Abstract
Brick is a recently proposed metadata schema and ontology for describing building components and the relationships between them. It represents buildings as directed labeled graphs using the RDF data model. Using the SPARQL query language, building-agnostic applications query a Brick graph to discover the set of resources and relationships they require to operate. Latency-sensitive applications, such as user interfaces, demand response, and model-predictive control, require fast queries—conventionally less than 100ms.
We benchmark a set of popular open source and commercial SPARQL databases against three real Brick models using seven application queries and find that none of them meet this performance target. This lack of performance can be attributed to design decisions that optimize for queries over large graphs consisting of billions of triples but give poor spatial locality and join performance on the small dense graphs typical of Brick. We present the design and evaluation of HodDB, a RDF/SPARQL database for Brick built over a node-based index structure. HodDB performs Brick queries 3--700× faster than leading SPARQL databases and consistently meets the 100ms threshold, enabling the portability of important latency-sensitive building applications.
This article is an extension of a previously published work [16].
- RDF Concepts Namespace. 1999. Retrieved from http://www.w3.org/1999/02/22-rdf-syntax-ns#.Google Scholar
- RDF Schema Namespace. 2000. Retrieved from https://www.w3.org/2000/01/rdf-schema#.Google Scholar
- The Go Programming Language. 2017. Retrieved from https://golang.org/.Google Scholar
- Jans Aasman. 2008. Unification of geospatial reasoning, temporal logic, 8 social network analysis in event-based systems. In Proceedings of the Second International Conference on Distributed Event-Based Systems. ACM, 139--145. Google ScholarDigital Library
- Michael P. Andersen and David E. Culler. 2016. BTrDB: Optimizing storage system design for timeseries processing. In Proceedings of the 14th USENIX Conference on File and Storage Technologies (FAST’16). Google ScholarDigital Library
- Grigoris Antoniou and Frank Van Harmelen. 2004. Web ontology language: Owl. In Handbook on Ontologies. Springer, 67--92.Google Scholar
- Bharathan Balaji, Arka Bhattacharya, Gabriel Fierro, Jingkun Gao, Joshua Gluck, Dezhi Hong, Aslak Johansen, Jason Koh, Joern Ploennigs, Yuvraj Agarwal, et al. 2016. Brick: Towards a unified metadata schema for buildings. In Proceedings of the ACM International Conference on Embedded Systems for Energy-Efficient Built Environments (BuildSys’16). ACM. Google ScholarDigital Library
- David Beckett, T. Berners-Lee, E. Prud’hommeaux, and G. Carothers. 2014. RDF 1.1 Turtle. In Proceedings of the World Wide Web Consortium (2014).Google Scholar
- Arka Bhattacharya, Joern Ploennigs, and David Culler. 2015. Short paper: Analyzing metadata schemas for buildings: The good, the bad, and the ugly. In Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments. ACM, 33--34. Google ScholarDigital Library
- Christian Bizer, Jens Lehmann, Georgi Kobilarov, Sören Auer, Christian Becker, Richard Cyganiak, and Sebastian Hellmann. 2009. DBpedia-A crystallization point for the web of data. Web Semant. 7, 3 (2009), 154--165. Google ScholarDigital Library
- Christian Bizer and Andreas Schultz. 2009. The berlin sparql benchmark. Retrieved from http://wifo5-03.informatik.uni-mannheim.de/bizer/berlinsparqlbenchmark/.Google Scholar
- Cayleygraph. 2017. Cayley. Retrieved from https://cayley.io.Google Scholar
- Leonidas Deligiannidis, Krys J. Kochut, and Amit P. Sheth. 2007. RDF data exploration and visualization. In Proceedings of the ACM 1st Workshop on CyberInfrastructure: Information Management in eScience. ACM, 39--46. Google ScholarDigital Library
- Inc Dgraph Labs. 2017. Dgraph. Retrieved from https://dgraph.io/index.html.Google Scholar
- Orri Erling and Ivan Mikhailov. 2009. RDF support in the Virtuoso DBMS. In Networked Knowledge-Networked Media. Springer, 7--24.Google Scholar
- Gabriel Fierro and David E. Culler. 2017. Design and analysis of a query processor for brick. In Proceedings of the ACM International Conference on Embedded Systems for Energy-Efficient Built Environments (BuildSys’17). ACM. Google ScholarDigital Library
- Franz Inc. 2017. AllegroGraph: Semantic Graph Database. Retrieved from https://allegrograph.com/allegrograph/.Google Scholar
- Flavius Frasincar, Alexandru Telea, and Geert-Jan Houben. 2006. Adapting graph visualization techniques for the visualization of RDF data. In Visualizing the Semantic Web. Springer, 154--171.Google Scholar
- Sadayuki Furuhashi. 2017. MessagePack: It’s like JSON. but fast and small, 2014. Retrieved from http://msgpack.org (2017).Google Scholar
- Google Inc. 2017. Badwolf. Retrieved from https://google.github.io/badwolf/.Google Scholar
- Steve Harris, Andy Seaborne, and Eric Prud’hommeaux. 2013. SPARQL 1.1 query language. W3C Recommend. 21, 10 (2013).Google Scholar
- Andreas Harth and Stefan Decker. 2005. Optimized index structures for querying rdf from the web. In Proceedings of the 3rd Latin American Web Congress (LA-WEB’05). IEEE. Google ScholarDigital Library
- Philipp Heim, Sebastian Hellmann, Jens Lehmann, Steffen Lohmann, and Timo Stegemann. 2009. RelFinder: Revealing relationships in RDF knowledge bases. In International Conference on Semantic and Digital Media Technologies. Springer, 182--187. Google ScholarDigital Library
- Ora Lassila and Ralph R. Swick. 1999. Resource Description Framework (RDF) Model and Syntax Specification. Recommendation 22 February 1999 REC-rdf-syntax-19990222. W3C, Cambridge, MA. http://www.w3.org/TR/REC-rdf-syntax/.Google Scholar
- Kamesh Madduri and Kesheng Wu. 2011. Massive-scale RDF processing using compressed bitmap indexes. In Proceedings of the International Conference on Scientific and Statistical Database Management. Springer, 470--479. Google ScholarDigital Library
- Dirk Merkel. 2014. Docker: Lightweight linux containers for consistent development and deployment. Linux J. 2014, 239 (2014), 2. Google ScholarDigital Library
- George A. Miller. 1995. WordNet: A lexical database for English. Commun. ACM 38, 11 (1995), 39--41. Google ScholarDigital Library
- Mohamed Morsey, Jens Lehmann, Sören Auer, and Axel-Cyrille Ngonga Ngomo. 2011. DBpedia SPARQL benchmark--performance assessment with real queries on real data. In International Semantic Web Conference. Springer, 454--469. Google ScholarDigital Library
- Neo Technology Inc. 2017. Neo4j. Retrieved from https://neo4j.com/.Google Scholar
- Thomas Neumann and Gerhard Weikum. 2008. RDF-3X: A RISC-style engine for RDF. Proc. VLDB Endow. 1, 1 (2008), 647--659. Google ScholarDigital Library
- Jakob Nielsen. 1994. Usability Engineering. Elsevier.Google ScholarDigital Library
- Natalya F. Noy, Michael Sintek, Stefan Decker, Monica Crubézy, Ray W. Fergerson, and Mark A. Musen. 2001. Creating semantic web contents with protege-2000. IEEE Intell. Syst. 16, 2 (2001), 60--71. Google ScholarDigital Library
- Harshal Patni, Cory Henson, and Amit Sheth. 2010. Linked sensor data. In Proceedings of the 2010 International Symposium on Collaborative Technologies and Systems (CTS’10). IEEE, 362--370.Google ScholarCross Ref
- Mary Ann Piette, Sila Kiliccote, and Girish Ghatikar. 2014. Field experience with and potential for multi-time scale grid transactions from responsive commercial buildings. In ACEEE Summer Study on Energy Efficiency in Buildings. Asilomar Convention Center, Pacific Grove, CA.Google Scholar
- Eric Prud'hommeaux and Andy Seaborne. SPARQL Query Language for RDF. Technical Report. http://www.w3.org/TR/rdf-sparql-query/.Google Scholar
- Marko A. Rodriguez. 2015. The gremlin graph traversal machine and language (invited talk). In Proceedings of the 15th Symposium on Database Programming Languages. ACM, 1--10. Google ScholarDigital Library
- Craig Sayers. 2004. Node-centric rdf graph visualization. http://www.hpl.hp.com/techreports/2004/HPL-2004-60.pdf.Google Scholar
- Michael Schmidt, Thomas Hornung, Georg Lausen, and Christoph Pinkel. 2009. SP2Bench: A SPARQL performance benchmark. In Proceedings of the IEEE 25th International Conference on Data Engineering (ICDE’09). IEEE, 222--233. Google ScholarDigital Library
- OpenLink Software. 2017. Virtuoso. Retrieved from https://virtuoso.openlinksw.com/download/.Google Scholar
- Markus Stocker, Andy Seaborne, Abraham Bernstein, Christoph Kiefer, and Dave Reynolds. 2008. SPARQL basic graph pattern optimization using selectivity estimation. In Proceedings of the 17th International Conference on World Wide Web. ACM, 595--604. Google ScholarDigital Library
- SYSTAP, LLC. 2017. Bigdata Database Architecture Whitepaper. Retrieved from https://www.blazegraph.com/whitepapers/bigdata_architecture_whitepaper.pdf.Google Scholar
- SYSTAP, LLC. 2017. blazegraph. Retrieved from https://www.blazegraph.com/.Google Scholar
- The Apache Software Foundation. 2017. A free and open source Java framework for building semantic web and linked data applications. Retrieved from https://jena.apache.org/ (2017).Google Scholar
- The Apache Software Foundation. 2017. High performance Triple Datastore. Retrieved from https://jena.apache.org/documentation/tdb/.Google Scholar
- The RDFLib Team. 2017. RDFLib. Retrieved from https://rdflib.readthedocs.io/en/stable/.Google Scholar
- TopQuadrant. 2017. TopBraid Live. Retrieved from http://www.topquadrant.com/products/topbraid-live/.Google Scholar
- Kesheng Wu, Sean Ahern, E. Wes Bethel, Jacqueline Chen, Hank Childs, Estelle Cormier-Michel, Cameron Geddes, Junmin Gu, Hans Hagen, Bernd Hamann, et al. 2009. FastBit: Interactively searching massive data. In Journal of Physics: Conference Series, Vol. 180. IOP Publishing, 012053.Google Scholar
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