Rewriting Table Functions as SQL Strings for RDF Query Optimization
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Solution Overview
Problem
Current systems for querying RDF models in relational database systems face high processing costs due to the overhead of setting up, executing, and transferring data from table functions, which limits the efficiency of RDF triple queries.
Innovation Solution
A rewrite method is associated with the table function to generate an SQL string that replaces the table function, allowing the relational database management system to execute the SQL query directly, reducing overhead and enabling optimizer usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If table functions are used to query RDF models in relational database systems, then RDF data can be integrated and queried using SQL, but the processing time and cost increase due to the overhead of setting up, executing, and transferring data from table functions
Solution Approach 1:
The patent extracts the RDF query logic from the table function execution context and transforms it into standalone SQL statements. By taking out the query processing from the table function overhead and representing it as native SQL strings, the system eliminates the setup, execution, and data transfer overhead while preserving the RDF query capability.
Solution Approach 2:
The patent creates a copy of the table function's query logic in the form of SQL strings. Instead of executing the original table function that incurs overhead, the system generates equivalent SQL statements that replicate the table function's query behavior, thereby achieving the same result without the performance penalty.
2Adaptability or versatility
If table functions are used to integrate RDF data into relational database systems, then RDF triples can be queried, but the device complexity increases due to the overhead mechanisms
Solution Approach 1:
The patent extracts the complex table function execution mechanism and replaces it with simpler SQL string generation. By removing the table function overhead layer and working directly with SQL statements, the system maintains RDF integration capability while reducing system complexity.
Solution Approach 2:
The patent substitutes the mechanical table function execution system with a lighter-weight SQL string generation and execution mechanism. This replacement eliminates the need for table function setup, execution, and data transfer mechanisms, thereby reducing device complexity while preserving functionality.
3Productivity
If table functions are used for RDF queries, then data can be retrieved from RDF models, but productivity decreases due to the overhead of setting up and executing table functions
Solution Approach 1:
The patent performs preliminary action by pre-generating SQL strings that represent the RDF query logic before execution. By preparing the query in the form of optimized SQL statements in advance, the system eliminates the need for table function setup and execution overhead during actual query processing, thereby improving productivity.
Solution Approach 2:
The patent creates copies of the query logic in the form of SQL strings that can be executed directly without table function overhead. This copying approach allows the system to retrieve data from RDF models using efficient SQL execution rather than through the slower table function mechanism.
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.