Here are a few examples of big data problems that can be solved with the MapReduce framework:
Given a repository of text files, find the frequency of each word. This is called the WordCount problem.
Given a repository of text files, find the number of words of each word length.
Given two matrices in sparse matrix format, compute their product.
Factor a matrix given in sparse matrix format.
Given a symmetric graph whose nodes represent people and edges represent friendship, compile a list of common friends.
Given a symmetric graph whose nodes represent people and edges represent friendship, compute the average number of friends by age.
Given a repository of weather records, find the annual global minima and maxima by year.
Sort a large list. Note that in most implementations of the MapReduce framework, this problem is trivial, because the framework automatically sorts the output from the
map()function.Reverse a graph.
Find a minimal spanning tree (MST) of a...