RDF Data Integration via TABLE Function in Relational Databases
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Solution Overview
Problem
Current systems for querying RDF models are not optimized for use in standard relational database management systems, lacking the efficiency and optimization techniques available in traditional SQL systems, such as automatic optimization and index utilization.
Innovation Solution
The integration of RDF data into a relational database system using a TABLE function mechanism, which allows for the execution of non-SQL queries within SQL queries, enabling the use of RDF patterns and rulebases to query RDF triples while leveraging relational database optimizations like indexing and materialized views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If RDF data is queried using current RDF-specific systems, then RDF triple querying capability is achieved, but query processing efficiency and optimization are insufficient compared to relational database systems
Solution Approach 1:
The patent segments the RDF triple data model into three separate relational database tables (subject table, predicate table, object table), each storing specific attributes of RDF triples. This segmentation allows the RDF data to be stored and queried using standard relational database structures, enabling the use of optimized SQL query processing while maintaining RDF data representation capabilities.
Solution Approach 2:
The patent introduces an intermediary mapping layer that translates RDF triple patterns into equivalent SQL queries. This intermediary mechanism converts RDF-specific query syntax and semantics into relational database SQL operations, allowing RDF queries to leverage relational database optimization techniques including index utilization, query rewriting, and execution plan optimization.
2Productivity
If RDF data is stored in a relational database system, then optimization techniques like indexing and materialized views can be utilized, but the system complexity increases due to integration requirements
Solution Approach 1:
The patent makes the relational database system universally capable of handling both traditional relational data and RDF triple data through a unified storage architecture. By representing RDF triples using standard relational tables and SQL operations, the system gains multi-functionality, allowing the same database infrastructure to optimize queries for both data models without requiring separate specialized systems.
Solution Approach 2:
The patent enables the relational database system to automatically optimize RDF queries through its existing optimization mechanisms. The database's query optimizer, index structures, and materialized view capabilities automatically apply to RDF triple pattern queries translated into SQL, allowing the system to self-optimize without requiring external specialized optimization layers.
Data Source
AI summary
The TABLE function mechanism available in a RDBMS is used to integrate RDF models into SQL queries. The table function invocation takes parameters including an RDF pattern, an RDF model, and an RDF rule base and returns result rows to the SQL query that contain RDF triples resulting from the application of the pattern to the triples of the model and the triples inferred by applying the rule base to the model. The RDBMS includes relational representations of the triples and the rules. Optimizations include indexes and materialized views of the representations of the triples, precomputed inferred triples, and a method associated with the TABLE function that rewrites the part of the SQL query that contains the TABLE function invocation as an equivalent SQL string. The latter technique is generally applicable to TABLE functions.