View Selection for Graph Pattern Matching

Xin Wang, Xiufeng Liu, Yuxiang Chen, Xueyan Zhong, Ping Cheng

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


View-based techniques have been investigated on relational data, XML and graphs and proven effective for querying big data. While the pivot of using materialized views for query answering is view selection. Though explored for several years, the view selection problem for graph pattern matching has not been investigated. To this end, we investigate the problem in this paper. We first formalize the problem and show its intractability feature. We next propose an appropriate cost model and develop an effective algorithm to identify a set of view definitions under resource constraints, e.g., space storage and query processing cost, from a query workload. We finally verify the performance of the algorithms, and show that our view selection algorithm can identify a set of views that not only have low cost, e.g., storage space (below specified budget) and query processing cost but also can answer queries efficiently.
Original languageEnglish
Title of host publicationProceedings of International Conference on Database and Expert Systems Applications
Publication date2020
Publication statusPublished - 2020
SeriesLecture Notes in Computer Science


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