Extended Adaptive Join Operator with Bind-Bloom Join for Federated SPARQL Queries

Author:

Oguz Damla1,Yin Shaoyi2,Ergenç Belgin3,Hameurlain Abdelkader2,Dikenelli Oguz4

Affiliation:

1. Institute of Research in Computer Science of Toulouse (IRIT), Paul Sabatier University, Toulouse, France & Department of Computer Engineering, Izmir Institute of Technology, Izmir, Turkey & Department of Computer Engineering, Ege University, Izmir, Turkey

2. Institute of Research in Computer Science of Toulouse (IRIT), Paul Sabatier University, Toulouse, France

3. Department of Computer Engineering, Izmir Institute of Technology, Izmir, Turkey

4. Department of Computer Engineering, Ege University, Izmir, Turkey

Abstract

The goal of query optimization in query federation over linked data is to minimize the response time and the completion time. Communication time has the highest impact on them both. Static query optimization can end up with inefficient execution plans due to unpredictable data arrival rates and missing statistics. This study is an extension of adaptive join operator which always begins with symmetric hash join to minimize the response time, and can change the join method to bind join to minimize the completion time. The authors extend adaptive join operator with bind-bloom join to further reduce the communication time and, consequently, to minimize the completion time. They compare the new operator with symmetric hash join, bind join, bind-bloom join, and adaptive join operator with respect to the response time and the completion time. Performance evaluation shows that the extended operator provides optimal response time and further reduces the completion time. Moreover, it has the adaptation ability to different data arrival rates.

Publisher

IGI Global

Subject

Hardware and Architecture,Software

Reference41 articles.

1. Acosta, M., & Vidal, M.-E. (2015). Networks of linked data eddies: An adaptive Web query processing engine for RDF data. In The Semantic Web - ISWC 2015: 14th International Semantic Web Conference, Bethlehem, PA, USA (pp. 111–127). Springer International Publishing.

2. Babu, S., & Bizarro, P. (2005). Adaptive Query Processing in the Looking Glass. In CIDR 2005,Second Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA (pp. 238–249).

3. Avalanche: Putting the Spirit of the Web back into Semantic Web Querying.;C.Basca;Proceedings of the ISWC 2010 Posters & Demonstrations Track: Collected Abstracts,2010

4. Querying a messy web of data with Avalanche

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3