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Method and system for adaptively building a static Ziv-Lempel dictionary for database compression

机译:自适应构建静态Ziv-Lempel词典进行数据库压缩的方法和系统

摘要

A system for creating a static data compression dictionary adapted to a hardware-based data compression architecture. A static Ziv- Lempel dictionary is created and stored in memory for use in compressing database records. No data compression occurs during dictionary construction. A fixed-size Ziv-Lempel parse-tree is adapted to database characteristics in one of two alternate ways. First, the parse-tree is overbuilt substantially and then pruned back to a static size by eliminating the least recently used (LRU) nodes having the lowest use count. Alternatively, the parse-tree is built to a static size and thereafter selected nodes are replaced with new nodes upon database sampling. This node recycling procedure chooses the least-useful nodes for replacement according to a use count and LRU strategy while exhausting the database sample. The pruned Ziv-Lempel parse-tree is then transformed to a static dictionary configuration and stored in memory for use in a hardware-based database compression procedure. Completion of the static dictionary before starting data compression eliminates the initial compression inefficiencies well-known for the Ziv-Lempel procedure. The parse-tree construction is enhanced by initializing the tree with NULL and DEFAULT sequences from database definitions before examining any data.
机译:一种用于创建适用于基于硬件的数据压缩体系结构的静态数据压缩字典的系统。将创建静态的Ziv-Lempel词典并将其存储在内存中,以用于压缩数据库记录。在字典构造过程中不会发生数据压缩。固定大小的Ziv-Lempel解析树以两种替代方式之一适应数据库特征。首先,对解析树进行实质性的过度构建,然后通过消除使用次数最少的最近最少使用(LRU)节点将其修剪为静态大小。或者,将分析树构建为静态大小,然后在数据库采样后将选定的节点替换为新的节点。该节点回收过程会在耗尽数据库样本的同时,根据使用次数和LRU策略选择最少用的节点进行替换。然后将修剪后的Ziv-Lempel解析树转换为静态字典配置,并将其存储在内存中,以用于基于硬件的数据库压缩过程。在开始数据压缩之前完成静态字典可以消除Ziv-Lempel程序众所周知的初始压缩效率低下的情况。通过在检查任何数据之前使用数据库定义中的NULL和DEFAULT序列初始化树来增强分析树的构造。

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