iGraph in Action: Performance Analysis of Disk-Based Graph Indexing Techniques

摘要

Graphs provide a powerful way to model complex structures such as chemical compounds, protein interactions, images, and program dependencies. The previous practice for experiments in graph indexing techniques is that the author of a newly proposed technique does not implement existing indexes on his own code base, but uses the original author's binary executables and reports only the wall clock time. We observed that this practice may result in several problems [6]. In order to address these problems, we implemented all representative graph indexing techniques in a common framework, called iGraph [6]. In this demonstration we showcase iGraph and its visual tools using several real datasets and their workloads. For selected queries from the workloads, we show several unique features including in-depth performance analysis.