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質問 1：
In a MapReduce job, the reducer receives all values associated with same key. Which statement best describes the ordering of these values?
A. The values are in sorted order.
B. The values are arbitrary ordered, but multiple runs of the same MapReduce job will always have the same ordering.
C. Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values.
D. The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce job.
正解：D
解説: (Pass4Test メンバーにのみ表示されます)
質問 2：
You want to perform analysis on a large collection of images. You want to store this data in HDFS and process it with MapReduce but you also want to give your data analysts and data scientists the ability to process the data directly from HDFS with an interpreted high-level programming language like Python. Which format should you use to store this data in HDFS?
A. CSV
B. XML
C. HTML
D. JSON
E. Avro
F. SequenceFiles
正解：E
解説: (Pass4Test メンバーにのみ表示されます)
質問 3：
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. 0
B. 5
C. 1
D. 3
E. 6
正解：D
解説: (Pass4Test メンバーにのみ表示されます)
質問 4：
When can a reduce class also serve as a combiner without affecting the output of a MapReduce program?
A. 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.
B. Never. Combiners and reducers must be implemented separately because they serve different purposes.
C. Always. Code can be reused in Java since it is a polymorphic object-oriented programming language.
D. Always. The point of a combiner is to serve as a mini-reducer directly after the map phase to increase performance.
E. When the signature of the reduce method matches the signature of the combine method.
正解：A
解説: (Pass4Test メンバーにのみ表示されます)
質問 5：
You are developing a combiner that takes as input Text keys, IntWritable values, and emits Text keys, IntWritable values. Which interface should your class implement?
A. Mapper <Text, IntWritable, Text, IntWritable>
B. Combiner <Text, Text, IntWritable, IntWritable>
C. Combiner <Text, IntWritable, Text, IntWritable>
D. Reducer <Text, IntWritable, Text, IntWritable>
E. Reducer <Text, Text, IntWritable, IntWritable>
正解：D
質問 6：
You want to count the number of occurrences for each unique word in the supplied input data. You've decided to implement this by having your mapper tokenize each word and emit a literal value 1, and then have your reducer increment a counter for each literal 1 it receives. After successful implementing this, it occurs to you that you could optimize this by specifying a combiner. Will you be able to reuse your existing Reduces as your combiner in this case and why or why not?
A. Yes, because Java is a polymorphic object-oriented language and thus reducer code can be reused as a combiner.
B. Yes, because the sum operation is both associative and commutative and the input and output types to the reduce method match.
C. No, because the Reducer and Combiner are separate interfaces.
D. No, because the Combiner is incompatible with a mapper which doesn't use the same data type for both the key and value.
E. No, because the sum operation in the reducer is incompatible with the operation of a Combiner.
正解：B
解説: (Pass4Test メンバーにのみ表示されます)
In a MapReduce job, the reducer receives all values associated with same key. Which statement best describes the ordering of these values?
A. The values are in sorted order.
B. The values are arbitrary ordered, but multiple runs of the same MapReduce job will always have the same ordering.
C. Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values.
D. The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce job.
正解：D
解説: (Pass4Test メンバーにのみ表示されます)
質問 2：
You want to perform analysis on a large collection of images. You want to store this data in HDFS and process it with MapReduce but you also want to give your data analysts and data scientists the ability to process the data directly from HDFS with an interpreted high-level programming language like Python. Which format should you use to store this data in HDFS?
A. CSV
B. XML
C. HTML
D. JSON
E. Avro
F. SequenceFiles
正解：E
解説: (Pass4Test メンバーにのみ表示されます)
質問 3：
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. 0
B. 5
C. 1
D. 3
E. 6
正解：D
解説: (Pass4Test メンバーにのみ表示されます)
質問 4：
When can a reduce class also serve as a combiner without affecting the output of a MapReduce program?
A. 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.
B. Never. Combiners and reducers must be implemented separately because they serve different purposes.
C. Always. Code can be reused in Java since it is a polymorphic object-oriented programming language.
D. Always. The point of a combiner is to serve as a mini-reducer directly after the map phase to increase performance.
E. When the signature of the reduce method matches the signature of the combine method.
正解：A
解説: (Pass4Test メンバーにのみ表示されます)
質問 5：
You are developing a combiner that takes as input Text keys, IntWritable values, and emits Text keys, IntWritable values. Which interface should your class implement?
A. Mapper <Text, IntWritable, Text, IntWritable>
B. Combiner <Text, Text, IntWritable, IntWritable>
C. Combiner <Text, IntWritable, Text, IntWritable>
D. Reducer <Text, IntWritable, Text, IntWritable>
E. Reducer <Text, Text, IntWritable, IntWritable>
正解：D
質問 6：
You want to count the number of occurrences for each unique word in the supplied input data. You've decided to implement this by having your mapper tokenize each word and emit a literal value 1, and then have your reducer increment a counter for each literal 1 it receives. After successful implementing this, it occurs to you that you could optimize this by specifying a combiner. Will you be able to reuse your existing Reduces as your combiner in this case and why or why not?
A. Yes, because Java is a polymorphic object-oriented language and thus reducer code can be reused as a combiner.
B. Yes, because the sum operation is both associative and commutative and the input and output types to the reduce method match.
C. No, because the Reducer and Combiner are separate interfaces.
D. No, because the Combiner is incompatible with a mapper which doesn't use the same data type for both the key and value.
E. No, because the sum operation in the reducer is incompatible with the operation of a Combiner.
正解：B
解説: (Pass4Test メンバーにのみ表示されます)
Aizawa -
貴社のCCD-410過去問を購入した、覚えるだけで合格することができました。とても助かりました。
また別の試験に活用したいですが、これからもよろしくお願いします。