使用统计估计的内存数据库优化

Sudhir Verma, Vidur S. Bhatnagar
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引用次数: 0

摘要

现有的字典压缩算法主要保留了直接访问的特性,从而严重影响了性能。在本文中,我们提出了一种谨慎的方法来格式化现有的字典表,以获得更好的性能水平,而不会失去直接访问。该方法基于减少字典列中未使用的空间,并适用于从统计数据派生的简单前提。本文在采用所提出的字典方法之后,进一步讨论了一种提高所创建的属性向量性能的技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In-Memory Database Optimization Using Statistical Estimation
Existing dictionary compression algorithms are notable to preserve the property of direct access, thereby leading to a severe hit in performance. In this paper, we propose a prudent approach to format the existing dictionary tables to achieve significantly better performance levels, without losing direct access. The approach is based on reducing the unused space in a dictionary column and works on simple premises derived from statistics. This paper further discusses a technique to improve performance of the attribute vector so created, after employing the proposed dictionary approach.
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