Relational Cube Storage for Multidimensional Data Access
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Solution Overview
Problem
Relational database management systems face challenges in efficiently storing and accessing multidimensional data, as existing approaches either sacrifice the benefits of multidimensional storage or relational storage, leading to difficulties in administration and access control.
Innovation Solution
The implementation of RCUBE (Relational Cube) approach, which uses ANSI SQL to store and access multidimensional data directly in relational tables, allowing for OLAP operations without local multi-dimensional storage structures, and extends SQL to support relational dimensions and hierarchies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multidimensional data is stored in specialized multidimensional database systems (MOLAP), then storage and access efficiency for multidimensional data is improved, but application compatibility and ease of access are worsened because only specially built applications can access the data
Solution Approach 1:
The patent creates a unified database system that performs both multidimensional storage (OLAP) and relational storage (OLTP) functions. The relational tables are designed to serve dual purposes: storing transactional data and storing multidimensional data with implicit cube structures. This allows standard SQL applications to access multidimensional data without requiring specialized MOLAP clients, thus achieving universality across different application types while maintaining efficient multidimensional access patterns through the relational structure itself
2Adaptability or versatility
If multidimensional data is stored in relational database systems using star schema, then application compatibility is improved, but storage efficiency and access performance are worsened due to the conventional table structure
Solution Approach 1:
The patent introduces a new dimensional organization within relational tables by creating implicit cube structures. Instead of the traditional star schema with separate fact and dimension tables, the invention organizes data in relational tables that inherently represent multidimensional cubes through their column and row structures. This allows the data to be accessed in dimensional patterns (by row, column, or page) directly from the relational storage, achieving both compatibility and efficiency
3Ease of manufacture
If conventional star schema is used to store multidimensional data, then ease of implementation is improved, but administration and access control become more difficult
Solution Approach 1:
The patent merges the management of relational data and multidimensional data into a single unified system. By creating implicit cube structures within relational tables and using standard SQL for all operations, the invention eliminates the need for separate multidimensional database management systems. This consolidation simplifies administration and access control because a single relational database management system handles both types of data with uniform security, backup, and management procedures, rather than requiring separate systems for OLTP and OLAP
Data Source
AI summary
A method and mechanism for performing an operation based on multidimensional data in a relational database. A first query is submitted to a relational database engine of the relational database management system, thereby causing a relational cube to be generated. The first query includes instructions to select a portion of multidimensional data for inclusion in the relational cube. The first query includes instructions to group the selected portion of multidimensional data using at least two or more levels of granularity of at least one dimension. The first query also includes instructions to generate a materialized view. Based on a received request for an operation, a second query is submitted to the relational database engine for execution against the relational cube, thereby causing the operation to be performed.