Abstract: A logical backup of a database is performed that allows physical properties of the database to be preserved upon restore. The physical properties of the database include properties related to storage of the data on the hard disk. Preserving the physical properties of a database allows performance debugging of the source database by performing performance tests on the target database rather than a production system. Incremental backup of metadata of a database is performed to minimize execution of statements that provide the final configuration of the database. Incremental backup is performed by restoring a database using a full backup and applying incremental backups to reach a particular state. The user can inspect the restored database after applying each incremental backup to determine whether the database has reached a desired state.

Abstract: A database system performs hash join process for processing queries that join an inner and an outer database table. The hash join processes builds a hash table in memory for the inner table. The database system receives a limit on the memory for storing the hash table. The database system maximizes the number of partitions stored in memory for the hash table. If the hash table exceeds the limit of the memory while adding rows from the inner table, the database system selects a partition for spilling to a persistent storage. The partition selected for spilling to may be the largest partition or a partition larger than most of the partitions. The database system initializes the hash table to a number of partitions that is substantially equal to half of the total number of blocks that can be stored within the specified limit of memory for the hash table.

Abstract: A database system performs hash join process for processing queries that join an inner and an outer database table. The hash join processes builds a hash table in memory for the inner table. The database system receives a limit on the memory for storing the hash table. The database system maximizes the number of partitions stored in memory for the hash table. If the hash table exceeds the limit of the memory while adding rows from the inner table, the database system selects a partition for spilling to a persistent storage. The partition selected for spilling to may be the largest partition or a partition larger than most of the partitions. The database system initializes the hash table to a number of partitions that is substantially equal to half of the total number of blocks that can be stored within the specified limit of memory for the hash table.

Abstract: The present invention provides a compound of formula I 1

Abstract: The present invention provides a compound of formula I 1

Abstract: The present invention provides a compound of formula I 1

Abstract: 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.

Abstract: 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.