Database Column Reordering via Translation Mapping
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Solution Overview
Problem
As data sets grow larger, implementing changes to data schemas becomes increasingly costly and inefficient, as existing methods often require recreating duplicate data sets, which burdens resources and incurs significant costs.
Innovation Solution
The implementation of online reordering of database table columns using storage format translation, allowing for on-demand data schema modifications without the need for duplicate data sets, by utilizing translation mappings to reorder columns while maintaining access to the original data schema, thereby applying schema changes instantly and efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional data schema changes are implemented by recreating duplicate data sets, then data consistency is maintained, but storage costs and resource consumption increase significantly
Solution Approach 1:
The patent creates a virtual copy of the data schema through translation mappings rather than physical duplication. The translation layer maps old schema definitions to new schema definitions, allowing the system to present a changed schema to users while the actual data remains unchanged in storage. This eliminates the need for costly duplicate data sets while maintaining data consistency.
Solution Approach 2:
The patent introduces a translation layer as an intermediary between the stored data and the accessed data. This translation layer handles schema transformations by mapping field names, data types, and structures from the original schema to the new schema without requiring physical data movement or duplication. The intermediary resolves the contradiction by enabling schema changes without affecting storage resources.
2Adaptability or versatility
If data schema changes are implemented by recreating duplicate data sets, then schema modifications are complete, but implementation time and resource burden increase
Solution Approach 1:
The patent prepares translation mappings in advance that define how old schema elements correspond to new schema elements. These mappings are created and stored before actual schema changes are needed, allowing the system to rapidly apply schema transformations when changes are required. The preliminary preparation of translation rules eliminates the time-consuming process of recreating data sets during schema changes.
Solution Approach 2:
The patent replaces the mechanical process of physically recreating data sets with a software-based translation system. Instead of moving and copying actual data through complex ETL processes, the system uses translation mappings to virtually transform schema definitions. This substitution dramatically reduces implementation time and resource burden while maintaining full schema modification capability.
3Quantity of substance
If online reordering of columns is implemented without duplicate data sets, then storage costs are reduced, but data consistency during transitions may be compromised
Solution Approach 1:
The patent changes the parameters of the schema definition rather than the actual data. Translation mappings modify field names, data types, and structural parameters to reflect the new schema while the underlying data remains unchanged. This parameter-based approach maintains data consistency because the same data is accessed through different parameter definitions, eliminating the risk of inconsistency between old and new data sets.
Data Source
AI summary
Online reordering for database table columns may allow a user to reorder the columns of a database table without taking the database offline. A mapping between different column orders for a database table may be generated and stored in response to a request to reorder columns in a database table. When a portion of the database table is accessed, the columns of the database table in the accessed portion of the database table may be reordered to perform the access request.