Abstract: The present disclosure relates to computer-implemented methods, software, and systems for importing metadata between applications. One example method includes providing, by a metadata integration service associated with a first application, a view of content from a data source. The metadata integration service defines a service metadata model including entities defined for data objects. The entities of the service metadata model are each associated with different scopes defining dependencies between entities. The view includes at least one entity associated with data objects of the first application. A query to acquire metadata associated with one or more data objects of the first application is received. A scope function is invoked based on evaluating the query to determine relevant entities for the query. The entities are determined based on dependency rules defining scopes for entities at the scope function.

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for exchanging metadata between applications. One example method includes providing a metadata service defining a service metadata model for exposing metadata of data objects defined at one or more applications. A connection to a data source associated with a first application is established from a separate application to acquire the metadata from the data source for one or more data objects related to the first application. In response to establishing the connection, a view of content from the data source is provided that includes a list of entities from the service metadata model. A query defined based on the list of entities is received for acquiring metadata associated with the one or more identified entities. The query is evaluated at a backend of the first application and the metadata for the identified entities from the data source is provided.

Abstract: Techniques for reducing CPU consumption in a federated search are disclosed. In some example embodiments, a computer-implemented method comprises determining an initial search scope by selecting a subset of searchable resources from a plurality of searchable resources based on interaction data of a user, with the initial search scope being defined by the selected subset of searchable resources, and the interaction data indicating online activity of the user directed towards past search results of past search queries submitted by the user. A federated search for a current search query is then performed using the initial search scope, with the federated search for the current search query being restricted to only the subset of searchable resources, and current search results for the current search query are generated based on the performing of the federated search.

Abstract: Techniques for reducing CPU consumption in a federated search are disclosed. In some example embodiments, a computer-implemented method comprises determining an initial search scope by selecting a subset of searchable resources from a plurality of searchable resources based on interaction data of a user, with the initial search scope being defined by the selected subset of searchable resources, and the interaction data indicating online activity of the user directed towards past search results of past search queries submitted by the user. A federated search for a current search query is then performed using the initial search scope, with the federated search for the current search query being restricted to only the subset of searchable resources, and current search results for the current search query are generated based on the performing of the federated search.

Abstract: A system includes reception of a query comprising one or more search terms, determination that one of the one or more search terms corresponds to a table column comprising Boolean operators, determination of a value of the table column corresponding to TRUE, and addition of a condition to the query, the condition specifying the value of the table column.

Abstract: Techniques for reducing CPU consumption in a federated search are disclosed. In some example embodiments, a computer-implemented method comprises determining an initial search scope by selecting a subset of searchable resources from a plurality of searchable resources based on interaction data of a user, with the initial search scope being defined by the selected subset of searchable resources, and the interaction data indicating online activity of the user directed towards past search results of past search queries submitted by the user. A federated search for a current search query is then performed using the initial search scope, with the federated search for the current search query being restricted to only the subset of searchable resources, and current search results for the current search query are generated based on the performing of the federated search.

Abstract: A system and method for modeling cross system content between a hub and one or more backend systems is disclosed. Model content of one or more data models is stored in a model stack defined in a storage. The model content of each data model includes model metadata representing a model of a backend system. Cross model content is stored in a cross model stack. The cross model content includes reference metadata representing one or more references associated with a data model of one backend system and that reference a data model of another backend system. Central cross model content is stored in a central cross model stack. The central cross model content includes one or more cross elements that do not belong to the model content of any of the data models, and that establish a connection between two data models of different backend systems.

Abstract: Methods, systems, and computer program products for ranking data items are described. A ranking configuration is defined for an object type, the ranking configuration comprising an assignment of one or more ranking dimensions to the object type and, for each of the one or more assigned ranking dimensions, one or more corresponding values and a significance weight assigned to each value, with at least one of the values being a dynamic value. Each ranking dimension comprises one or more object attributes and a ranking-impact weight, with at least one of the object attributes being a context-based object attribute. A ranking condition is generated for each ranking dimension assigned to the object type. The generation of the ranking condition is based at least in part on one or more object attributes, a specified ranking-impact weight, a context value, and the one or more values and associated significance weights.

Abstract: Methods, systems, and computer program products for ranking data items are described. A ranking configuration is defined for an object type, the ranking configuration comprising an assignment of one or more ranking dimensions to the object type and, for each of the one or more assigned ranking dimensions, one or more corresponding values and a significance weight assigned to each value. Each ranking dimension comprises one or more object attributes and a ranking-impact weight, at least one of the object attributes being a continuous-scales object attribute. A ranking condition is generated for each ranking dimension assigned to the object type. The generation of the ranking condition is based at least in part on the one or more object attributes, a specified ranking-impact weight, the one or more values and associated significance weights, and a distance function corresponding to the continuous-scales object attribute.

Abstract: Methods, systems, and computer program products for ranking data items are described. In accordance with various example embodiments, a ranking configuration is defined for an object type, the ranking configuration comprising an assignment of one or more ranking dimensions each comprising one or more object attributes to the object type and, for each of the one or more assigned ranking dimensions, one or more corresponding values and a significance weight assigned to each value, at least one of values being a dynamic value corresponding to the context-based object attribute. A ranking condition is generated for each ranking dimension assigned to the object type. The generation of the ranking condition is based at least in part on one or more object attributes, a specified ranking-impact weight, a context value corresponding to the context-based object attribute, and the one or more values and associated significance weights.

Abstract: Methods, systems, and computer program products for ranking data items are described. In accordance with various example embodiments, a ranking configuration is defined for an object type, the ranking configuration comprising an assignment of one or more ranking dimensions each comprising one or more object attributes to the object type and, for each of the one or more assigned ranking dimensions, one or more corresponding values and a significance weight assigned to each value, at least one of values being a dynamic value corresponding to the context-based object attribute. A ranking condition is generated for each ranking dimension assigned to the object type. The generation of the ranking condition is based at least in part on one or more object attributes, a specified ranking-impact weight, a context value corresponding to the context-based object attribute, and the one or more values and associated significance weights.

Abstract: Various embodiments of systems and methods for a search-independent ranking and arranging data are described herein. Initially a rank value computation data is received. The rank value computation data is then forwarded to a database engine for computing rank values corresponding to an object type. The computation of rank values is independent of receiving the search query. Finally the data values corresponding to the object type are arranged based on the computed rank values.

Abstract: An exhaust-gas turbocharger (1) having a turbine housing (2), having a compressor housing (3), having a bearing housing (4), which has a bearing housing axis (L), and having a connecting device (5), for connecting the bearing housing (4) to the compressor housing (3) and/or the turbine housing (2). The connecting device has a plurality of connecting elements (6) which each have a connecting element end face (7). The number of bores (8) in the compressor housing (3) corresponds to the number of connecting elements (6). The bores (8) and the connecting elements (6) inserted into the bores (8) are arranged at an acute angle (?) with respect to the bearing housing axis (L), and the connecting element end faces (7) rest on an associated bearing surface (9) of the bearing housing (4) and/or turbine housing (2).

Abstract: A system includes reception of a request conforming to a modeled query and join filter criteria, the request comprising a first subrequest associated with a search attribute view and a second subrequest associated with an analytical view, definition of a join between the search attribute view and the analytical view based on one or more view attributes of the search attribute view, and filtering of a result set associated with the first subrequest based on the join and on the join filter criteria.

Abstract: Methods, systems, and computer program products for ranking data items are described. A ranking configuration is defined for an object type, the ranking configuration comprising an assignment of one or more ranking dimensions to the object type and, for each of the one or more assigned ranking dimensions, one or more corresponding values and a significance weight assigned to each value, with at least one of the values being a dynamic value. Each ranking dimension comprises one or more object attributes and a ranking-impact weight, with at least one of the object attributes being a context-based object attribute. A ranking condition is generated for each ranking dimension assigned to the object type. The generation of the ranking condition is based at least in part on one or more object attributes, a specified ranking-impact weight, a context value, and the one or more values and associated significance weights.

Abstract: Methods, systems, and computer program products for ranking data items are described. In accordance with various example embodiments, a ranking configuration is defined for an object type, the ranking configuration comprising an assignment of one or more ranking dimensions each comprising one or more object attributes to the object type and, for each of the one or more assigned ranking dimensions, one or more corresponding values and a significance weight assigned to each value, at least one of values being a dynamic value corresponding to the context-based object attribute. A ranking condition is generated for each ranking dimension assigned to the object type. The generation of the ranking condition is based at least in part on one or more object attributes, a specified ranking-impact weight, a context value corresponding to the context-based object attribute, and the one or more values and associated significance weights.

Abstract: Methods, systems, and computer program products for ranking data items are described. In accordance with various example embodiments, a ranking configuration is defined for an object type, the ranking configuration comprising an assignment of one or more ranking dimensions each comprising one or more object attributes to the object type and, for each of the one or more assigned ranking dimensions, one or more corresponding values and a significance weight assigned to each value, at least one of values being a dynamic value corresponding to the context-based object attribute. A ranking condition is generated for each ranking dimension assigned to the object type. The generation of the ranking condition is based at least in part on one or more object attributes, a specified ranking-impact weight, a context value corresponding to the context-based object attribute, and the one or more values and associated significance weights.

Abstract: Methods, systems, and computer program products for ranking data items are described. A ranking configuration is defined for an object type, the ranking configuration comprising an assignment of one or more ranking dimensions to the object type and, for each of the one or more assigned ranking dimensions, one or more corresponding values and a significance weight assigned to each value. Each ranking dimension comprises one or more object attributes and a ranking-impact weight, at least one of the object attributes being a continuous-scales object attribute. A ranking condition is generated for each ranking dimension assigned to the object type. The generation of the ranking condition is based at least in part on the one or more object attributes, a specified ranking-impact weight, the one or more values and associated significance weights, and a distance function corresponding to the continuous-scales object attribute.

Abstract: Various embodiments of systems and methods for a search-independent ranking and arranging data are described herein. Initially a rank value computation data is received. The rank value computation data is then forwarded to a database engine for computing rank values corresponding to an object type. The computation of rank values is independent of receiving the search query. Finally the data values corresponding to the object type are arranged based on the computed rank values.

Abstract: A system includes reception of an instruction to access a column of a database table, determination that the column is not associated with the schema of the database table, determination of whether the schema of the database table is flexible or static, returning, if it is determined that the schema of the database table is static, of an error in response to the instruction, and, if it is determined that the schema of the database table is flexible, not returning an error in response to the instruction.