Database Identifier Generation via Hashing and Segmentation
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Solution Overview
Problem
As databases grow in size and are cloned to improve accessibility, the likelihood of duplicate database record identifiers increases, leading to inefficiencies in data storage and access.
Innovation Solution
The system generates unique identifiers by combining the database name and identifier through hashing, ensuring a high probability of uniqueness, even as the number of databases expands, by incorporating a b-tree data structure and sequence values within the database management system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the number of databases is increased to distribute queries, then query responsiveness is improved, but the likelihood of duplicate identifiers increases
Solution Approach 1:
The identifier generation system segments the identifier into multiple components: database name, database identifier, and sequence value. Each component serves a specific purpose in ensuring uniqueness across distributed databases while maintaining query performance.
Solution Approach 2:
The system changes the parameters of identifier generation by incorporating hashing of the database name and identifier, combined with sequence values. This transforms simple sequential identifiers into composite hashed identifiers that maintain uniqueness probability across expanded database networks.
2Ease of operation
If databases are cloned to improve accessibility, then data accessibility is improved, but duplicate record identifiers are generated
Solution Approach 1:
The system performs preliminary action by generating a unique database identifier before cloning databases. This preliminary identifier, combined with the database name in the hashing function, ensures that cloned databases automatically receive unique identifiers without requiring post-clone modification.
Solution Approach 2:
The hashing function acts as an intermediary that processes both the database name and database identifier to generate a unique record identifier. This intermediary mechanism ensures that even cloned databases with identical structures produce unique identifiers through the hashing transformation.
3Productivity
If the number of databases increases, then data distribution is improved, but identifier collision probability increases
Solution Approach 1:
The system adds another dimension to identifier generation by incorporating the database name into the hashing function along with the database identifier and sequence value. This dimensional expansion ensures that identifiers remain unique even as the number of databases increases, maintaining data distribution efficiency.
Data Source
AI summary
Described herein are systems and methods for generating integrated identifiers that may be combined with database sequence values to create a high probability of uniqueness that minimizes assigning duplicate identifiers to one or more databases. The integrated identifier may be based in part on several identifiers associated with a database. This may include a numeric identifier assigned to the database, a name assigned to the database, or any other database property that may be relatively unique. In one embodiment, the integrated identifier may be associated with a sequence value for a database. While the sequence value may be unique within the database, the integrated identifier may be unique to other database identifiers. When an existing database is cloned, a new integrated identifier may be generated from the cloned database. New records stored in the new database may use the new integrated identifier, while the cloned records will remain unedited.