Abstract: A computer system executes a database management system (DBMS). The DBMS manages a database comprised of DBMS resources. The DBMS receives a request to be executed. The request is a DBMS action to be executed using the DBMS resources. The request includes a predicate specifying a maximum cost for executing the request, and a deadline, specifying a deadline by which the request is to be completed in its execution. The DBMS determines a plurality of workloads under which the request is qualified to execute. Each workload of the plurality of workloads includes a respective set of requests that have common characteristics. Each workload of the plurality of workloads includes a respective cost criterion and a respective elapsed time criterion. The DBMS selects a selected workload from among the plurality of workloads. The selected workload has a selected cost criterion and a selected elapsed time criterion. The DBMS begins execution of the request using the selected workload.

Abstract: A database system receives a query and determines that the query includes an inner join between a parent table and a child table. The database system determines that the following relationships exists between the parent table and the child table: referential integrity (“RI”) between a primary key attribute (pk) in the parent table and a foreign key attribute (fk) in the child table and a temporal relationship constraint (“TRC”) between a period attribute in the parent table and a TRC-attribute in the child table. The database system determines that the query satisfies non-temporal join elimination conditions and temporal join elimination conditions and that the query contains no other qualification conditions on the parent table's period attribute and eliminates the inner join when planning execution of the query.

Abstract: A database system receives a query to be processed. The database system has resources. A user assigns the query to a tier of resource allocation priorities in a hierarchy of tiers. The tier has been designated as being automatically managed by the database system. The tier has a plurality of levels of priority for resource allocation (LPRAs). The database system decomposes the query into a first step and a set of subsequent steps. The first step has a beginning and each of the set of subsequent steps has a respective beginning. The database system assigns the first step to a first LPRA, wherein executing the query at the first LPRA is projected by the database system to satisfy a service level goal (SLG) within a on_schedule_range of the SLG.

Abstract: A data-warehousing system allows various areas of an enterprise to view data at varying levels of data freshness. The system acquires data that represents an event in the life of a business enterprise, such as a transaction between the enterprise and one of its customers, and loads this data into a database table. The system then makes the data available for retrieval from the table and stores information indicating when the data was made available for retrieval. In some embodiments, the system also acquires data that is related to and more current than the data representing the event and stores the more current data in the database. The system then stores information indicating when the more current data was stored in the database. Such a data warehouse allows decision-makers in the business to see some information (e.g., customer transaction or account data) up-to-the-moment and other information as it stood at some specific point-in-time, such as at the end of the previous month.

Abstract: A database system includes an optimizer to generate resource estimates regarding execution of a request in the database system, and a regulator to monitor execution of a request and to adjust a priority level of the request based on the monitored execution and based on the resource estimates provided by the optimizer. The regulator is executable to further feed back statistics regarding execution of the request to the optimizer to improve accuracy of resource estimates provided by the optimizer.

Abstract: A query is received. It is determined that the query includes an inner join between a parent table and a child table. It is determined that the following relationships exist between the parent table and the child table: referential integrity (“RI”) between a primary key attribute (pk) in the parent table and a foreign key attribute (fk) in the child table, where “attribute” is defined to mean one or more columns, and a temporal relationship constraint (“TRC”) between a period attribute in the parent table and a TRC-attribute in the child table, the TRC-attribute being a date or time attribute. It is determined that the query does not access any attribute in the parent table other than the pk. It is determined that the query specifies an equality predicate of the form pk=fk. It is determined that the query selects a snapshot from the parent using a predicate of the form parent.[period attribute] contains a point in time (t1).

Abstract: A data-warehousing system allows various areas of an enterprise to view data at varying levels of data freshness. The system acquires data that represents an event in the life of a business enterprise, such as a transaction between the enterprise and one of its customers, and loads this data into a database table. The system then makes the data available for retrieval from the table and stores information indicating when the data was made available for retrieval. In some embodiments, the system also acquires data that is related to and more current than the data representing the event and stores the more current data in the database. The system then stores information indicating when the more current data was stored in the database. Such a data warehouse allows decision-makers in the business to see some information (e.g., customer transaction or account data) up-to-the-moment and other information as it stood at some specific point-in-time, such as at the end of the previous month.

Abstract: A data-warehousing system allows various areas of an enterprise to view data at varying levels of data freshness. The system acquires data that represents an event in the life of a business enterprise, such as a transaction between the enterprise and one of its customers, and loads this data into a database table. The system then makes the data available for retrieval from the table and stores information indicating when the data was made available for retrieval. In some embodiments, the system also acquires data that is related to and more current than the data representing the event and stores the more current data in the database. The system then stores information indicating when the more current data was stored in the database. Such a data warehouse allows decision-makers in the business to see some information (e.g., customer transaction or account data) up-to-the-moment and other information as it stood at some specific point-in-time, such as at the end of the previous month.

Abstract: A logical data model (LDM) design methodology that utilizes common or shared subject areas, developed for applications across two or more industries, in the design and construction of data warehouse solutions and logical data models for specific customers. The development and use of shared subject areas provides for more effective new LDM development through re-use of common elements and quicker deployment of horizontal applications on all industries.

Abstract: An interactive visual-modeling tool helps a database architect implement a database system. The tool gathers information about data that will form the content of the database, gathers information about one or more applications that will access the database, and gathers information about one or more phases in which the database-implementation project will occur. The tool uses this information to create a model of relationships among the content, the applications, and the project phases and to calculate costs for the implementation project. The tool then presents the model and the calculated costs to a human user through a graphical display.

Abstract: A data-warehousing system allows various areas of an enterprise to view data at varying levels of data freshness. The system acquires data that represents an event in the life of a business enterprise, such as a transaction between the enterprise and one of its customers, and loads this data into a database table. The system then makes the data available for retrieval from the table and stores information indicating when the data was made available for retrieval. In some embodiments, the system also acquires data that is related to and more current than the data representing the event and stores the more current data in the database. The system then stores information indicating when the more current data was stored in the database. Such a data warehouse allows decision-makers in the business to see some information (e.g., customer transaction or account data) up-to-the-moment and other information as it stood at some specific point-in-time, such as at the end of the previous month.

Abstract: An interactive visual-modeling tool helps a database architect implement a database system. The tool gathers information about data that will form the content of the database, gathers information about one or more applications that will access the database, and gathers information about one or more phases in which the database-implementation project will occur. The tool uses this information to create a model of relationships among the content, the applications, and the project phases and to calculate costs for the implementation project. The tool then presents the model and the calculated costs to a human user through a graphical display.

Abstract: A subject's motor skills are quantified by a standardized task in which a user places a pen in a specific position on a tablet. The position of the pen on the tablet in a plane of the tablet and a pressure exerted by the tablet on the pen in a direction transverse to the tablet is sampled while the user performs the task to produce a series of position samples and pressure samples taken at a corresponding sequence of sample times. The series of position and pressure samples and the sequence of sample times are assembled in a data array. The data array is subsequently analyzed to produce a quantitative measure of the user's performance of the task. This includes comparing the position samples to the specific position on the tablet specified by the task.