ATLAS: A Distributed File System for Spatiotemporal Data
ATLAS: A Distributed File System for Spatiotemporal Data
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DOI：
10.1145/3344341.3368802
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发表时间：
2019-12
期刊：
影响因子：
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通讯作者：
Daniel Rammer;S. Pallickara;S. Pallickara
中科院分区：
文献类型：
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作者：
Daniel Rammer;S. Pallickara;S. Pallickara
在几个域中生成的大部分数据都是地理标记的。这些数据也有与之相关的按时间顺序排列的组成部分。普遍的数据生成和收集工作导致数据量增加。这些数据有可能揭示有价值的见解。为了便于及时地进行这种知识提取，底层文件系统必须满足几个目标。在这项研究中，我们提出了阿特拉斯，专门为时空数据设计的分布式文件系统。Atlas包括几种适合执行大规模分析的功能：将分散与数据访问模式相结合，负载平衡存储，以及促进与Hadoop和Spark等分析引擎的互操作。我们的经验基准简介阿特拉斯的几个方面，并证明我们的方法的适用性。
A majority of the data generated in several domains is geotagged. These data also have a chronological component associated with them. Pervasive data generation and collection efforts have led to an increase in data volumes. These data hold the potential to unlock valuable insights. To facilitate such knowledge extraction in a timely manner, the underlying file system must satisfy several objectives. In this study, we present Atlas, a distributed file system designed specifically for spatiotemporal data. Atlas includes several capabilities that are suited for performing large-scale analyses: aligning dispersion with data access patterns, load balancing storage, and facilitating interoperation with analytical engines such as Hadoop and Spark. Our empirical benchmarks profile several aspects of Atlas, and demonstrate the suitability of our methodology.