跟踪和绘制分布式数据来源

T. Malik, L. Nistor, Ashish Gehani
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引用次数: 33

摘要

当前的来源收集系统通常在远程主机上收集元数据,并将其提交给中央服务器。相比之下,一些数据密集型科学应用程序需要分散的体系结构,其中每个主机维护在该主机上收集的来源元数据的权威本地存储库。后一种方法允许系统以细粒度处理审计时生成的大量元数据,并允许用户保留对其来源记录的控制。然而,分散的体系结构增加了审计、跟踪和查询分布式来源的复杂性。我们描述了一个用于在分布式应用程序中捕获数据来源的系统,以及使用来源草图来优化后续的数据来源查询。从分布式工作流应用中收集数据的实验证明了分散式来源管理系统的可行性,并提高了来源查询的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tracking and Sketching Distributed Data Provenance
Current provenance collection systems typically gather metadata on remote hosts and submit it to a central server. In contrast, several data-intensive scientific applications require a decentralized architecture in which each host maintains an authoritative local repository of the provenance metadata gathered on that host. The latter approach allows the system to handle the large amounts of metadata generated when auditing occurs at fine granularity, and allows users to retain control over their provenance records. The decentralized architecture, however, increases the complexity of auditing, tracking, and querying distributed provenance. We describe a system for capturing data provenance in distributed applications, and the use of provenance sketches to optimize subsequent data provenance queries. Experiments with data gathered from distributed workflow applications demonstrate the feasibility of a decentralized provenance management system and improvements in the efficiency of provenance queries.
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