Type
ArticleKAUST Department
Computer Science ProgramComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
InfoCloud Research Group
Date
2015-08Permanent link to this record
http://hdl.handle.net/10754/668634
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A growing number of applications require combining SPARQL queries with generic graph search on RDF data. However, the lack of procedural capabilities in SPARQL makes it inappropriate for graph analytics. Moreover, RDF engines focus on SPARQL query evaluation whereas graph management frameworks perform only generic graph computations. In this work, we bridge the gap by introducing SPARTex, an RDF analytics framework based on the vertex-centric computation model. In SPARTex, user-defined vertex centric programs can be invoked from SPARQL as stored procedures. SPARTex allows the execution of a pipeline of graph algorithms without the need for multiple reads/writes of input data and intermediate results. We use a cost-based optimizer for minimizing the communication cost. SPARTex evaluates queries that combine SPARQL and generic graph computations orders of magnitude faster than existing RDF engines. We demonstrate a real system prototype of SPARTex running on a local cluster using real and synthetic datasets. SPARTex has a real-time graphical user interface that allows the participants to write regular SPARQL queries, use our proposed SPARQL extension to declaratively invoke graph algorithms or combine/pipeline both SPARQL querying and generic graph analytics.Citation
Abdelaziz, I., Harbi, R., Salihoglu, S., Kalnis, P., & Mamoulis, N. (2015). SPARTex. Proceedings of the VLDB Endowment, 8(12), 1880–1883. doi:10.14778/2824032.2824091Publisher
VLDB EndowmentAdditional Links
https://dl.acm.org/doi/10.14778/2824032.2824091ae974a485f413a2113503eed53cd6c53
10.14778/2824032.2824091
Scopus Count
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