Sap Se

Welf N Walter

Volker Driesen

Christian Stork

Uwe Schlarb

Immo-Gert Birn

Kerstin Hoeft

Ulrich Auer

Ralf-Juergen Hauck

Torsten Ziegler

Karsten K Bohlmann

Rolf Hammer

Kai Baumgarten

Andrea Neufeld

Thilo Boehm

Helmut Prestel

Andreas Blumenthal

Andreas Simon Schmitt

Gerd G Forstmann

Stefan Bresch

Sigrid K Wortmann

Ralf Wendelgass

Jens Lieberum

Christian Lutter

Systems and methods include determination of a plurality of artifacts of a first data schema and a first view schema of a first database version to be updated in a second database version, determination of target structures of a plurality of runtime objects for the second database version based on the artifacts, and loading of current structures of the runtime objects into a runtime buffer of a first work process connected to the first view schema. While the first work process serves first incoming requests using the runtime buffer and the first view schema, the runtime objects are updated to the determined target structures in the first data schema and in a second view schema of the second database version, a second work process is connected to the second view schema, and the second work process serves second incoming requests, the second view schema and the updated first data schema.

Downtime-minimized database version deployment

Systems and methods include configuration of a first database view to read from common versions of rows of a database table or from rows of the database table associated with a first version of the application, the database table storing application content, configuration of a first application server to write to the common versions of rows of the database table, configuration of a second database view to read from common versions of rows of the database table or from rows of the database table associated with a second version of the application, configuration of a second application server to write to rows of the database table associated with the second version of the application, modification of the database table to include rows associated with the second version of the application while the first application server executes the first version of the application and incoming user requests are directed to the first application server, configuration of the second application server to write to common versions of the rows of the database table, and re-direction of incoming user requests to the second application server executing the second version of the application.

Management of two application versions in one database table

The present disclosure involves systems, software, and computer implemented methods for key pattern management. One example method includes receiving a query for a logical database table from an application. A determination is made as to whether the query is a write query. In response to determining that the query is a write query, a determination is made as to whether the query complies with a key pattern configuration that describes keys of records included in a physical database table that is part of a logical table implementation. The physical table includes records of the logical database table that are allowed to be written by the application. The write query is redirected to the physical database table in response to determining that the query complies with the key pattern definition. The query is rejected in response to determining that the query does not comply with the key pattern configuration.

Key pattern management in multi-tenancy database systems

The present disclosure teaches solutions for transitioning between database system sharing types. In one example, a tenant container includes a read-only table, a first writable table, and a mixed table for storing read-only and writable data. When transitioning to a sharing setup, a shared container is created and a shared table is created in the shared container. Data is copied from the read-only table to the shared table and the read-only table is dropped. A read-only view is created in the tenant container and a second shared table is created in the shared container. Read-only mixed data is copied from the mixed table to the second shared table and deleted from the mixed table, and after the deletion, the mixed table is renamed as the second writable table. A union view is created that provides unified access to the second shared table and the second writable table.

Transitioning between system sharing types in multi-tenancy database systems

The present disclosure involves systems, software, and computer implemented methods for enabling multiple system sharing types in multi-tenancy database systems. One example method includes determining a system sharing type configuration for a database system. The system sharing type configuration is one of standard, shared, tenant, or simulated. Tables are created in the database system based on the system sharing type configuration and the table sharing type of each table. Content is deployed to created tables in the database system based on the system sharing type configuration and the table sharing type of each table. Access is provided to at least one application to the database system based on the system sharing type configuration and the table sharing type of each table.

System sharing types in multi-tenancy database systems

The present disclosure involves systems, software, and computer implemented methods for data separation and write redirection in multi-tenancy database systems. One example method includes providing access to at least one application to a database system. A query is received from an application. A determination is made that the query is associated with a union view that provides unified access to a first read-only table in a shared database container and a first writable table in a tenant database container. A determination is made as to whether the query is a read query or a write query. In response to determining that the query is a read query, the query is processed using the union view. In response to determining that the query is a write query, the query is modified to use the first writable table and the query is processed using the writable table.

Data separation and write redirection in multi-tenancy database systems

A mesh structure can be a type concept that extends internal tables or other data structures of a business programming languages (e.g., ABAP) by associations, as known from a data object meta-model. A mesh can include a set of operations, such as for example iteration via an iterator object and selection of instances expressed by a path language. A mesh structure can be optimized for read access and traversal, and can provide a working area that is processed with statements in the business programming language to implement one or more core services directly from the mesh data structure. Related methods, computer program products, and systems are described.

Native language support for intra-and interlinked data collections using a mesh framework

In one embodiment, a method includes defining a parent structure including an extension. A polymorphic structure is defined for the extension. The polymorphic structure is associated with a plurality of client specialization structures, each client specialization being associated with a client in a plurality of clients. During runtime by a computing device, the parent structure is generated with an extension to a client specialization structure associated with one of the plurality of clients where client specialization structures associated with other clients are not visible to the parent structure.

Generic boxed components for multi-client systems

In an embodiment, a method of computer program compilation is presented. In this method, a compiler for a first programming language is provided. In one example, the first programming language allows a data assignment to depend on a result of a previous data assignment. Source code including a first portion written in the first programming language and a second portion written in a second programming language is accessed, with the second portion representing a data transformation from a first data structure accessible in the first portion to a second data structure accessible in the first portion. In one example, the second programming language prevents a data assignment that depends on a result of a previous data assignment. The source code is compiled using the compiler to generate executable code to be executed by an engine for the first programming language, which includes an interpretation engine to interpret the second portion.

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Rauenberg, Germany

Welf N Walter