Towards an Integral System for Processing Big Graphs at Scale

Abstract

Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. An increasing number of business applications naturally model data as graphs to capture complex relationships and dynamic interactions among entities. Processing such big graphs typically involves a variety of graph computations over billions of vertices and edges. It imposes many new challenges on users and developers. In this talk, I will first give an overview of the landscape of big graph processing and then present the design and implementation of GraphScope, a unified and open-source engine for big graph processing from Alibaba and Ant Group. GraphScope provides a unified programming interface to a wide range of graph computations such as graph traversal, pattern matching, iterative algorithms, and graph neural networks with a high-level programming language and supports parallel and distributed execution of sophisticated graph analysis on a cluster of machines. In addition, it provides an seamless integration of a highly optimized graph engine in a general-purpose data-parallel computing system. Finally, I will outline some challenges and future research directions for complex graph computations.