[논문]Distributed RDF store for efficient searching billions of triples based on Hadoop

Um, Jung-Ho; Lee, Seungwoo; Kim, Tae-Hong; Jeong, Chang-Hoo; Song, Sa-Kwang; Jung, Hanmin

doi:10.1007/s11227-016-1670-6

Distributed RDF store for efficient searching billions of triples based on Hadoop

The Journal of supercomputing, v.72 no.5, 2016년, pp.1825 - 1840

Um, Jung-Ho , Lee, Seungwoo , Kim, Tae-Hong , Jeong, Chang-Hoo , Song, Sa-Kwang , Jung, Hanmin

Abstract ▼ AI-Helper

As the development of IT and scientific technology, very large amounts of knowledge data are continuously being created and the big data era can be said to have arrived. Therefore, RDF store inserting and inquiring into knowledge bases has to be scaled up in order to deal with such large sources of data. To this end, we propose a scalable distributed RDF store based on a distributed database that uses bulk-loading for billions of triples to store data and to respond to user queries quickly. In order to achieve this purpose, we introduce a bulk-loading algorithm using the MapReduce framework and the SPARQL query processing engine to connect to a large distributed database. Experimental results show that the proposed bulk-loading algorithm achieves 67.893K triples per second to load approximately 33 billion triples. Therefore, the experiment proves proposed RDF store can manage billions of triples scale data.

참고문헌 (22)

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표제어: PCR

동의어: Packet Collision Rate

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용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

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Distributed RDF store for efficient searching billions of triples based on Hadoop

Abstract ▼ AI-Helper

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