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Storing and Querying Semantic Data in the Cloud

机译:在云中存储和查询语义数据

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摘要

In the last years, huge RDF graphs with trillions of triples were created. To be able to process this huge amount of data, scalable RDF stores are used, in which graph data is distributed over compute and storage nodes for scaling efforts of query processing and memory needs. The main challenges to be investigated for the development of such RDF stores in the cloud are: (ⅰ) strategies for data placement over compute and storage nodes, (ⅱ) strategies for distributed query processing, and (ⅲ) strategies for handling failure of compute and storage nodes. In this manuscript, we give an overview of how these challenges are addressed by scalable RDF stores in the cloud.
机译:在过去的几年中,创建了具有三万亿个三元组的巨大RDF图。为了能够处理大量数据,使用了可伸缩的RDF存储,其中图形数据分布在计算和存储节点上,以扩展查询处理和内存需求的工作量。在云中开发此类RDF存储所要研究的主要挑战是:(ⅰ)在计算和存储节点上放置数据的策略,(ⅱ)分布式查询处理策略,以及(ⅲ)处理计算失败的策略和存储节点。在本手稿中,我们概述了如何通过云中的可伸缩RDF存储解决这些挑战。

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  • 会议地点 Esch-sur-Alzette(LU)
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    Daniel Janke; Steffen Staab;

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    Institute for Web Science and Technologies Universitaet Koblenz-Landau Koblenz Germany;

    Institute for Web Science and Technologies Universitaet Koblenz-Landau Koblenz Germany Web and Internet Science Group University of Southampton Southampton UK;

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