A General-Purpose Query-Centric Framework for Querying Big Graphs
Publication in refereed journal


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摘要Pioneered by Google's Pregel, many distributed systems have been developed for large-scale graph analytics. These systems employ a user-friendly "think like a vertex" programming model, and exhibit good scalability for tasks where the majority of graph vertices participate in computation. However, the design of these systems can seriously under-utilize the resources in a cluster for processing light-workload graph queries, where only a small fraction of vertices need to be accessed. In this work, we develop a new open-source system, called Quegel, for querying big graphs. Quegel treats queries as first-class citizens in its design: users only need to specify the Pregel-like algorithm for a generic query, and Quegel processes light-workload graph queries on demand, using a novel superstep-sharing execution model to effectively utilize the cluster resources. Quegel further provides a convenient interface for constructing graph indexes, which significantly improve query performance but are not supported by existing graph-parallel systems. Our experiments verified that Quegel is highly efficient in answering various types of graph queries and is up to orders of magnitude faster than existing systems.
著者Yan D, Cheng J, Ozsu MT, Yang F, Lu Y, Lui JCS, Zhang QZ, Ng W
期刊名稱Proceedings of the VLDB Endowment
出版年份2016
月份3
卷號9
期次7
出版社ASSOC COMPUTING MACHINERY
頁次564 - 575
國際標準期刊號2150-8097
語言英式英語
Web of Science 學科類別Computer Science; Computer Science, Information Systems

上次更新時間 2021-12-09 於 23:33