Abstract: System control over the logging of objects in order to meet the user specified recovery requirements. Under the fixed recovery time environment, the user chooses a length of time to be spent on object recovery, and the system dynamically manages the logging of objects to meet this time. The shorter the time the user chooses, the more objects the system will log, and the more performance degradation there will be as a result of the logging at run-time. The user may partition storage into Auxiliary Storage Pools (ASPs), which are groups of non-volatile storage, and then specify the recovery time on a per ASP basis. Under the minimal impact environment, the system dynamically manages the objects to be logged such that the object logging has a minimal impact on run-time performance.

Abstract: System control over the logging of objects in order to meet the user specified recovery requirements. Under the fixed recovery time environment, the user chooses a length of time to be spent on object recovery, and the system dynamically manages the logging of objects to meet this time. The shorter the time the user chooses, the more objects the system will log, and the more performance degradation there will be as a result of the logging at run-time. The user may partition storage into Auxiliary Storage Pools (ASPs), which are groups of non-volatile storage, and then specify the recovery time on a per ASP basis. Under the minimal impact environment, the system dynamically manages the objects to be logged such that the object logging has a minimal impact on run-time performance.

Abstract: An in use table manager in a computer system uses an in use table to track the use of files, or objects. The in use table is used to determine which objects may need recovery in the event of a system failure. Object addresses are hashed by the in use manager to identify a preferred slot in the table. The slots contain information identifying the object, and indicating the extent of use of the object. The in use manager assigns alternate slots, and dynamically changes the size of the in use table to reduce contention for slots. Several atomic operations on the table ensure integrity of the table, while permitting concurrent use. Portions of the table are bundled into single I/O operations to enhance system performance by minimizing I/O.

Abstract: Optimization I/O buffers are used to write data into or read data from auxiliary storage using a double buffering scheme. When a user wants to send data to auxiliary storage, the first buffer is filled with data and the contents are asynchronously written to auxiliary storage. Without waiting for the asynchronous write to complete, the second buffer is filled with data. When the second buffer is filled, the contents of the second buffer are asynchronously written to auxiliary storage. If the first buffer has not completed its write operation by this point, the buffers are determined to be too small and the size of both buffers is increased. Control switches back and forth between these two buffers until all of the desired data is sent to auxiliary storage. The size of the buffers is increased until the computer system does not have to synchronously wait for one buffer to complete its write operation before it can refill that buffer with new data.

Abstract: A quick recovery of logical files which provide alternate views of databases is provided. Unchanged logical file pages are journaled before being changed. Transactions affecting databases covered by the logical files are also journaled. To recover a logical file, the journaled unchanged pages of the logical file that correspond to the changed pages are inserted back into the logical file, and the transactions that were journaled are processed to provide the changes to the logical file and to the database. This brings the logical file and the underlying database up to date, and in synchronization with each other.

Abstract: A key estimator estimates the number of keys over a key range defined by key endpoints in an index to a data space. The number of keys in the key range required to be processed for a particular operation is estimated as a function of the number of pages referenced during a range level limited search. Two keys defining range endpoint keys are searched down to their lowest level in the tree. The level limit is then calculated as a function of desired granularity or accuracy of the estimate. The entire range of keys in the desired key range is then searched down to the level limit and the number of pages referenced during the search is counted and multiplied by an average key density per page to calculate the number of keys in the range.