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A Data Reusing Strategy Based on Column-Stores

机译:基于列存储的数据重用策略

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摘要

Data reusing is an important way to save storage capacity and improve query efficiency in the management of massive data. The column-store architecture stores data from the same column continuously, which greatly improves the performance of 'read optimization' application and moreover increases the feasibility and flexibility of data reusing. In this paper, we propose a novel reusing method based on the column-store data warehouse. Firstly, we propose an improved iMAP method based on the schema mapping technique to generate as more candidate reusable columns as possible and then conduct further filter on these candidate data, which greatly reduces the complexity of reusable data detection. Based on the column-store architecture, we then propose the reuse implement at the storage layer. The method for query execution based on reusable data is provided finally. The experiment results conducted on the real data sets indicate that the presented strategy can reduce the storage space and query execution time efficiently.
机译:数据重用是节省存储容量并提高海量数据管理查询效率的重要方法。列存储体系结构连续存储来自同一列的数据,这极大地提高了“读取优化”应用程序的性能,并且还增加了数据重用的可行性和灵活性。本文提出了一种基于列存储数据仓库的重用方法。首先,我们提出了一种基于模式映射技术的改进的iMAP方法,以生成尽可能多的候选可重用列,然后对这些候选数据进行进一步过滤,从而大大降低了可重用数据检测的复杂度。然后,基于列存储体系结构,我们在存储层提出重用实现。最后提供了一种基于可重用数据的查询执行方法。在真实数据集上进行的实验结果表明,该策略可以有效地减少存储空间和查询执行时间。

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