Patent application number | Description | Published |
20130166495 | GENERATING A COMPILER INFRASTRUCTURE - In an embodiment, the compiler infrastructure allows execution of multidimensional analytical metadata from various databases by providing a generic transformation. A compilation request to execute a multidimensional analytical metadata is received. A type of the compilation request is determined to identify an associated transformation and corresponding transformation rules. Based upon the type of compilation request, a database of an application server is queried to retrieve the corresponding multidimensional analytical metadata. Based upon the identified transformation rules, the multidimensional analytical metadata is transformed into a generic metadata that is executable by any desired engine. An instance of a calculation scenario is generated based upon the transformation. The compiler infrastructure is generated by deploying the instance of the calculation scenario in the desired engine (e.g. in-memory computing engine.) | 06-27-2013 |
20130166496 | EXECUTING RUNTIME CALLBACK FUNCTIONS - In an embodiment, a runtime callback function is a part of a code that is invoked upon execution of an associated function. To execute the runtime callback function associated with an in-memory computing engine, multidimensional analytical metadata associated with an application server is received and transformed into an in-memory executable metadata, to generate an instance of an in-memory executable calculation scenario. The instance of the in-memory executable calculation scenario is analyzed to determine process callbacks associated with nodes of the in-memory executable calculation scenario. Based upon the determined process callbacks, the runtime callback function is executed by executing a selection callback at the nodes and a transformation callback at part providers associated with the in-memory executable calculation scenario. | 06-27-2013 |
20130166497 | DYNAMIC RECREATION OF MULTIDIMENSIONAL ANALYTICAL DATA - According to one aspect of systems and methods for dynamic recreation of multidimensional analytical data, lost sets of calculation scenarios that provide multidimensional analytical data results after aggregations and transformations of the multidimensional analytical data are recreated in the volatile storage of an in-memory computing engine. A multidimensional analytical data view (MDAV) compiler is triggered to read the MDAV metadata stored in an intermediate buffer in the MDAV compiler. The read MDAV metadata is compiled into a calculation scenario including calculation view metadata. The calculation view metadata is stored in the intermediate buffer. The recreated set of calculation scenarios is deployed on the in-memory computing engine. | 06-27-2013 |
20130166892 | GENERATING A RUNTIME FRAMEWORK - In an embodiment, the runtime framework is responsible for executing multidimensional analytical metadata in a runtime environment that is determined by the runtime framework. To generate such a runtime framework, the received multidimensional analytical metadata is analyzed to determine a type of an associated calculation pattern. Based upon the type, subsets of the multidimensional analytical metadata and corresponding runtime decision rules are determined. To execute the subsets, executable conditions corresponding to the multidimensional analytical metadata are identified. Based upon the executable conditions, the calculation pattern associated with the multidimensional analytical metadata is executed by executing the associated subsets, and the runtime framework is generated. The runtime framework determines calculation scenario executable subsets and calculation scenario inexecutable subsets that are associated with the multidimensional analytical metadata, and executes the subsets in their respective engines. | 06-27-2013 |
20140289183 | KEY FIGURE DATA FILTERS IN OLAP WITH HEIRARCHIES - A system and method of key figure data filters are presented. The key figure data filters are implemented in an analytical engine of a business warehouse system. The key figure data filters employ conditions, which can be expressed as a kind of selection that describe a set. A key figure data algorithm can be implemented by the analytical engine using the conditions, yet still respect hierarchies in the business warehouse database. | 09-25-2014 |