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1. 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.

2. Which one of the following statements describes a Pig bag. tuple, and map, respectively?

A) Unordered collection of maps, ordered collection of tuples, ordered set of key/value pairs
B) Ordered collection of maps, ordered collection of bags, and unordered set of key/value pairs
C) Unordered collection of tuples, ordered set of fields, set of key value pairs
D) Ordered set of fields, ordered collection of tuples, ordered collection of maps

3. When can a reduce class also serve as a combiner without affecting the output of a MapReduce program?

A) When the signature of the reduce method matches the signature of the combine method.
B) Always. The point of a combiner is to serve as a mini-reducer directly after the map phase to increase performance.
C) When the types of the reduce operation's input key and input value match the types of the reducer's output key and output value and when the reduce operation is both communicative and associative.
D) Always. Code can be reused in Java since it is a polymorphic object-oriented programming language.
E) Never. Combiners and reducers must be implemented separately because they serve different purposes.

4. Indentify the utility that allows you to create and run MapReduce jobs with any executable
or script as the mapper and/or the reducer?

A) Flume
B) Oozie
C) Hadoop Streaming
D) Sqoop
E) mapred

5. What types of algorithms are difficult to express in MapReduce v1 (MRv1)?

A) Large-scale graph algorithms that require one-step link traversal.
B) Text analysis algorithms on large collections of unstructured text (e.g, Web crawls).
C) Algorithms that require applying the same mathematical function to large numbers of individual binary records.
D) Relational operations on large amounts of structured and semi-structured data.
E) Algorithms that require global, sharing states.

問題與答案：