Use MapReduce framework to convert the set of written book reviews to quantitative ratings of certain criteria. The output is the average of all numeric ratings of the book criteria. Reviewer1: Book A: I love reading it. The story is interesting, the writing is very good. Reviewer2: Book A: the story is amazing, however, the writing can be more entertaining. Reviewer3: Book B: the story is interesting, the writing is entertaining, I like reading it. Note: no standard answer since you decide the map function
Question 1:
Use MapReduce framework to convert the set of written book reviews to quantitative ratings of certain criteria. The output is the average of all numeric ratings of the book criteria.
Reviewer1: Book A: I love reading it. The story is interesting, the writing is very good.
Reviewer2: Book A: the story is amazing, however, the writing can be more entertaining.
Reviewer3: Book B: the story is interesting, the writing is entertaining, I like reading it.
Note: no standard answer since you decide the map function
Question 2:
Assume there are two files each of which contains city names and their recorded temperatures (note that each file might have the same city represented multiple times) as follows:
File 01: (Cheney, 20), (Spokane, 25), (Seattle, 31), (Cheney, 14), (Spokane, 23)
File 02: (Cheney, 18), (Seattle, 33), (Spokane, 32), (Seattle, 29), (Spokane, 30)
Given these two files as the input, illustrate the Splitting, Mapping, Shuffling, Reducing, and Final Result steps (in this order) in the MapReduce framework to return the maximum temperature for each city.
Submit a Word file.
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