TY - GEN
T1 - TriAG
T2 - 2020 10th International Workshop on Computer Science and Engineering, WCSE 2020
AU - Pang, Jinhui
AU - Wang, Shujun
AU - Jiao, Jie
AU - Zhou, Weikang
AU - Feng, Fan
AU - Zhang, Ding
N1 - Publisher Copyright:
© WCSE 2020.
PY - 2020
Y1 - 2020
N2 - In this paper, we present a new RDF engine accelerated by GPU, named TriAG, to query the RDF graph efficiently. Firstly, to improve the processing efficiency of SPARQL on RDF, new storage models of RDF systems is proposed. Then we use query decomposition to further reduce the query response time; at the same time, a cost model based on machine learning is used to determine the granularity of query decomposition. After this, we develop a MapReduce-based algorithm to join solutions of SPARQL subqueries in a parallel way. Finally, we implement TriAG and evaluate it by comparing it with two popular SPARQL query engines, namely, gStore and RDF3X on the LUBM benchmark. The experiments demonstrate that TriAG is highly efficient and effective.
AB - In this paper, we present a new RDF engine accelerated by GPU, named TriAG, to query the RDF graph efficiently. Firstly, to improve the processing efficiency of SPARQL on RDF, new storage models of RDF systems is proposed. Then we use query decomposition to further reduce the query response time; at the same time, a cost model based on machine learning is used to determine the granularity of query decomposition. After this, we develop a MapReduce-based algorithm to join solutions of SPARQL subqueries in a parallel way. Finally, we implement TriAG and evaluate it by comparing it with two popular SPARQL query engines, namely, gStore and RDF3X on the LUBM benchmark. The experiments demonstrate that TriAG is highly efficient and effective.
KW - GPU
KW - RDF
KW - SPARQL
UR - http://www.scopus.com/inward/record.url?scp=85092336174&partnerID=8YFLogxK
U2 - 10.18178/wcse.2020.06.045
DO - 10.18178/wcse.2020.06.045
M3 - Conference contribution
AN - SCOPUS:85092336174
T3 - WCSE 2020: 2020 10th International Workshop on Computer Science and Engineering
SP - 300
EP - 306
BT - WCSE 2020
PB - International Workshop on Computer Science and Engineering (WCSE)
Y2 - 19 June 2020 through 21 June 2020
ER -