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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. Which of the following statements most accurately describes the relationship between MapReduce and Pig?

A) Pig provides the additional capability of allowing you to control the flow of multiple MapReduce jobs.
B) Pig programs rely on MapReduce but are extensible, allowing developers to do special-purpose processing not provided by MapReduce.
C) Pig provides no additional capabilities to MapReduce. Pig programs are executed as MapReduce jobs via the Pig interpreter.
D) Pig provides additional capabilities that allow certain types of data manipulation not possible with MapReduce.

2. You have the following key value pairs as output from your Map task:
(The, 1)
(Fox, 1)
(Runs, 1)
(Faster, 1)
(Than, 1)
(The, 1)
(Dog, 1)
How many keys will be passed to the reducer?

A) Three
B) Two
C) Six
D) Five
E) One
F) Four

3. Which two of the following are valid statements? (Choose two)

A) HDFS is a distributed file system that replaces ext3 or ext4 on Linux nodes in a Hadoop cluster.
B) HDFS is a distributed file system that runs on top of native OS filesystems and is well suited to storage of very large data sets.
C) HDFS has the Characteristic of supporting a "write once, read many" data access model.
D) HDFS is optimized for storing a large number of files smaller than the HDFS block size.

4. What is a SequenceFile?

A) A SequenceFile contains a binary encoding of an arbitrary number of homogeneous writable objects.
B) A SequenceFile contains a binary encoding of an arbitrary number of heterogeneous writable objects.
C) A SequenceFile contains a binary encoding of an arbitrary number key-value pairs. Each key must be the same type. Each value must be same type.
D) A SequenceFile contains a binary encoding of an arbitrary number of WritableComparable objects, in sorted order.

5. In a MapReduce job, the reducer receives all values associated with the same key. Which statement is most accurate about the ordering of these values?

A) The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce job.
B) The values are in sorted order.
C) The values are arbitrarily ordered, but multiple runs of the same MapReduce job will always have the same ordering.
D) Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values.

Solutions: