SQL Query SPARQL Endpoint Integration
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Solution Overview
Problem
Legacy database systems face challenges in accessing remote RDF data stored at SPARQL endpoints, requiring pre-access and staging of data before it can be combined with local relational data, which is inefficient, especially with large RDF data sizes.
Innovation Solution
The system allows for a single SQL query to access a SPARQL endpoint from within a database system context, enabling the retrieval and integration of RDF data from remote SPARQL endpoints into a local database context, using the SPARQL_SERVICE construction to specify remote SPARQL endpoints and combine results with relational data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If RDF data is pre-accessed and pre-staged by middleware before access by the database engine, then the RDF data can be combined with local relational data, but the resource requirements increase significantly especially with large RDF data sizes
Solution Approach 1:
The patent extracts the RDF data access operation from the traditional middleware pre-staging process and integrates it directly into the SQL query execution. The database engine directly queries the remote RDF repository via HTTP URL and processes the results within the query context, eliminating the need to pre-stage large amounts of RDF data locally. This extraction of the pre-staging step resolves the contradiction by maintaining ease of access while significantly reducing resource requirements.
Solution Approach 2:
The patent performs preliminary actions by embedding the RDF data retrieval and processing directly in the SQL query statement. The database engine executes the SPARQL query against the remote RDF repository as part of the query preparation phase, converting RDF results to relational format before the main query execution. This preliminary action eliminates the need for separate pre-staging operations, reducing resource consumption while maintaining operational ease.
2Adaptability or versatility
If legacy techniques are used to access RDF data, then data can be combined with local relational data, but the process requires multiple steps including pre-access and pre-staging
Solution Approach 1:
The patent merges the RDF data access, conversion, and integration operations into a single SQL query statement. The SPARQL_SERVICE construction allows the database engine to execute SPARQL queries against remote RDF repositories and integrate the results with local relational data in one unified operation. This merging eliminates the need for separate pre-access and pre-staging steps, reducing process complexity while maintaining the adaptability to combine different data types.
Solution Approach 2:
The patent creates a universal SQL query construction (SPARQL_SERVICE) that can access both local and remote RDF data sources and integrate them with relational data through a single interface. This multi-functional construction allows the database engine to handle RDF data retrieval, conversion, and integration uniformly, regardless of whether the RDF data is local or remote, thereby reducing access process complexity while maintaining versatility.
3Reliability
If RDF data is stored locally for later access, then queries can be performed over the corpus of locally-stored RDF data, but large resource requirements are incurred to move the data
Solution Approach 1:
The patent introduces an intermediary mechanism where the database engine acts as a mediator between the SQL query and the remote RDF repository. The engine executes SPARQL queries directly against the remote repository and converts the results to relational format on-demand, without requiring local storage of the RDF corpus. This intermediary approach maintains reliable data access by handling conversions within the query execution context while eliminating the need for large quantities of local data storage.
Data Source
AI summary
A method, system, and computer program product for accessing a SPARQL endpoint that is specified from within a SQL database query language statement. A method embodiment receives a SQL database query language statement that is then parsed in order to identify the locations of one or more SPARQL endpoints to be accessed. The database query language statement comprises operations and/or queries (e.g., SPARQL queries) to be performed over at least some linked data (e.g., queries over named RDF graphs) found at the one or more SPARQL endpoints. The database query language statement can also specify relational operations such as a relational database table operation, and/or a view operation, and/or other relational database functions that operate in conjunction with retrieved linked data.