SPARTex: A Vertex-Centric Framework for RDF Data Analytics

Handle URI:
http://hdl.handle.net/10754/581344
Title:
SPARTex: A Vertex-Centric Framework for RDF Data Analytics
Authors:
Abdelaziz, Ibrahim; Harbi, Raze; Salihoglu, Semih; Kalnis, Panos ( 0000-0002-5060-1360 ) ; Mamoulis, Nikos
Abstract:
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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Journal:
Proceedings of the VLDB Endowment
Conference/Event name:
the 41st International Conference on Very Large Data Bases
Issue Date:
31-Aug-2015
Type:
Conference Paper
Additional Links:
http://www.vldb.org/pvldb/vol8/p1880-abdelaziz.pdf
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorAbdelaziz, Ibrahimen
dc.contributor.authorHarbi, Razeen
dc.contributor.authorSalihoglu, Semihen
dc.contributor.authorKalnis, Panosen
dc.contributor.authorMamoulis, Nikosen
dc.date.accessioned2015-10-28T13:40:11Zen
dc.date.available2015-10-28T13:40:11Zen
dc.date.issued2015-08-31en
dc.identifier.urihttp://hdl.handle.net/10754/581344en
dc.description.abstractA 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.en
dc.relation.urlhttp://www.vldb.org/pvldb/vol8/p1880-abdelaziz.pdfen
dc.rightsThis work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/. Obtain permission prior to any use beyond those covered by the license.en
dc.titleSPARTex: A Vertex-Centric Framework for RDF Data Analyticsen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalProceedings of the VLDB Endowmenten
dc.conference.dateAugust 31st - September 4th 2015en
dc.conference.namethe 41st International Conference on Very Large Data Basesen
dc.conference.locationKohala Coast, Hawaiien
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionStanford University, USAen
dc.contributor.institutionUniversity of Ioannina, Greeceen
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