Explosive growth in volume and complexity of data exacerbates the key challenge to effectively and efficiently manage data in a way that fundamentally improves the ease and efficacy of their use. Existing large-scale file systems rely on hierarchically structured namespace that leads to severe performance bottlenecks and renders it impossible to support real-time queries on multi-dimensional attributes. This paper proposes a novel semantic-sensitive scheme, called Rapport, to provide dynamic and adaptive namespace management and support complex queries. The basic idea is to build files’ namespace by utilizing their semantic correlation and exploiting dynamic evolution of attributes to support namespace management. Extensive tracedriven experiments validate the effectiveness and efficiency of our proposed schemes. To the best of our knowledge, this is the first work on semantic-sensitive namespace management for ultra-scale file systems.
Available at: http://works.bepress.com/yifeng_zhu/12/