S2X: graph-parallel querying of RDF with GraphX
Abstract: RDF has constantly gained attention for data publishing due to its flexible data model, raising the need for distributed querying. However, existing approaches using general-purpose cluster frameworks employ a record-oriented perception of RDF ignoring its inherent graph-like structure. Recently, GraphX was published as a graph abstraction on top of Spark, an in-memory cluster computing system. It allows to seamlessly combine graph-parallel and data-parallel computation in a single system, an unique feature not available in other systems. In this paper we introduce S2X, a SPARQL query processor for Hadoop where we leverage this unified abstraction by implementing basic graph pattern matching of SPARQL as a graph-parallel task while other operators are implemented in a data-parallel manner. To the best of our knowledge, this is the first approach to combine graph-parallel and data-parallel computation for SPARQL querying of RDF data based on Hadoop
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Edition
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Postprint
- Language
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Englisch
- Notes
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Wang F., Luo G., Weng C., Khan A., Mitra P., Yu C. (eds) Biomedical Data Management and Graph Online Querying. Big-O(Q) 2015, DMAH 2015. Lecture Notes in Computer Science, vol 9579, isbn: 978-3-319-41575-8
cc_by_nc_nd http://creativecommons.org/licenses/by-nc-nd/4.0/deed.de cc
- Classification
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Informatik
- Keyword
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Hadoop
RDF
SPARQL
Semantic Web
- Event
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Veröffentlichung
- (where)
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Freiburg
- (who)
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Universität
- (when)
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2016
- Creator
- DOI
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10.1007/978-3-319-41576-5_12
- URN
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urn:nbn:de:bsz:25-freidok-122783
- Rights
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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25.03.2025, 1:55 PM CET
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
Time of origin
- 2016
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Identifying, Relating, Consisting and Querying Large Heterogeneous RDF Sources
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Distributed RDF Querying on Hadoop
S2RDF: RDF querying with SPARQL on spark
Efficient management and querying of RDF data in a P2P framework : = Effiziente Verwaltung und Abfrage von RDF-Daten in einem P2P-Rahmen
Distributed querying of large labeled graphs
Querying RDF Streams with C-SPARQL
RDFPath: path query processing on large RDF graphs with MapReduce
RDF2Vec: RDF graph embeddings for data mining
OER4SDI - Aufbau einfacher RDF-Graphen (KG 1)
Collaborative graph exploration
RDF graph embeddings for content-based recommender systems
Identifying, Relating, Consisting and Querying Large Heterogeneous RDF Sources
Robust graph-based localization and mapping : = Robuste Graph-basierte Lokalisierung und Kartierung
Distributed RDF Querying on Hadoop
S2RDF: RDF querying with SPARQL on spark
Efficient management and querying of RDF data in a P2P framework : = Effiziente Verwaltung und Abfrage von RDF-Daten in einem P2P-Rahmen
Distributed querying of large labeled graphs
Querying RDF Streams with C-SPARQL
RDFPath: path query processing on large RDF graphs with MapReduce
RDF2Vec: RDF graph embeddings for data mining
OER4SDI - Aufbau einfacher RDF-Graphen (KG 1)
Collaborative graph exploration
RDF graph embeddings for content-based recommender systems
Identifying, Relating, Consisting and Querying Large Heterogeneous RDF Sources