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Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:

1. MapReduce v2 (MRv2/YARN) is designed to address which two issues?

A) Single point of failure in the NameNode.
B) Standardize on a single MapReduce API.
C) Resource pressure on the JobTracker.
D) Ability to run frameworks other than MapReduce, such as MPI.
E) Reduce complexity of the MapReduce APIs.
F) HDFS latency.

2. In the reducer, the MapReduce API provides you with an iterator over Writable values. What does calling the next () method return?

A) It returns a reference to a Writable object from an object pool.
B) It returns a reference to a different Writable object time.
C) It returns a reference to a Writable object. The API leaves unspecified whether this is a reused object or a new object.
D) It returns a reference to the same Writable object if the next value is the same as the previous value, or a new Writable object otherwise.
E) It returns a reference to the same Writable object each time, but populated with different data.

3. Which HDFS command displays the contents of the file x in the user's HDFS home directory?

A) hadoop fs -cat x
B) hadoop fs -Is x
C) hadoop fs -cp x
D) hdfs fs -get x

4. In a MapReduce job, you want each of your input files processed by a single map task. How do you configure a MapReduce job so that a single map task processes each input file regardless of how many blocks the input file occupies?

A) Increase the parameter that controls minimum split size in the job configuration.
B) Set the number of mappers equal to the number of input files you want to process.
C) Write a custom FileInputFormat and override the method isSplitable to always return false.
D) Write a custom MapRunner that iterates over all key-value pairs in the entire file.

5. In a large MapReduce job with m mappers and n reducers, how many distinct copy
operations will there be in the sort/shuffle phase?

A) mn (i.e., m to the power of n)
B) m
C) mXn (i.e., m multiplied by n)
D) m+n (i.e., m plus n)
E) n

Solutions: