Abstract: A method and apparatus for a graph database instance (GDI) maintaining a secondary index, that indexes data from a sparse data map storing graph application data, within a sparse data map dedicated to the secondary index. The GDI formulates row-keys, for the secondary index map, by hashing the values of key/value pairs stored in rows of a map storing application data. The GDI stores for each formulated row-key, in the row of the secondary index that is indexed by the formulated row-key, references to rows of the map storing application data that match the key/value pair on which formulation of the row-key was based. The row-keys into the secondary index map may incorporate bucket identifiers, which, for each key/value pair, allows the GDI to spread the references to graph elements that match the key/value pair among a set number of “buckets” for the key/value pair within the secondary index map.

Abstract: A method, system, and computer program product for transforming RDF quads to relational views. The method commences by receiving a named graph, the named graph comprising at least one RDF quad, and analyzing the named graph to produce analysis metadata. The method uses the analysis metadata to generate relational views. The method further comprises publishing a relational view in the form of a SPARQL query. The quality of the results can be quantitatively measured and reported by calculating a goodness score based at least in part on aspects of the relational view definitions. Several variants for transformation include generating relational view definitions formed using a named-graph strict variant, or a named-graph relaxed variant, or a named-graph agnostic variant. The transformations can form outputs responsive to characteristics or properties such as a number of classes, a number of single-valued properties, a number of nullability properties, or a number of type-uniformed ranges.

Abstract: Techniques for efficiently loading graph data into memory are provided. A plurality of node ID lists are retrieved from storage. Each node ID list is ordered based on one or more order criteria, such as node ID, and is read into memory. A new list of node IDs is created in memory and is initially empty. From among the plurality of node ID lists, a particular node ID is selected based on the one or more order criteria, removed from the node ID list where the particular node ID originates, and added to the new list. This process of selecting, removing, and adding continues until no more than one node ID list exists, other than the new list. In this way, the retrieval of the plurality of node ID lists from storage may be performed in parallel while the selecting and adding are performed sequentially.

Abstract: Techniques for storing and processing graph data in a database system are provided. Graph data (or a portion thereof) that is stored in persistent storage is loaded into memory to generate an instance of a particular graph. The instance is consistent as of a particular point in time. Graph analysis operations are performed on the instance. The instance may be used by multiple users to perform graph analysis operations. Subsequent changes to the graph are stored separate from the instance. Later, the changes may be applied to the instance (or a copy thereof) to refresh the instance.

Abstract: A method, system, and computer program product for transforming RDF quads to relational views. The method commences by receiving a named graph, the named graph comprising at least one RDF quad, and analyzing the named graph to produce analysis metadata. The method uses the analysis metadata to generate relational views. The method further comprises publishing a relational view in the form of a SPARQL query. The quality of the results can be quantitatively measured and reported by calculating a goodness score based at least in part on aspects of the relational view definitions. Several variants for transformation include generating relational view definitions formed using a named-graph strict variant, or a named-graph relaxed variant, or a named-graph agnostic variant. The transformations can form outputs responsive to characteristics or properties such as a number of classes, a number of single-valued properties, a number of nullability properties, or a number of type-uniformed ranges.

Abstract: A method and apparatus for a graph database instance (GDI) maintaining a secondary index, that indexes data from a sparse data map storing graph application data, within a sparse data map dedicated to the secondary index. The GDI formulates row-keys, for the secondary index map, by hashing the values of key/value pairs stored in rows of a map storing application data. The GDI stores for each formulated row-key, in the row of the secondary index that is indexed by the formulated row-key, references to rows of the map storing application data that match the key/value pair on which formulation of the row-key was based. The row-keys into the secondary index map may incorporate bucket identifiers, which, for each key/value pair, allows the GDI to spread the references to graph elements that match the key/value pair among a set number of “buckets” for the key/value pair within the secondary index map.

Abstract: Techniques for storing and querying graph data in a key-value store are provided. A graph statement (e.g., an RDF graph statement) includes a plurality of values, at least two of which correspond to nodes in a graph. A key is generated based on the graph statement. The key may be generated based on concatenating hash values that are generated based on the plurality of values. The key-value store stores the key. The value that corresponds to the key may be a null or empty value. In response to a graph query (e.g., in SPARQL) that includes one or more query patterns, each of which includes one or more values, a key is generated based on the one or more values and sent to the key-value store, which returns one or more other keys, each of which is a superset of the generated key.

Abstract: A method, system, and computer program product for transforming RDF quads to relational views. The method commences by receiving a named graph, the named graph comprising at least one RDF quad, and analyzing the named graph to produce analysis metadata. The method uses the analysis metadata to generate relational views. The method further comprises publishing a relational view in the form of a SPARQL query. The quality of the results can be quantitatively measured and reported by calculating a goodness score based at least in part on aspects of the relational view definitions. Several variants for transformation include generating relational view definitions formed using a named-graph strict variant, or a named-graph relaxed variant, or a named-graph agnostic variant. The transformations can form outputs responsive to characteristics or properties such as a number of classes, a number of single-valued properties, a number of nullability properties, or a number of type-uniformed ranges.

Abstract: Techniques for efficiently loading graph data into memory are provided. A plurality of node ID lists are retrieved from storage. Each node ID list is ordered based on one or more order criteria, such as node ID, and is read into memory. A new list of node IDs is created in memory and is initially empty. From among the plurality of node ID lists, a particular node ID is selected based on the one or more order criteria, removed from the node ID list where the particular node ID originates, and added to the new list. This process of selecting, removing, and adding continues until no more than one node ID list exists, other than the new list. In this way, the retrieval of the plurality of node ID lists from storage may be performed in parallel while the selecting and adding are performed sequentially.

Abstract: Techniques for history enabling a table in a database system so that past versions of rows of the history-enabled table are available for temporal querying. The table is history enabled by adding a start time column to the table and creating a history table for the history-enabled table. The start time field's value in a row of the history-enabled table indicates when the contents of the row last changed. The rows of the history table are copies of rows of the history-enabled table that have been deleted or updated. The rows include end time fields whose values indicate when the row was updated or deleted. A history table's row thus indicates a period in which the history table's row was in the history-enabled table. Temporal queries are performed on a view which is the union of the history-enabled table and the history table.

Abstract: Systems, methods, and other embodiments associated with resource description framework (RDF) security are described. One example method includes generating, based on sensitivity labels associated with the contents of a triple in an RDF record, a sensitivity label. The example method may also include comparing the sensitivity label to an access label associated with an entity requesting an action associated with the record to be performed. The example method may also include performing the action upon determining that the entity has sufficient permission to request the action.

Abstract: Techniques for storing and processing graph data in a database system are provided. Graph data (or a portion thereof) that is stored in persistent storage is loaded into memory to generate an instance of a particular graph. The instance is consistent as of a particular point in time. Graph analysis operations are performed on the instance. The instance may be used by multiple users to perform graph analysis operations. Subsequent changes to the graph are stored separate from the instance. Later, the changes may be applied to the instance (or a copy thereof) to refresh the instance.

Abstract: Disclosed is an approach for presenting RDF data as a set of relational views. By presenting the RDF data as relational views, this permits integrated access to the RDF-based data from existing relational database tools, such as by asserting SQL queries against the relational views. One or more classes are identified within the RDF data, wherein a relational view of the set of the relational views maps properties relating to a particular class.

Abstract: Techniques for storing and querying graph data in a key-value store are provided. A graph statement (e.g., an RDF graph statement) includes a plurality of values, at least two of which correspond to nodes in a graph. A key is generated based on the graph statement. The key may be generated based on concatenating hash values that are generated based on the plurality of values. The key-value store stores the key. The value that corresponds to the key may be a null or empty value. In response to a graph query (e.g., in SPARQL) that includes one or more query patterns, each of which includes one or more values, a key is generated based on the one or more values and sent to the key-value store, which returns one or more other keys, each of which is a superset of the generated key.

Abstract: Techniques for storing and querying graph data in a key-value store are provided. A graph statement (e.g., an RDF graph statement) includes a plurality of values, at least two of which correspond to nodes in a graph. A key is generated based on the graph statement. The key may be generated based on concatenating hash values that are generated based on the plurality of values. The key-value store stores the key. The value that corresponds to the key may be a null or empty value. In response to a graph query (e.g., in SPARQL) that includes one or more query patterns, each of which includes one or more values, a key is generated based on the one or more values and sent to the key-value store, which returns one or more other keys, each of which is a superset of the generated key.

Abstract: A method, system, and computer program product for transforming RDF quads to relational views. The method commences by receiving a named graph, the named graph comprising at least one RDF quad, and analyzing the named graph to produce analysis metadata. The method uses the analysis metadata to generate relational views. The method further comprises publishing a relational view in the form of a SPARQL query. The quality of the results can be quantitatively measured and reported by calculating a goodness score based at least in part on aspects of the relational view definitions. Several variants for transformation include generating relational view definitions formed using a named-graph strict variant, or a named-graph relaxed variant, or a named-graph agnostic variant. The transformations can form outputs responsive to characteristics or properties such as a number of classes, a number of single-valued properties, a number of nullability properties, or a number of type-uniformed ranges.

Abstract: Systems, methods, and other embodiments associated with sequence matching with no more than a number E errors are disclosed. A test fragment to be located within a target sequence with at most a number E errors is received. The test fragment is broken into E+1 test sub-fragments. If one test sub-fragment is located within the target sequence with no errors; a determination is made as to whether the other test sub-fragments are located within the target sequence adjacent to the one test sub-fragment with a total of at most E errors. If the other test sub-fragments are located within the target sequence adjacent the one test sub-fragment with at most E errors, a location of the test fragment within the target sequence is returned.

Abstract: Disclosed is an approach for presenting RDF data as a set of relational views. By presenting the RDF data as relational views, this permits integrated access to the RDF-based data from relational tools.

Abstract: Systems, methods, and other embodiments associated with access control for graph data at the instance-level are described. One example method includes accepting data access constraints that are expressed as match and apply pattern pairs to enforce security policies. A user query on graph data with a security policy restricts the returned data to data that the user is authorized to access. For this purpose, a user query that includes query selection criteria corresponding to one or more match pattern criteria based on the resource referenced in the query is rewritten to include security conditions specified in the associated apply pattern to restrict access to the graph data.

Abstract: Techniques for history enabling a table in a database system so that past versions of rows of the history-enabled table are available for temporal querying. The table is history enabled by adding a start time column to the table and creating a history table for the history-enabled table. The start time field's value in a row of the history-enabled table indicates when the contents of the row last changed. The rows of the history table are copies of rows of the history-enabled table that have been deleted or updated. The rows include end time fields whose values indicate when the row was updated or deleted. A history table's row thus indicates a period in which the history table's row was in the history-enabled table. Temporal queries are performed on a view which is the union of the history-enabled table and the history table.