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1. Explain how you would compute the average of a billion integers using map-reduce. What would the map function do? What would the reduce function do? Not necessary to write any code. Use...

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1. Explain how you would compute the average of a billion integers using map-reduce. What would the map function do? What would the reduce function do? Not necessary to write any code. Use English sentences to describe what each method will do.
2. Explain how you will use the map-reduce framework to search a large file for a specific string, e.g., "a
acada
a". What would the map function do? What would the reducer do? Not necessary to write any code. Use English sentences to describe what each method will do.
3. Assume we want to implement map-reduce in a parallel setting involving a cluster of 10 computers, with 100 mappers and 100 reducers. Explain how you might distribute the 200 mappers+reducers onto the 10 computers.

1. Explain how you would compute the average of a billion integers using map-reduce. What would the map function do? What would the reduce function do? Not necessary to write any code. Use English sentences to describe what each method will do.
2. Explain how you will use the map-reduce framework to search a large file for a specific string, e.g., "a
acada
a". What would the map function do? What would the reducer do? Not necessary to write any code. Use English sentences to describe what each method will do.
3. Assume we want to implement map-reduce in a parallel setting involving a cluster of 10 computers, with 100 mappers and 100 reducers. Explain how you might distribute the 200 mappers+reducers onto the 10 computers.
Answered 1 days After Nov 16, 2021

Solution

Neha answered on Nov 18 2021
118 Votes
1. Explain how you would compute the average of a billion integers using map-reduce. What would the map function do? What would the reduce function do? Not necessary to write any code. Use English sentences to describe what each method will do.
The mapper will output 2 columns of the data, count and the average. For every input record it will be simply one and the output of the field. The reducer will multiply the count field by the average field and add it to the running sum and add the count field to the running count. It will divide the running sound with the driving count and show the output for the count with their calculated average.
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