Abstract: To discover functional dependencies in a large relation, a sample of tuples from the relation is collected. The sample is examined to determine whether one or more candidate functional dependencies exist just within the sample as a nominal dependency. When a nominal dependency is found in the sample, than all the tuples in the relation are examined to verify whether the nominal dependency holds for the whole relation. Candidate functional dependencies are disqualified when either a nominal dependency is found or when it is verified as functional dependency that holds for the entire relation.

Abstract: To discover functional dependencies in a large relation, a sample of tuples from the relation is collected. The sample is examined to determine whether one or more candidate functional dependencies exist just within the sample as a nominal dependency. When a nominal dependency is found in the sample, than all the tuples in the relation are examined to verify whether the nominal dependency holds for the whole relation. Candidate functional dependencies are disqualified when either a nominal dependency is found or when it is verified as functional dependency that holds for the entire relation.

Abstract: A computer implemented method, apparatus, and computer usable program code for monitoring health of a data processing system. A determination is made whether a response is received within a first time period in response to an I/O device sending a receive descriptor to the data processing system. A determination is made whether a second time period passes before the receive descriptor becomes available for sending to the data processing system in response to an unavailability of the receive descriptor for sending by the I/O device to the data processing system. A health check is performed on the data processing system if the first time period passes without receiving a response. A health check is performed on the data processing system if the second time period passes without a receive descriptor becoming available to send the data processing system.

Abstract: A method, apparatus and computer program product are provided for offloading functions to improve processor performance. A single LAN adapter is provided that allows for predefined functions to be offloaded to other devices. Different methods are described for offloading functions. First, users and applications may pick and choose, on demand, only the functions that are to be offloaded. Second, a scheduler schedules those functions that are to be offloaded through a predetermined scheduler. Third, functions may be offloaded based on heuristic or learning methods which are stored in a knowledge database.

Abstract: A method, system, and computer program product in a data processing system are disclosed for dynamically selecting software buffers for aggregation in order to optimize system performance. Data to be transferred to a device is received. The data is stored in a chain of software buffers. Current characteristics of the system are determined. Software buffers to be combined are then dynamically selected. This selection is made according to the characteristics of the system in order to maximize performance of the system.

Abstract: A method, apparatus, and computer instructions for managing data transfer in a data processing system. An amount of space available for storing data in a receive buffer is detected. In response to the amount of space available, a first priority for a receive function and a second priority for a transfer function is set. The first priority and the second priority is used to access resources for the data transfer.

Abstract: A framework is provided for management of models. Management of data models or other types of models includes model change comparison and change implementation. For example, in the context of data warehouse models, model components and their process interactions are captured in a form such that different versions of a model can be automatically compared and any changes between versions determined. The framework provides the capability of capturing a model definition down to the level of an individual object and the semantics and relationships of each object. A model is represented and stored as a set of (1) unique object identifiers, (2) object metadata signatures that represent the semantics of objects, and (3) object relationships. Such model information can be stored in a relational database, against which a query, such as an SQL (Structured Query Language) query, can be executed to determine whether two models differ.

Abstract: A framework is provided for management of models. Management of data models or other types of models includes model change comparison and change implementation. For example, in the context of data warehouse models, model components and their process interactions are captured in a form such that different versions of a model can be automatically compared and any changes between versions determined. The framework provides the capability of capturing a model definition down to the level of an individual object and the semantics and relationships of each object. A model is represented and stored as a set of (1) unique object identifiers, (2) object metadata signatures that represent the semantics of objects, and (3) object relationships. Such model information can be stored in a relational database, against which a query, such as an SQL (Structured Query Language) query, can be executed to determine whether two models differ.