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Constructing Event Processing Systems of Layered and Heterogeneous Events with SPARQL

机译:用SPARQL构建分层和异构事件的事件处理系统

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SPARQL was originally developed to process queries over finite-length datasets encoded as RDF graphs. Processing of infinite data streams can be enabled through continuous incremental evaluation of an incoming event stream. SPARQL Update provides tools for interconnecting queries, enabling event processing applications to be constructed out of multiple incrementally processed collaborating rules. These rule networks can perform event processing on heterogeneous event structures. Heterogeneous event support combined with the capability to synthesise new events enables the creation of layered event processing networks. In this paper, we review the different types of complex event processing building blocks presented in the literature and show their translations to SPARQL Update rules through examples, supporting a modular and layered approach. The interconnected examples demonstrate the creation of an elaborate network for solving event processing tasks. The performance of the example event processing network is verified on the Instans platform.
机译:SPARQL最初开发用于处理对编码为RDF图的有限长度数据集的查询。可以通过对传入事件流进行连续增量评估来启用无限数据流的处理。 SPARQL Update提供了用于互连查询的工具,使事件处理应用程序可以从多个增量处理的协作规则中构建。这些规则网络可以对异构事件结构执行事件处理。异构事件支持与综合新事件的能力相结合,可以创建分层的事件处理网络。在本文中,我们回顾了文献中介绍的不同类型的复杂事件处理构建基块,并通过示例说明了它们对SPARQL Update规则的翻译,并支持模块化和分层方法。相互关联的示例演示了如何创建复杂的网络来解决事件处理任务。示例事件处理网络的性能在Instans平台上得到了验证。

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