Suppose our Accumulo system stores entire documents in the value column using the following data structure to represent the Gettysburg Address and the Declaration of Independence: rowID family qual time value gettysburg speech script Four score and seven years ago ... When in the course of human events declaration document script Write Map and Reduce pseudocode that determines document similarity according to combinations of three important words. Important words are the words that are not in stop word lists. Stop words are words that are common to all documents that do not provide much indication of the topic of the document. Example stop words include the, аnd, to, but, bеcаuse, an, a, .... Assume that you are given the following array of stop words to use: private String[] stopWords = {"the", "and", "to", "but", "because", "an", "a", ...}; %3D For all combinations of three important (non-stop word) words, create an Accumulo output table that clusters documents according to the important word triples. Two sample output rows from the MapReduce algorithm applied to the table above will look like: rowID family qual time value government:liberty:people speech script gettysburg government:liberty:people document script declaration Make sure that the important words used in the rowID are sorted in alphabetical order so you have only one "government:liberty:people" rowID value, not "government:people:liberty", "liberty:government:people", "liberty:people:government", "people:liberty:government", "people:government:liberty". Also, do not worry about multiple occurrences of any word. Even though the word government appears many times in the Declaration of Independence, just create one output for the "government:liberty:people" triple.