1. A computer-implemented method for processing graph data, the method comprising: executing a Markov Clustering algorithm (MCL) to find clusters of vertices of the graph data; organizing the graph data by column by calculating a probability percentage for each column of a similarity matrix of the graph data to produce column data; generating a probability matrix of states of the column data; performing an expansion of the probability matrix by computing a power of the probability matrix using a Map-Reduce model executed in a processor-based computing device; and organizing the probability matrix into a set of sub-matrices to find the least amount of data needed for the Map-Reduce model given that two lines of data in the probability matrix are required to compute a single value for the power of the probability matrix.