CCD-333 試験問題を無料オンラインアクセス

If you run the word count MapReduce program with m mappers and r reducers, how many output files will you get at the end of the job? And how many key-value pairs will there be in each file? Assume k is the number of unique words in the input files.

• A.There will be r files, each with approximately k/r key-value pairs.
• B.There will be m files, each with exactly k/m key value pairs.
• C.There will be r files, each with exactly k/r key-value pairs.
• D.There will be r files, each with approximately k/m key-value pairs.
• E.There will be m files, each with approximately k/m key-value pairs.

For each intermediate key, each reducer task can emit:

• A.As many final key-value pairs as desired, as long as all the keys have the same type and all the values have the same type.
• B.As many final key-value pairs as desired, but they must have the same type as the intermediate key-value pairs.
• C.As many final key value pairs as desired. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous)
• D.One final key value pair per key; no restrictions on the type.
• E.One final key-value pair per value associated with the key; no restrictions on the type.

What types of algorithms are difficult to express MapReduce?

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

MapReduce is well-suited for all of the following applications EXCEPT? (Choose one):

• A.Online transaction processing (OLTP) for an e-commerce Website.
• B.Text mining on a large collections of unstructured documents.
• C.Analysis of large amounts of Web logs (queries, clicks, etc.).
• D.Graph mining on a large social network (e.g., Facebook friends network).

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

• A.r
• B.m+r (i.e., m plus r)
• C.m
• D.mxr (i.e., m multiplied by r)
• E.mr (i.e., m to the power of r)