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An adaptive projection strategy and its implementation in column stores

机译:Adaptive投影策略及其在列商店中的实现

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Tuple reconstruction is an important component in column-stores. Some well-known column-stores, such as C-Store, employ projection to support tuple reconstruction. This paper proposes an adaptive projection strategy and an implementation method for projection. The proposed strategy employs association analysis to a considerable amount of query accesses submitted by users to group attributes of a relation into various projections. The strategy makes selections of projections adaptive to usage behaviors of users. This paper implements projections using main indexes and jointing address mapping indexes. The main index stores all columns of a projection, therefore, the proposed storage pattern is a compromise pattern rather than pure column store. But, with the proposed storage structure, the system not only avoids reading unnecessary attribute columns to answer query, but also does tuple reconstruction. The address mapping index is used to locate fast tuples. Finally, the experimental results on benchmark data set SSB show that the proposed strategy and implementation method can improve significantly the performance of multicolumn queries.
机译:元组重建是列存储中的重要组成部分。一些众所周知的专栏商店,如C-Store,采用投影来支持元组重建。本文提出了一种自适应投影策略和投影的实现方法。拟议的策略采用关联分析对用户提交的相当数量的查询访问,以将关系的属性分为各种预测。该策略使选择适应用户的使用行为。本文使用主索引和连接地址映射索引实现投影。主要索引存储投影的所有列,因此,所提出的存储模式是折衷方型图案而不是纯列存储。但是,通过提出的存储结构,系统不仅避免读取不必要的属性列来回答查询,还可以进行元组重建。地址映射索引用于定位快速元组。最后,基准数据集SSB上的实验结果表明,所提出的策略和实施方法可以显着提高多块查询的性能。

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