Title: Planning operators of concurrent RDF stream processing queries

Authors: Sejin Chun; Seungjun Yoon; Jooik Jung; Kyong-Ho Lee

Addresses: Department of Computer Science, Yonsei University, 134 Shinchon-dong, Sudaemoon-ku, Seoul 120-749, South Korea ' Department of Computer Science, Yonsei University, 134 Shinchon-dong, Sudaemoon-ku, Seoul 120-749, South Korea ' Department of Computer Science, Yonsei University, 134 Shinchon-dong, Sudaemoon-ku, Seoul 120-749, South Korea ' Department of Computer Science, Yonsei University, 134 Shinchon-dong, Sudaemoon-ku, Seoul 120-749, South Korea

Abstract: RDF stream processing (RSP), which aims to query data streams and linked datasets using common data model and query languages extended from RDF and SPARQL, is gaining popularity. However, most of the existing RSP engines do not provide any optimisation techniques for shared join operators among query plans from concurrent queries. Many number of shared join operators can incur the waste of a lot of CPU resources like a processing memory. Moreover, queries on shared operators cause a slow response time because they must be re-evaluated without reusing intermediate results. To solve these problems, we propose an efficient method of optimising query plans on multiple queries. First, the proposed method evicts some data that get notified from the streams in order to maintain an efficient memory usage. Second, the proposed method optimises query plans to maximise the reuse of shared join results. Experimental results show that the proposed method has significant improvements in terms of memory consumption and latency, compared to the state-the-of-art methods.

Keywords: resource description framework; RDF; semantic web; SPARQL; stream processing; distributed processing; operator planning.

DOI: 10.1504/IJWGS.2019.10017543

International Journal of Web and Grid Services, 2019 Vol.15 No.1, pp.93 - 117

Received: 06 Aug 2017
Accepted: 29 May 2018

Published online: 15 Nov 2018 *

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