Sap Se

Sap Ag

Sebastian Schroetel

Stefan Dipper

Ulrich Bestfleisch

Michael Wilking

Gerrit Simon Kazmaier

Nadine Sachs

Christof Mueller

Oliver Klemenz

Stefan Unnebrink

Sergey Smirnov

Veit Spaegele

Karl-Peter Nos

Dirk Baumgaertel

Zoltan Albrecht

Dirk Janning

Tim Kaiser

Methods, systems, and computer-readable storage media for receiving user input indicating a value of a first setting of one or more settings, the first setting defining a data integrity scenario that is be applied during a query session with a database system, the data integrity scenario defining data sources for reading data in response to one or more navigation requests, if a concurrent change occurs in the database system, receiving a query, reading, data from one or more data sources based on the query and the first setting, selectively caching at least a portion of the data based on the first setting, and providing a result for display to a user that submitted the query.

Accommodating concurrent changes in underlying data during reporting

In one embodiment, a method receives a query for analyzing data in a database. The query includes a first level calculation that is performed before a second level calculation. When an operator associated with the first level calculation is present in the query, the method performs: calculating the first level calculation by removing group by information for a reference characteristic for the first level calculation to determine a first level calculation result and calculating the second level calculation using the first level calculation result using the group by information for the reference characteristic to determine a second level calculation result, wherein the group by in the second level calculation combines groups of rows in a database table of the database that have the same content in their specified columns.

Database query calculation using an operator that explicitly removes group-by characteristics

A method for internationalization of a computer application being designed and developed as cloud application in a platform-as-a-service (PaaS) environment includes disposing a translatable texts table in a data layer of the computer application as a common source of translatable texts for all layers of the computer application. The method further includes disposing a text string translation service in a logic layer of the computer application. to expose the translatable texts table disposed in the data layer to a presentation layer of the computer application.

Translatable texts in cloud applications

Techniques are described for providing a non-blocking application object framework allowing parallelization of operation and function calls throughout an application executing within the framework. In one example, a dependency model associated with an application in a non-blocking application object framework is identified, where the application is associated with a plurality of operations and the dependency model defines at least one dependency between at least two of the operations. At runtime of the non-blocking application object framework, the identified dependency model is interpreted. An optimized execution plan of the application is automatically generated in the non-blocking application object framework based on the interpreted dependency model, wherein at least a first portion of the operations of the application are optimized in a sequential execution order based on dependencies defined in the dependency model. The application is then executed in the non-blocking application object framework based on the optimized execution plan.

Non-blocking application object framework and dependency model management

In one embodiment, a method receives a query for analyzing data in a database. The method then determines a constant in the query and determines an operator applied to the constant in the query. The operator explicitly controls a behavior of the constant. The constant is represented as a scalar representation in the query instead of as a vectorial representation where the constant would have been used as the vectorial representation without the use of the operator due to a rule governing use of constants. Then, the method performs a calculation for the query to determine a query result using the constant as the scalar representation.

Operators for constants in aggregated formulas

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.

Key figure data filters in OLAP with hierarchies

In one embodiment, a method receives a query for analyzing data in a database. The query includes a first level calculation that is performed before a second level calculation. The method determines an operator in the query configured to explicitly remove group by information for a reference characteristic in the first level calculation where the group by information is specified for the reference characteristic in the second level calculation. The first level calculation is performed by removing the group by information for the reference characteristic for the first level calculation to determine a first level calculation result and the second level calculation is performed using the first level calculation result using the group by information for the reference characteristic to determine a second level calculation result.

Removing group-by characteristics in formula exception aggregation

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.

Dynamic recreation of multidimensional analytical data

A system includes determination of a dimension over which to iterate, determination of a first measure for which an aggregated value is determined per iteration, determination of a second measure for which a value is determined once per calculation of an iterative measure and against which to compare the aggregated value per iteration, and storage of the dimension, the first measure and the second measure as metadata of an iterative measure.

Iterative measures

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.

Generating a runtime framework

In accordance with aspects of the disclosure, a system and methods may be provided for integrating software layers in OLAP including receiving, at an OLAP engine, a dynamic result set structure passed from an application layer via one or more other software layers. The dynamic result set structure may include a description of entities for a target layer. The system and methods may include enhancing raw data, at the OLAP engine, acquired from a database associated with a source layer based on the description of entities for the dynamic result set structure and passing one or more references to one or more memory locations for data elements in the dynamic result set structure from the OLAP engine to the application layer via the one or more other software layers for acquiring each data element associated with each corresponding reference in the dynamic result set structure.

System and methods for integrating software layers for OLAP

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.)

Generating a compiler infrastructure

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.

Growing community of inventors

Heidelberg, Germany

Sebastian Schroetel