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Adaptively incremental dictionary compression method for column-oriented database

机译:针对列的数据库的自适应增量词典压缩方法

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As an efficient method, the dictionary compression approach has attracted much interest and been widely used in column-oriented database systems. The core idea is to represent a longer string by a shorter integer, which significantly reduces the size of data and then improves the input-output (I/O) performance. To further reduce the space overhead of the dictionary compression method based on static increment, a novel adaptively incremental dictionary compression encoding method is developed in this paper. The developed method makes full use of the statistical characteristics of the data to reduce the footprint of the dictionary in the memory, which is also shown more flexible in reality. Furthermore, a better performance of query execution can be obtained by the adoption of such compression method in the query plan. The simulation results under different experiments show the effectiveness and efficiency of our proposed method.
机译:作为一种有效的方法,字典压缩方法吸引了很多兴趣,并广泛用于面向列的数据库系统。核心思想是表示较短的整数的较长字符串,这显着降低了数据的大小,然后提高了输入输出(I / O)性能。为了进一步降低基于静态增量的字典压缩方法的空间开销,本文开发了一种新颖的自适应增量词典压缩编码方法。开发方法充分利用数据的统计特性,以减少内存中的字典的占地面积,这也是在现实中更加灵活的。此外,通过在查询计划中采用这种压缩方法可以获得更好的查询执行性能。不同实验下的仿真结果表明了我们所提出的方法的有效性和效率。

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