Power Grid Time Series Data Analysis with Pig on a Hadoop Cluster Compared to Multi Core Systems

F. Bach, H. Çakmak, H. Maass, U. Kühnapfel
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引用次数: 26

Abstract

In order to understand the dependencies in the power system we try to derive state information by combining high-rate voltage time series captures at different locations together with data analysis at different scales. This may enable large-scale simulation and modeling of the grid. Data captured by our recently introduced Electrical Data Recorders (EDR) and power grid simulation data are stored in the large scale data facility (LSDF) at Karlsruhe Institute of Technology (KIT) and growing rapidly in size. In this article we compare classic sequential multithreaded time series data processing to a distributed processing using Pig on a Hadoop cluster. Further we present our ideas for a better organization for our raw- and metadata that is indexable, searchable and suitable for big data.
与多核系统相比,在Hadoop集群上用Pig分析电网时间序列数据
为了了解电力系统中的依赖关系,我们试图通过将不同位置的高速率电压时间序列捕获与不同尺度的数据分析相结合来获得状态信息。这可能使网格的大规模模拟和建模成为可能。我们最近推出的电气数据记录仪(EDR)和电网模拟数据捕获的数据存储在卡尔斯鲁厄理工学院(KIT)的大型数据设施(LSDF)中,并且规模迅速增长。在本文中,我们将经典的顺序多线程时间序列数据处理与在Hadoop集群上使用Pig的分布式处理进行比较。此外,我们提出了我们的想法,为我们的原始数据和元数据提供一个更好的组织,可索引,可搜索,适合大数据。
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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