Sap Se

Romans Kasperovics

Thomas Fischer

Marcus Paradies

Cornelia Kinder

Jan Bross

Roland Sedler

Gerald Franz

Hannes Jakschitsch

Umang Rawat

Hinnerk Gildhoff

Bastian Erler

Florian Schimmel

Christoph Weyerhaeuser

Tobias Mindnich

Markus Fath

Matthias Hauck

A method may include receiving a definition of a table user-defined function (TUDF) in a graph query language. The table user-defined function may be created based on the definition. For example, the creation of the table user-defined function may include checking and compiling the definition to generate executable code associated with the table user-defined function. Upon receiving a query including a relational query language statement invoking the table user-defined function, such as a structured query language select statement, the query may be executed on at least a portion of a graph data stored in a database. The executing of the query may include calling the executable code to execute the table user-defined function included in the relational query language statement. Related systems and computer program products are also provided.

Table user-defined function for graph data processing

A method may include generating, for a heterogeneous graph comprising a plurality of vertex tables and/or edge tables, an adjacency structure including a vertex adjacency structure specifying a plurality of neighboring vertices in the heterogeneous graph and an edge adjacency structure specifying a plurality of neighboring edges in the heterogeneous graph. A graph processing algorithm operating on the heterogeneous graph may be executed based on the adjacency structure. Related systems and computer program products are also provided.

Adjacency structure for heterogeneous graph data

A method for performing a path finding operation in graph data stored in a database is provided. The method may include receiving, from a client, a request to perform a weighted path operation on at least portion of the graph data. The portion of the graph data may correspond to a graph. The request may specify attributes associated with vertices and/or edges included in the graph. In response to the request, the weighted path operation may be performed by at least identifying a shortest path between two endpoints in the graph. The shortest path may minimize the one or more attributes of vertices and/or edges included in the shortest path. Related systems and articles of manufacture, including computer program products, are also provided.

Extended path finding operations on graph data

A method, a system, and a computer program product for querying graph data. A graph workspace object is identified. One or more parameters for executing a declarative language query are identified. Using the identified parameters, the declarative language query is executed on the identified graph workspace object. Based on the executed declarative language query, one or more tables responsive to a request to access graph data stored in a relational database are processed.

SQL interface for embedded graph subqueries

A method, a system, and a computer program product for generating graphs using a stored procedure. One or more graph data tables are generated. A procedure having a predetermined name is generated. One or more inputs to the generated procedure includes the generated one or more graph data tables. The generated procedure includes one or more graph objects. The graph data tables are configured to be input to the graph objects. The generated procedure is stored. The stored generated procedure is executed using one or more graph data stored in a graph database.

Ad-hoc graph definition

A method for executing a graph algorithm is provided. The method may include responding to a request from a client to execute a graph algorithm on graph data stored in a database by determining data required to execute the graph algorithm. In response to determining that a first portion of the data required to execute the graph algorithm is absent from an existing adjacency structure that includes a second portion of the data required to execute the graph algorithm, the existing adjacency structure may be modified to include the first portion of data. The graph algorithm may be executed based on the modified adjacency structure. The execution of the graph algorithm may include querying, based on the modified adjacency structure, the graph data stored in the database. Related systems and articles of manufacture, including computer program products, are also provided.

Adaptable adjacency structure for querying graph data

A method for executing a graph algorithm may include responding to a request from a client to execute a graph algorithm on graph data stored in a database by determining data required to execute the graph algorithm. In response to determining that a first portion of the data required to execute the graph algorithm is absent from an existing adjacency structure that includes a second portion of the data required to execute the graph algorithm, the existing adjacency structure may be modified to include the first portion of data. The graph algorithm may be executed based on the modified adjacency structure. The execution of the graph algorithm may include querying, based on the modified adjacency structure, the graph data stored in the database. Related systems and articles of manufacture, including computer program products, are also provided.

Graph data derivatives

A method for performing text searches on graph data stored in a database is provided. The method may include receiving, from a client, a request to perform a text search to locate a target string in the graph data stored in the database. The request may be in accordance with a declarative graph query configured to query the graph data stored in the database. The response to the request may include performing the text search to locate, in the graph data stored in the database, one or more records of strings that are exact matches, approximate matches, and/or linguistic matches for the target string. Related systems and articles of manufacture, including computer program products, are also provided.

Text searches on graph data

A system for processing graph-modeled data in a relational database is provided. The system can include at least one data processor and at least one memory storing instructions that are executed by the at least one data processor. Executing the instructions can result in operations comprising: receiving a request to execute a graph algorithm operating on graph-modeled data stored at a relational database; and executing the graph algorithm within the relational database, the executing comprising use of an adjacency structure within the relational database. Related methods and articles of manufacture, including computer program products, are also provided.

Adjacency structures for executing graph algorithms in a relational database

A system for processing graph-modeled data in a relational database is provided. In some implementations, the system performs operations comprising: receiving, from a first user, a request to define a graph algorithm operating on a graph workspace, the graph workspace comprising at least a portion of graph-modeled data stored at a relational database; applying a first security rule associated with the relational database, the applying comprising determining whether the first user has a privilege to define the graph algorithm operating on the graph workspace; and storing the graph algorithm at the relational database, when the first user is determined to have the privilege to define the graph algorithm operating on the graph workspace. Related methods and articles of manufacture, including computer program products, are also provided.

Graph-modeled data processing in a relational database

Based on received input, a vertex table of the database layer and a vertex key column in the vertex table can be identified. The vertex key column defines vertices of a graph representation. Also based on the received input, an edge table of the database layer, an edge key column in the edge table, a source column in the edge table, and a target column in the edge table can be identified. The source column and target column define relationships between vertices of the plurality of vertices. Within a graph workspace object, graph relationships linking the vertices defined by the vertex key column via edges defined by the source column and target column in the edge table can be assigned, and the graph workspace can be generated in a higher level programming layer based on the graph workspace object.

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Speyer, Germany

Romans Kasperovics