GraphDB – storing large graphs on secondary memory

Abstract

The volume of complex network data has been exponentially increased in the last years madding graph mining area the focus of a lot of research efforts. Most algorithms for mining this kind of data assume, however, that the complex network fits in primary memory. Unfortunately, such assumption is not always true. Even considering that, in some cases, using big computer clusters (in a MapReduce fashion, for instance) might be a suitable way to circumvent part of the difficulties of mining big data, efficiently storing and retrieving complex network data is still a great challenge. Thus the main goal of this work is to introduce the definition of a new data structure, called GraphDB-tree that can be used to efficiently store and retrieve complex networks, and also, allowing efficient queries in large complex networks.