Abstract: Methods and systems for supporting multiple deployment models for enterprise business applications, are described. In one embodiment, the method may include designating pillars associated with an enterprise business application. Each pillar may include application units which comprise logical groupings for application units used in the enterprise business application. The method may further include determining which of the application units are dependent to more than one of the pillars. Furthermore, based on the determination of the dependent application units, the method may generate deployment code associated with the dependent application units which is configured to be deployment model independent. The method may then receive, at deployment time, a deployment model designation indicating a type of deployment model selected to be used for the enterprise business application. Then, the enterprise business application may be deployed according to the deployment model designation.

Abstract: This disclosure describes, generally, methods and systems for supporting multiple deployment models for enterprise business applications. In one embodiment, the method may include designating pillars associated with an enterprise business application. Each pillar may include application units which comprise logical groupings for application units used in the enterprise business application. The method may further include determining which of the application units are dependent to more than one of the pillars. Furthermore, based on the determination of the dependent application units, the method may generate deployment code associated with the dependent application units which is configured to be deployment model independent. The method may then receive, at deployment time, a deployment model designation indicating a type of deployment model selected to be used for the enterprise business application. Then, the enterprise business application may be deployed according to the deployment model designation.

Abstract: An optimizer function of a Relational Database Management System (RDBMS) generates alternative query execution plans (QEPs) for executing a query, provides an execution model of each of the QEPs, chooses one of the QEPs for execution based on the model associated therewith, and exploits an empirical measurement from the execution of the chosen QEP to validate the model associated therewith, by determining whether the model is in error, and by computing one or more adjustments to the model to correct the determined error.

Abstract: An optimizer function of a Relational Database Management System (RDBMS) generates alternative query execution plans (QEPs) for executing a query, provides an execution model of each of the QEPs, chooses one of the QEPs for execution based on the model associated therewith, and exploits an empirical measurement from the execution of the chosen QEP to validate the model associated therewith, by determining whether the model is in error, and by computing one or more adjustments to the model to correct the determined error.