Bounded Pattern Matching Using Views

Wang, Xin and Wang, Yang and Zhang, Ji and Zhu, Yan (2020) Bounded Pattern Matching Using Views. In: 31st International Conference on Database and Expert Systems Applications (DEXA 2020), 14–17 Sept 2020, Bratislava, Slovakia.


Abstract

Bounded evaluation using views is to compute the answers Q(D) to a query Q in a dataset D by accessing only cached views and a small fraction DQ of D such that the size |DQ| of DQ and the time to identify DQ are independent of |D|, no matter how big D is. Though proven effective for relational data, it has yet been investigated for graph data. In light of this, we study the problem of bounded pattern matching using views. We first introduce access schema C for graphs and propose a notion of joint containment to characterize bounded pattern matching using views. We show that a pattern query Q can be boundedly evaluated using views V(G) and a fraction GQ of G if and only if the query Q is jointly contained by V and C. Based on the characterization, we develop an efficient algorithm as well as an optimization strategy to compute matches by using V(G) and GQ. Using real-life and synthetic data, we experimentally verify the performance of these algorithms, and show that (a) our algorithm for joint containment determination is not only effective but also efficient; and (b) our matching algorithm significantly outperforms its counterpart, and the optimization technique can further improve performance by eliminating unnecessary input.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 -)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 -)
Date Deposited: 22 Feb 2021 03:29
Last Modified: 26 Feb 2021 04:18
Uncontrolled Keywords: Graph data; Improve performance; Matching algorithm; Optimization strategy; Optimization techniques; Pattern query; Relational data; Synthetic data
Fields of Research (2008): 08 Information and Computing Sciences > 0804 Data Format > 080403 Data Structures
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4605 Data management and data science > 460503 Data models, storage and indexing
46 INFORMATION AND COMPUTING SCIENCES > 4605 Data management and data science > 460505 Database systems
Identification Number or DOI: https://doi.org/10.1007/978-3-030-59003-1_19
URI: http://eprints.usq.edu.au/id/eprint/41395

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