To counter societal and economic problems caused by data silos on the Web, efforts such as Solid strive to reclaim private data by storing it in permissioned documents over a large number of personal vaults across the Web. Building applications on top of such a decentralized Knowledge Graph involves significant technical challenges: centralized aggregation prior to query processing is excluded for legal reasons, and current federated querying techniques cannot handle this large scale of distribution at the expected performance. We propose an extension to Link Traversal Query Processing (LTQP) that incorporates structural properties within decentralized environments to tackle their unprecedented scale. In this article, we analyze the structural properties of the Solid decentralization ecosystem that are relevant for query execution, and provide the SolidBench benchmark to simulate Solid environments representatively. We introduce novel LTQP algorithms leveraging these structural properties, and evaluate their effectiveness. Our experiments indicate that these new algorithms obtain accurate results in the order of seconds for non-complex queries, which existing algorithms cannot achieve. Furthermore, we discuss limitations with respect to more complex queries. This work reveals that a traversal-based querying method using structural assumptions can be effective for large-scale decentralization, but that advances are needed in the area of query planning for LTQP to handle more complex queries. These insights open the door to query-driven decentralized applications, in which declarative queries shield developers from the inherent complexity of a decentralized landscape.
翻译:为了应对网上数据仓造成的社会和经济问题,我们努力争取将私人数据储存在网上大量个人保险库的允许文档中,从而将私人数据存储在网上大量个人保险库中。 在这种分散式知识图之上建立应用程序涉及巨大的技术挑战:由于法律原因,在查询处理之前排除集中汇总,而目前联邦化的查询技术无法在预期业绩中处理如此大规模的分发。我们提议扩展将结构特性纳入分散式环境的结构性特性,以解决其前所未有的规模。在本篇文章中,我们分析了用于查询执行的固体分权生态系统的结构特性,并为模拟固体环境提供了固体Bench基准。我们引入了利用这些结构特性的新型LTQP算法,并评估了其有效性。我们的实验表明,这些新的算法在时间顺序上取得了准确的结果,用于不兼容的查询,而现有的算法无法实现。此外,我们讨论了与更复杂的分权化环境查询的局限性。在更复杂的分权化环境中,我们分析了与结构假设相关的分权化生态系统的结构性查询方法,为有代表性的模拟环境环境环境环境环境环境模拟提供了一种基准。我们采用了新的LTQ算算算法的算方法,这些新的算式的分权化查询,这些分权化式的分权化查询是更复杂的分权化式的分权化式的分权式的查询,对于大规模的分权化式的查询的分权化的分权化的分权化式的查询,这些分权式式式的查询的查询是用于对方向式的分权化的查询的查询的查询的查询,这些分权式的分权式的分权化式的分权化式的查询的查询的分权的查询的查询的分权式的查询的查询的分权式查询的查询的查询,对于大的分权式的分权的分权的分权的分向方向的查询的查询,对于方向的分向的分向的查询,对于方向的查询的查询需要是,对于大的分权式的查询的查询的分权式的分权式查询的查询的查询是,对于分级式的查询的分向式的查询的分级式查询的分级式查询是比较的分向的分向的分向的分向的分向的分向的分向的分权式查询的分向