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Exchange and Consumption of Huge RDF Data

机译:交换和消耗大量RDF数据

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Huge RDF datasets are currently exchanged on textual RDF formats, hence consumers need to post-process them using RDF stores for local consumption, such as indexing and SPARQL query. This results in a painful task requiring a great effort in terms of time and computational resources. A first approach to lightweight data exchange is a compact (binary) RDF serialization format called HDT. In this paper, we show how to enhance the exchanged HDT with additional structures to support some basic forms of SPARQL query resolution without the need of "unpacking" the data. Experiments show that i) with an exchanging efficiency that outperforms universal compression, ii) post-processing now becomes a fast process which iii) provides competitive query performance at consumption.
机译:当前,大量的RDF数据集以文本RDF格式进行交换,因此,消费者需要使用RDF存储对它们进行后处理,以供本地使用,例如索引和SPARQL查询。这导致痛苦的任务,需要大量的时间和计算资源。轻量级数据交换的第一种方法是称为HDT的紧凑(二进制)RDF序列化格式。在本文中,我们展示了如何使用其他结构来增强交换的HDT,以支持一些基本形式的SPARQL查询解析,而无需“拆包”数据。实验表明,i)交换效率优于通用压缩,ii)后处理现在成为一种快速过程,iii)消耗时提供具有竞争力的查询性能。

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