Cloudera Certified Developer for Apache Hadoop (CCDH): CCD-410

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. Write a custom MapRunner that iterates over all key-value pairs in the entire file.

C. Set the number of mappers equal to the number of input files you want to process.

D. Write a custom FileInputFormat and override the method isSplitable to always return false.

You have written a Mapper which invokes the following five calls to the OutputColletor.collect method:

output.collect (new Text ("Apple"), new Text ("Red") ) ;

output.collect (new Text ("Banana"), new Text ("Yellow") ) ; output.collect (new Text ("Apple"), new Text

("Yellow") ) ; output.collect (new Text ("Cherry"), new Text ("Red") ) ;

output.collect (new Text ("Apple"), new Text ("Green") ) ;

How many times will the Reducer's reduce method be invoked?

A. 6

B. 3

C. 1

D. 0

E. 5

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 different Writable object time.

B. It returns a reference to a Writable object from an object pool.

C. It returns a reference to the same Writable object each time, but populated with different data.

D. It returns a reference to a Writable object. The API leaves unspecified whether this is a reused object or a new object.

E. 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.