whether the key has changed





Question : Please map the following, with regards to Streaming

A. key.value.separator.in.input.line
B. stream.map.input.field.separator
C. stream.map.output.field.separator
D. mapred.texoutputformat.separator

1. output field separator in the map
2. Setting key-value separator (default value is \t)
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4. configure the key-value separator in the reducer output files


1. A-1, B-3, C-2, D-4
2. A-3, B-1, C-2, D-4
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4. A-1, B-3, C-4, D-2
5. A-2, B-3, C-1, D-4

Correct Answer : Get Lastest Questions and Answer :
Explanation: You can configure the key-value separator (default is \t) using the key.value.separator.in.input.line parameter. Configure the
input and output field separator in the map
using stream.map.input.field.separator and stream.map.output.field.separator parameters (default is any white space).
Last, you can configure the key-value separator in the reducer output files by configuring the mapred.texoutputformat.separator (default is \t).

MapReduce streaming mapper function loops through and reads standard input, cleans up the line, extracts the key and value,
performs any operations per your program logic, and then writes key and value (separated by \t) to standard output

Related Questions

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Question :

Is there anyway in the MapReduce model that reducers communicate with each other in Hadoo framework ?


1. Yes, using JobConf configuration object it is possible
2. Using distributed cache it is possible
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4. No, each reducers runs independently and in isolation.






1. A
2. B
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4. D




">
1. A
2. B
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4. D
5. E




Question :
How do you differentiate between failed task and killed task



1. A
2. B
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4. D


Question :

Using combiner you can reduce...


1. The number of values across different keys in the iterator supplied to a single reduce method call.
2. The amount of intermediate data that must be transferred between the mapper and reducer.
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4. The number of output files a reducer must produce.




Question :

What is true about combiner ?


1. Combiner does the local aggregation of data, thereby allowing the number of mappers to process input data faster.
2. Combiner does the local aggregation of data, thereby reducing the number of mappers that need to run.
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