Abstract: Methods for determining database management system server hardware requirements as a function of user-supplied transactions per second requirements, maximum processor utilization, and server type. Methods are also provided for determining workload requirements as a function of the expected transaction composition of the system including the expected transaction execution rate in transactions per second and the percent of total workload contribution by each statement. In one method, each transaction is further specified as a set of SQL statements each having a parameter list, where the workload contribution of each SQL statement is calculated as a function of the SQL statement parameter list.

Abstract: A method for calculating and recalculating hardware requirements for a database management system computer. One method includes establishing default values for hardware utilization limits such as percent utilization of processors or network interface cards. Working copies of the hardware utilization limits can be initialized to the default utilization limits. Workload requirements can be obtained from a human user. In one method, the workload requirements are obtained as transactions per second value. In another embodiment, the workload requirements are obtained as a detailed list of transactions, expected execution rate of those transactions, and the composition of those transactions, including SQL statement type and parameters upon which those statements operate. The hardware requirements are then calculated so as to be within the hardware utilization limits, and can include discrete numbers of required hardware components such as processors and network interface cards.

Abstract: Methods for calculating mass storage requirements for a relational database table including both data pages and index pages. The methods allow direct calculation of the data storage and index storage requirements for a data base table, the methods based in part on the page size, the record length, and the number of records. The database requirement can be increased by partial unavailability of pages and rows. The methods include methods for calculating the number of B-tree levels in the index or indexes. The methods avoid the need for interactive calculations of the required size for a database table starting from the number of records, record size, and page size.

Abstract: A computerized method enabling a user to specify and select a server for a database management system. The computerized method can include software modules for specifying the hardware required to handle the database and the transaction processing. The hardware required to handle the database such as the mass storage and memory can be estimated using either estimated or detailed inputs. When using the detailed inputs, the database composition of each table can be described in great detail, including details about the columns and rows. The hardware required to handle the transaction processing such as the number of processors and the LAN speed can be estimated using either the required transactions per second or the detailed SQL composition for each transaction. A comparator function can allow comparison between two systems in terms of performance ratios and price to performance ratios.

Abstract: Methods for calculating total mass storage requirements for a relational database table including database storage requirements, application and software requirements, system table requirements, scratch and sort requirements, log file requirements, and growth requirements. One method utilizes detailed inputs for each table and table index. Another method produces and utilizes estimates for the database and index requirements for all tables together. Methods can use input parameters including the page size, a fill factor, the log file space, the temporary space, the operating system and application software space, the system database space, the growth percent space, and the page file space. Some methods also take into account inputs such as the number of table, the amount of data, the average number of columns per row, the average row size, the percent of variable length columns, and the average variable length column size per table.

Abstract: A computerized method is disclosed which aids in the comparison of different computer systems according to their performance parameters under established or proprietary benchmark performance tables or databases. The method, particularly when implemented in executable code, allows system planners to conveniently make an accurate decision about what computer system will most efficiently meet their computing needs. System planners may also determine how much money is required for a marginal increase in performance. In this way, a system planner may consider whether the additional expenditures required to increase power or capacity across vendors results in a cost-effective increase, when compared against a less powerful but less expensive system.

Abstract: A selective, non-manual power controller provides the selective, non-manual power control of various components of a data processing equipment from and reports the power status of such components to a central location. As opposed to pass power controllers which were limited to powering on or off all of the computer equipment controlled by a given controlling element, this invention provides a non-manual capability for remotely powering on or off any one or more components of a system or systems in a selective manner and providing the power status thereof. By being able to selectively activate or deactivate any or all of the components of a data processing system, the ability to conserve electrical energy is optimized. In many cases, a single component or a set of components are not used for extended periods of time, such as an entire production period or at least a large portion of a production period.

Abstract: A centralized control unit for use in a multisystem data processing configuration to provide dynamic access to shared and non-shared peripheral subsystems is disclosed. This unit, known herein as a subsystem access unit (SAU) is able to remotely control one or more system's accessibility to peripheral subsystem's from a central location. It is able to provide this control with the capability of either allowing a peripheral subsystem to be concurrently accessed by more than one system or forcibly ensuring that the peripheral subsystem is exclusively accessible by only a single system.