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首页> 外文期刊>ACM transactions on sensor networks >Design and Analysis of a Query Processor for Brick
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Design and Analysis of a Query Processor for Brick

机译：砖查询处理器的设计与分析

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摘要

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 3-700x 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].
机译：Brick是最近提出的元数据架构和本体，用于描述建筑组件及其之间的关系。它使用RDF数据模型将建筑物表示为有向标记图。使用SPARQL查询语言，与建筑物无关的应用程序查询Brick图以发现它们需要操作的资源和关系集。对延迟敏感的应用程序（例如用户界面，需求响应和模型预测控制）需要快速查询（通常不到100毫秒）。我们使用7个应用程序查询和3个真实Brick模型，对一组流行的开源和商业SPARQL数据库进行了基准测试发现他们都没有达到这个绩效目标。这种性能不足的原因可归因于以下设计决策：这些设计决策针对包含数十亿个三元组的大型图进行了查询优化，但空间定位性较差，并且在Brick常见的小型密集图上的连接性能也不佳。我们介绍了HodDB的设计和评估，HodDB是用于Brick的RDF / SPARQL数据库，该数据库建立在基于节点的索引结构上。 HodDB执行Brick查询的速度比领先的SPARQL数据库快3-700倍，并且始终达到100ms的阈值，从而实现了对延迟敏感的重要建筑应用程序的可移植性。本文是对先前发表的工作的扩展[16]。

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