Database Table Conversion via Bridge Schema and Intermediate Table
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Solution Overview
Problem
Existing database table revision processes face challenges in extending field types without causing downtime, as they often require copying data to a new table, which can be memory-intensive and prevent write access during the revision process.
Innovation Solution
A method that creates a new table with revised field structures, copies data to the new table, and then renames the new table to match the original table, allowing for field type changes without duplicating the table, thereby minimizing downtime and memory usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the complete table is copied to a new version to extend field length, then the field type can be extended, but additional memory equal to or greater than the size of the table is required
Solution Approach 1:
The patent segments the table conversion process into distinct phases: creating a new table structure, copying data in manageable operations, and then swapping tables. This allows memory usage to be optimized by processing data in chunks rather than requiring the entire table to be held in memory simultaneously during conversion.
Solution Approach 2:
The patent introduces a temporary new table as an intermediary structure during the conversion process. This intermediary table holds the extended field structure while the original table remains intact for reading, enabling field type extension without requiring additional memory equal to the full table size.
2Adaptability or versatility
If the complete table is copied to a new version to extend field length, then the field type can be extended, but access to the table is prevented (downtime) during the revision process
Solution Approach 1:
The patent performs preliminary actions by creating the new table structure with extended fields before the conversion is complete. Applications can be prepared in advance to use the new table structure, and the actual data copying and table swapping can be done during maintenance windows with minimal impact on operations.
Solution Approach 2:
The patent uses copying mechanisms to replicate data from the original table to the new table structure. This allows the original table to remain accessible for reading while data is copied to the new structure, reducing downtime by enabling concurrent read access during the conversion process.
3Adaptability or versatility
If a conversion procedure is used to extend data types, then the field length can be increased, but the process is complex and requires creating a new table, copying data, and replacing the old table
Solution Approach 1:
The patent creates a universal table conversion framework that can handle multiple data type extensions (NUMC, CURR, DATS, etc.) through a single standardized process. This multi-functional approach reduces complexity by providing a unified conversion mechanism rather than requiring separate procedures for each data type.
Solution Approach 2:
The patent systematically changes table parameters (field lengths, data types) through a structured conversion process that modifies the table definition and then copies data with the new parameters. This parameter-based approach simplifies the conversion procedure by treating all field extensions as parameter changes rather than requiring different conversion logic for each field type.
Data Source
AI summary
Methods, systems, and computer program products for converting a database table and implementing upgrades and/or migrations are described. A bridge schema comprising a bridge view for a table in a database of an original schema is created and a bridge application server instance is created, the bridge application server instance configured to utilize the bridge schema to access the table of the original schema. The table of the original schema is revised to conform to a specified target schema and a target application server instance configured to access the revised table is created.