Real-Time Database Indexing via Character Code Segmentation
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Solution Overview
Problem
As data sets grow, existing database indexing methods become inefficient and resource-intensive, leading to slower search times and increased storage requirements, with offline indexing causing search results to become outdated and requiring excessive management resources.
Innovation Solution
A method of building a database index in real-time by analyzing and grouping data elements, storing each element with its position, and updating existing entries with references, allowing for efficient retrieval of data items based on consecutive or neighboring elements, which reduces storage needs and improves search speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by stationary object
If database indexes are built offline or rarely used, then system burden during data access is reduced, but search results become outdated and incorrect
Solution Approach 1:
The patent transitions from static offline indexing to dynamic real-time indexing. The index is continuously updated as new data arrives, making the indexing system adaptive and responsive to changing data states. This dynamic approach ensures search results remain accurate while allowing the system to manage indexing burden through incremental updates rather than large batch operations.
Solution Approach 2:
The patent performs preliminary indexing actions by maintaining the index in real-time as data is added, rather than waiting until offline. This preliminary continuous maintenance ensures the index is always current, eliminating the need for later corrective updates and ensuring search accuracy without requiring heavy offline processing.
2Adaptability or versatility
If traditional word-based indexing is used, then keyword search capability is provided, but storage requirements increase due to variable word sizes requiring large field types
Solution Approach 1:
The patent fundamentally changes the parameter of indexing units from variable-length words to fixed-length character codes (1-8 bits). This parameter transformation eliminates the need for large field types like CLOB or VARCHAR, reducing storage requirements while maintaining search capability through character-based indexing that can reconstruct searchable terms.
Solution Approach 2:
The patent segments data into individual characters and indexes these basic units rather than treating whole words as atomic units. This segmentation allows for more efficient storage by using fixed-size character codes and enables flexible reconstruction of search terms from indexed character sequences, reducing overall storage requirements while preserving search functionality.
3Quantity of substance
If data sets grow larger, then more information is stored, but indexing becomes slower and requires more management resources
Solution Approach 1:
The patent segments the indexing process into character-level operations that can be performed incrementally as data arrives. By breaking down words into individual character codes, the system can process and index data in small, manageable units rather than requiring large batch processing, maintaining indexing speed even as data sets grow to big data scales.
Solution Approach 2:
The patent changes the indexing parameter from word-based to character-code-based indexing with fixed sizes (1-8 bits). This parameter change enables more efficient processing of individual indexing units, allowing the system to handle larger data volumes without proportionally increasing indexing time or management resource requirements.
Data Source
AI summary
Methods and systems for generating a database index and searching the database index are described herein. In one aspect this may include receiving an item of database data, wherein the item of database data comprises a sequence of data elements. Groups of data elements may be identified within the received item of database data. If any one or more of the identified groups of data elements have not been previously identified within the item of database data and/or previous items database data then the one or more identified group may be stored as index entries in a database index. Information describing the sequence of the groups of neighbouring data elements may be recorded within the database index as they are located within the item of database data. The database index may be searched based on a received search term comprising a sequence of data elements.