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

Question : You have following Perl script, which you want to use as a Streaming identity Mapper

#!/usr/bin/env perl

while(<>) {
chomp;
my($key, $value) = split(/\t/,$_);
print "Key:".$key.XXXXX."value:".$value.YYYYY;
}

What would be the correct replacement for separator?


1. XXXXX-> \n , YYYYY -> \n

2. XXXXX -> \t , YYYYY-> \t

3. Access Mostly Uused Products by 50000+ Subscribers

4. XXXXX -> \n , YYYYY-> \t


Correct Answer : Get Lastest Questions and Answer :
Explanation: It is just take data as input and convert into key-value pair. For each record, it chomp the last character (\n), and create a new
key and value variables as output to the split method (split on \t).
While printing "key:" followed by the key and "value:" followed by the value to standard out. Here key and value strings are separated by the \t, and the
key-value pair is terminated by a \n.
For intermediate results of the streaming job.




Question : Which is the following is/are correct way to debug streaming job



1. We need to check mapper and reducer script can run on its own by feeding it input on standard in

2. We must test with bad data as well.

3. Access Mostly Uused Products by 50000+ Subscribers

4. 1,2

5. 1,2,3


Correct Answer : Get Lastest Questions and Answer :
Explanation: General approaches to debug hadoop streaming code
We must make sure that mapper and reducer script can run on it's own by feeding it input on standard in. As with any program, we should always test with
bad data for instance data is
' not formatted according to what map and reduce scripts expect. Test the map and reduce functions in the hadoop framework by using "identity" mapper and
reducers accordingly.





Question : How to monitor streaming jobs using counter



1. update counters from within your map and reduce scripts, with the string "reporter:counter"

2. update status from within your map and reduce scripts, with the string "reporter:status"

3. Access Mostly Uused Products by 50000+ Subscribers

4. 1,2

5. 1,2,3

Correct Answer : Get Lastest Questions and Answer :
Explanation:

Related Questions

---

Question :

in 3 mappers and 2 reducers how many distinct copy operations will be there in the sort or shuffle phase


1. 3
2. 2
3. Access Mostly Uused Products by 50000+ Subscribers
4. 5




Question :

In which scenario MapReduce is not suitable..


1. text mining on the unstructured documents
2. Analyzing web documents
3. Access Mostly Uused Products by 50000+ Subscribers
4. for a large computation of financial risk modeling and performance analysis.




Question : How can you use binary data in MapReduce?


1. Binary data can be used directly by a map-reduce job. Often binary data is added to a sequence file
2. Binary data cannot be used by Hadoop framework. Binary data should be converted to a Hadoop compatible format prior to loading
3. Access Mostly Uused Products by 50000+ Subscribers
4. Hadoop can freely use binary files with map-reduce jobs so long as the files have headers



Question : What is map - side join?

1. Map-side join is done in the map phase and done in memory
2. Map-side join is a technique in which data is eliminated at the map step
3. Access Mostly Uused Products by 50000+ Subscribers
4. None of these answers are correct





Question : How can you disable the reduce step?


1. The Hadoop administrator has to set the number of the reducer slot to zero on all slave nodes. This will disable the reduce step.
2. It is impossible to disable the reduce step since it is critical part of the Map-Reduce abstraction.
3. Access Mostly Uused Products by 50000+ Subscribers
4. While you cannot completely disable reducers you can set output to one.
There needs to be at least one reduce step in Map-Reduce abstraction.




Question : Why would one create a map-reduce without the reduce step?

1. Developers should design Map-Reduce jobs without reducers only if no reduce slots are available on the cluster
2. Developers should never design Map-Reduce jobs without reducers. An error will occur upon compile
3. Access Mostly Uused Products by 50000+ Subscribers
4. It is not possible to create a map-reduce job without at least one reduce step.
A developer may decide to limit to one reducer for debugging purposes