Spar(k)ql: Spark GraphX上的SPARQL评估方法

2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW) Pub Date : 2016-08-01 DOI:10.1109/W-FiCloud.2016.48

G. Gombos, G. Rácz, A. Kiss

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引用次数: 5

摘要

RDF是一种灵活的数据表示模型。由于它的灵活性和简单性，它已经成为一个流行的框架，因此RDF数据的数量正在快速增长。通常，查询大量数据是一项严峻的挑战，对于RDF数据也是如此。在本文中，我们研究了如何评估分布式系统上的SPARQL查询。我们提出了一种使用GraphX图分析工具评估SPARQL查询的新方法。GraphX是建立在Spark之上的，Spark是一个用于分布式计算的内存数据处理系统。通过这个工具，我们成功地利用了主体-谓词-对象形式的RDF语句的类图结构。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Spar(k)ql: SPARQL Evaluation Method on Spark GraphX

RDF is a flexible data representation model. Due to its flexibility and simplicity it has become a popular framework, hence the amount of RDF data is increasing fast. Querying massive amount of data is a serious challenge in general and it is true for RDF data as well. In this paper we investigating how to evaluate SPARQL queries on a distributed system. We propose a novel method for evaluating SPARQL queries using the GraphX graph analytical tool. GraphX is built on the top of Spark that is an in-memory data processing system for distributive computation. With this tool we managed to utilize the graph-like structure of the RDF statements which are in form of subject-predicate-object.

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2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)

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