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Processing large-scale multi-dimensional data In parallel and distributed environments

机译:在并行和分布式环境中处理大规模多维数据

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摘要

Analysis of data is an important step in understanding and solving a scientific problem. Analysis involves extracting the data of interest from all the available raw data in a dataset And processing it into a data product however, in many areas of science and engineering, A scientist's ability to analyze information is increasingly becoming hindered by dataset sizes. The vast amount of data in scientific datasets makes it a difficult task to efficiently access the Data of interest, and manage potentially heterogeneous system resources to process the data. Subsetting and aggregation are common operations executed in a wide rage of data-intensive Application.
机译:数据分析是理解和解决科学问题的重要步骤。分析涉及从数据集中所有可用的原始数据中提取感兴趣的数据,并将其处理为数据产品,但是,在科学和工程学的许多领域,科学家分析信息的能力越来越受到数据集大小的限制。科学数据集中的大量数据使高效访问感兴趣的数据以及管理潜在的异构系统资源来处理数据变得十分困难。子集和聚合是在大量数据密集型应用程序中执行的常见操作。

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