Knowledge Graph Dictionary Compression for Unified RDF Querying
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Solution Overview
Problem
Maintaining multiple data systems for traditional and RDF data formats incurs increased maintenance costs and requires separate queries and additional processing, which is inefficient and resource-intensive.
Innovation Solution
The Triple Integration and Querying System (TQS) integrates RDF-formatted data into a relational database using a table designed for triples, employing a dictionary to reduce memory overhead and enable single queries across both traditional and RDF data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple data systems are used to maintain traditional database data and RDF data separately, then data format integrity is maintained, but maintenance costs increase and system complexity increases
Solution Approach 1:
The patent merges RDF data and traditional database data into a single unified data system. RDF triples are stored in a table structure with columns for subject, predicate, and object, allowing both data types to coexist in one system. This eliminates the need for separate RDF and SQL systems, reducing system complexity while maintaining data integrity through type-specific columns.
Solution Approach 2:
The unified table structure serves multiple functions: it stores both traditional relational data and RDF triple data, supports both SQL and SPARQL queries, and handles different data types (strings, integers, floats, decimals, dates, times) through specialized columns. This multi-functional design reduces the need for multiple specialized systems.
2Reliability
If multiple data systems are used to maintain traditional and RDF data, then data format specificity is preserved, but processing time increases due to separate queries
Solution Approach 1:
By combining RDF and traditional data into one table, the system enables unified query processing. A single query can access both RDF triples and traditional database records without requiring separate query systems or data movement, significantly improving query processing efficiency.
Solution Approach 2:
The unified table structure acts as an intermediary layer between RDF data and traditional database data. It translates RDF triples into a tabular format that can be efficiently queried using standard SQL operations while preserving the semantic meaning of RDF relationships, enabling fast processing of both data types.
3Device complexity
If RDF data is stored in traditional database tables, then system simplicity increases, but memory overhead increases without optimization
Solution Approach 1:
The patent applies local quality optimization by creating separate columns for different data types (string, integer, float, decimal, date, time) within the unified table. Each column is optimized for its specific data type, reducing memory overhead compared to storing all RDF data as generic strings. This localized optimization maintains system simplicity while improving storage efficiency.
Data Source
AI summary
Various embodiments for a triple integration and querying system with dictionary compression are described herein. An embodiment operates by identifying a table of a database with four or more columns with triple formatted data including one subject column, one predicate column, and two or more object columns. It is determined that a master dictionary is to be generated for the both the subject column and the predicate column based on an identical datatype being used for both columns. A master dictionary including both the unique values from the subject data dictionary and the predicate data dictionary is generated. Values in the subject column and the predicate column are replaced based on the unique values from the master dictionary.