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.
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.