Efficient and Scalable SPARQL Query Processing with Transformed Table

Sheng Wei Huang, Chia Ho Yu, Ce-Kuen Shieh, Ming Fong Tsai

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

Resource Description Framework (RDF) is the core technology of Semantic Web and has been more and more popular in recent years. With the rapid growth of the RDF data, the TripleStore, which is the query engine and RDF data storage, requires more scalable and efficient technologies. To improve the scalability and the performance of triple query, which is called SPARQL query processing, MapReduce programming model and NoSQL database system such as HBase are well-known solutions for large scale data processing. However, in general case, the subject of a triple is regarded as RowKey in the table. In some queries, finding matched triple patterns is a time-consuming job. Therefore, we design another table with different storage schema called Transformed Table to reduce the time cost for read operation. The experimental results show that using Transformed Table can improve the triple query performance significantly.

原文English
主出版物標題2015 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2015
發行者Institute of Electrical and Electronics Engineers Inc.
頁面103-106
頁數4
ISBN(電子)9781479987603
DOIs
出版狀態Published - 2015 6月 11
事件2015 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2015 - New Orleans, United States
持續時間: 2015 3月 92015 3月 12

出版系列

名字2015 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2015

Other

Other2015 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2015
國家/地區United States
城市New Orleans
期間15-03-0915-03-12

All Science Journal Classification (ASJC) codes

  • 電氣與電子工程
  • 電腦網路與通信

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