Partial replica selection for spatial datasets

Yun Tian, P. J. Rhodes
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引用次数: 6

Abstract

The implementation of partial or incomplete replicas, which represent only a subset of a larger dataset, has been an active topic of research. Partial Spatial Replicas extend this functionality to spatial data, allowing us to distribute a spatial dataset in pieces over several locations. Accessing only a subset of a spatial replica usually results in a large number of relatively small read requests made to the underlying storage device. For this reason, an accurate model of disk access is important when working with spatial subsets. We make two primary contributions in this paper. First, we describe a model for disk access performance that takes filesystem prefetching into account and is sufficiently accurate for spatial replica selection. Second, making a few simplifying assumptions, we propose a fast replica selection algorithm for partial spatial replicas. The algorithm uses a greedy approach that attempts to maximize performance by choosing a collection of replica subsets that allow fast data retrieval by a client machine. Experiments show that the performance of the solution found by our algorithm is on average always at least 91% and 93.4% of the performance of the optimal solution in 4-node and 8-node tests respectively.
空间数据集的部分副本选择
部分或不完整副本的实现仅代表较大数据集的一个子集,一直是研究的活跃主题。部分空间复制将此功能扩展到空间数据,允许我们将空间数据集分散到多个位置。只访问空间副本的一个子集通常会导致对底层存储设备发出大量相对较小的读请求。因此,在处理空间子集时,准确的磁盘访问模型非常重要。我们在本文中做出了两个主要贡献。首先,我们描述了一个磁盘访问性能模型,该模型考虑了文件系统预取,并且对于空间副本选择足够准确。其次,通过一些简化的假设,提出了一种局部空间副本的快速副本选择算法。该算法使用一种贪心方法,通过选择一组副本子集来实现性能最大化,从而允许客户端机器快速检索数据。实验表明,在4节点和8节点测试中,我们的算法找到的解的性能平均至少是最优解的91%和93.4%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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