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Title: HodDB: Design and Analysis of a Query Processor for Brick.

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 modelpredictive 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 3-700x faster than leading SPARQL databases and consistently meets the 100ms threshold, enabling the portability of important latency-sensitive building applications.

Authors:
 [1];  [1]
  1. UC Berkeley
Publication Date:
Research Org.:
Regents of the University of California, Berkeley; California Institute for Energy and Environment
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Building Technologies Office (EE-5B)
Contributing Org.:
UC Berkeley
OSTI Identifier:
1420425
Report Number(s):
DOE-UCB-EE0007685-2
FOA-0001383 (BENEFIT)
DOE Contract Number:
EE0007685
Resource Type:
Conference
Resource Relation:
Journal Name: Proceedings of The 4th International Conference on Systems for Energy-Efficient Built Environments (BuildSys ‘17); Conference: BuildSys '17; Delft, The Netherlands; November 8–9, 2017
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; Smart Buildings, Building Management, Metadata, Graph Database, RDF, SPARQL

Citation Formats

Fierro, Gabriel, and Culler, David. HodDB: Design and Analysis of a Query Processor for Brick.. United States: N. p., 2017. Web.
Fierro, Gabriel, & Culler, David. HodDB: Design and Analysis of a Query Processor for Brick.. United States.
Fierro, Gabriel, and Culler, David. Wed . "HodDB: Design and Analysis of a Query Processor for Brick.". United States. doi:.
@article{osti_1420425,
title = {HodDB: Design and Analysis of a Query Processor for Brick.},
author = {Fierro, Gabriel and Culler, David},
abstractNote = {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 modelpredictive 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 3-700x faster than leading SPARQL databases and consistently meets the 100ms threshold, enabling the portability of important latency-sensitive building applications.},
doi = {},
journal = {Proceedings of The 4th International Conference on Systems for Energy-Efficient Built Environments (BuildSys ‘17)},
number = ,
volume = ,
place = {United States},
year = {Wed Nov 08 00:00:00 EST 2017},
month = {Wed Nov 08 00:00:00 EST 2017}
}

Conference:
Other availability
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