In-Memory Parallel SPARQL Engine

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10363621" target="_blank" >RIV/00216208:11320/17:10363621 - isvavai.cz</a>

Result on the web

<a href="http://www.kbigdata.or.kr/bigdas2017/" target="_blank" >http://www.kbigdata.or.kr/bigdas2017/</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

In-Memory Parallel SPARQL Engine

Original language description

Contemporary semantic database engines support parallel computation of multiple queries. However, they do not apply parallelism to processing individual queries. In this paper, we propose decomposition of basic SPARQL operations to increase parallelism during the query evaluation. For efficient implementation, we use the combination of Bobox runtime and Bobolang streaming language. Using the frameworks, we implemented the in-memory SPARQL engine. According to our experiments, the engine achieves significant speed up on SMP and NUMA systems.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 4th International Conference on Big Data Applications and Services

ISBN

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ISSN

2466-135X

e-ISSN

neuvedeno

Number of pages

6

Pages from-to

229-234

Publisher name

Korea Big Data Service Society

Place of publication

Tashkent

Event location

Tashkent, Uzbekistan

Event date

Aug 15, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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