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Querying in a Workload-Aware Triplestore Based on NoSQL Databases

机译:基于NoSQL数据库查询工作负载感知三平段

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RDF and SPARQL are increasingly used in a broad range of information management, scenarios (e.g., governments, corporations, and startups). Scalable SPARQL querying has been the main issue for virtually all the recent RDF triplestores. This paper presents WA-RDF, a middleware that addresses workload-adaptive management of large RDF graphs. Our middleware not only employs all the most used NoSQL data models but also provides a novel RDF data partitioning approach based on a fragmentation strategy that maps RDF data into multiple NoSQL databases. 'Phis workload-aware partitioning scheme provides, in turn, efficient processing of SPARQL queries over these NoSQL databases. Our experimental evaluation shows that the solution is promising, outperforming three recent baselines.
机译:RDF和SPARQL越来越多地用于广泛的信息管理,场景(例如,政府,公司和初创公司)。可扩展的SPARQL查询是几乎所有最近的RDF三平台的主要问题。本文介绍了WA-RDF,一个中间件,用于解决大型RDF图的工作负载 - 自适应管理。我们的中间件不仅采用了所有最常用的NoSQL数据模型,还可以基于将RDF数据映射到多个NoSQL数据库的碎片策略来提供新的RDF数据分区方法。 'PHIS工作负载感知分区方案依次提供这些NoSQL数据库的SparQL查询的高效处理。我们的实验评价表明,该解决方案很有前景,优于最近的三个基线。

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