Towards a Distributed Infrastructure for Evolving Graph Analytics

Graphs are used to represent a plethora of phenomena, from the Web and social networks, to biological pathways, to semantic knowledge bases. Arguably the most interesting and important questions one can ask about graphs have to do with their evolution. Which Web pages are showing an increasing popularity trend? How does influence propagate in social networks? How does knowledge evolve? In this paper we present our ongoing work on the Portal system, an open-source distributed framework for evolving graphs. Portal streamlines exploratory analysis of evolving graphs, making it efficient and usable, and providing critical tools to computational and data scientists. Our system implements a declarative query language by the same name, which we briefly describe in this paper. Our basic abstraction is a TGraph, which logically represents a series of adjacent snapshots. We present different physical representations of TGraphs and show results of a preliminary experimental evaluation of these physical representations for an important class of evolving graph analytics.