This part of the hadoop process groups and sorts data by commonalities.

parallel processing

indexing

induction

map

D. Map

Explanation:

Hadoop MapReduce is used to sort data and group the data. The big data is handlled in two phases in the Mapreduce. they are known as Map Phase and Reduce Phase.

In this framework keys generated by the mappers are sorted automatically.

map(key1, value1) → list(key2, value2)

Here the map function receives the input as key value pairs and outputs any numbers of these pairs.

reduce(key2, list(value2)) → list(key3, value3)

reduce function receives input as key value pairs and outputs as key value pairs as well.

map reduce framework will group all the values associated with output and reducer will determine the final output. Comparators are used to control the grouping.

i think the answer is b.