Challenges and Approaches for Large Graph Analysis Using Map/Reduce Paradigm

Analysis of big graphs has become possible due to the convergence of many technologies such as server farms, new paradigms for processing data in massively parallel ways (e.g., Map/Reduce, Bulk Synchronous Parallelization), as well as the ability to process unstructured data. This has allowed one to solve problems that were not possible (or extremely time consuming) earlier. Many algorithms are being mapped to new paradigms to deal with larger versions with a meaningful response time.