DM数据库中大规模数据智能自适应压缩算法研究

DM数据库中存在大量冗余数据,需对其进行压缩处理。传统数据压缩算法大多只追求高压缩率,不能保证数据的完整性;且适用范围小。为此,提出一种新的DM数据库中大规模数据智能自适应压缩算法。给出算法涉及的相关术语,介绍了智能自适应最优消零压缩算法的压缩原理,给出位数因子、编码长度、最优位数因子、最短编码长度以及编码因子的计算过程。在不同时刻对采集的DM数据库中的数据进行排列,通过自适应最优消零压缩算法原理求出数据序列最小编码长度和对应的最优位数因子;依据最优位数因子完成对数据序列的消零计算与编码,删除时间冗余,获取压缩后数据。实验结果表明,所提算法压缩效率高,在保证压缩比的同时,能够保证压缩后数据的完整性,且适用范围广。

Research on adaptive compression algorithm for large scale data in DM database

There are a lot of redundant data in DM database, so it needs to be compressed. Most traditional data compression algorithms only pursue high compression rate, can not guarantee the integrity of the data, and the scope of application is small. For this reason, a new algorithm of large scale data intelligent adaptive compression in DM database is proposed. Terminology of algorithm involved, introduces the intelligent adaptive optimal zero compression principle, given digit factor, encoding length, optimal number factor, the shortest encoding length and the encoding process factor calculation. At different times of the collected DM data in the database are arranged by the adaptive optimal zero compression algorithm principle to derive the optimal digit factor data sequence and the corresponding minimum encoding length, according to the optimal number zero factor calculation and elimination of encoding data sequence, delete time redundancy, compressed data acquisition. The experimental results show that the proposed algorithm has high compression efficiency, can guarantee the compression ratio, and can ensure the integrity of the compressed data.