QUBLE: blending visual subgraph query formulation with query processing on large networks

In a previous paper, we laid out the vision of a novel graph query processing paradigm where instead of processing a visual query graph after its construction, it interleaves visual query formulation and processing by exploiting the latency offered by the GUI [4]. Our recent attempts at implementing this vision [4,6], show significant improvement in the system response time (SRT) for subgraph queries. However, these efforts are designed specifically for graph databases containing a large collection of small or medium-sized graphs. Consequently, its frequent fragment-based action-aware indexing schemes and query processing strategy are unsuitable for supporting subgraph queries on large networks containing thousands of nodes and edges. In this demonstration, we present a novel system called QUBLE (QUery Blender for Large nEtworks) to realize this novel paradigm on large networks. We demonstrate various innovative features of QUBLE and its promising performance.