Relational Dictionary Encoding Decoding Database Tables
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Solution Overview
Problem
Existing database management systems face inefficiencies in encoding and decoding database data due to the overhead of maintaining separate encoding and decoding dictionaries, which can lead to wasted computing resources and poor scalability, especially in distributed systems where synchronization and partitioning add complexity.
Innovation Solution
Implementing a relational dictionary that serves as both an encoding and decoding dictionary, stored as a database table with tokens and codes, allowing for efficient encoding and decoding processes tailored to each column's characteristics without significant programming effort, leveraging existing DBMS infrastructure and query optimization frameworks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If separate encoding and decoding dictionaries are maintained, then encoding and decoding functions are provided, but overhead increases and resource utilization decreases
Solution Approach 1:
The patent combines separate encoding and decoding dictionaries into a single unified dictionary structure. This dictionary contains both encoding mappings (tokens to codes) and decoding mappings (codes to tokens), eliminating the need to maintain two separate dictionary structures and their associated synchronization overhead, thereby reducing system complexity while preserving both encoding and decoding functionalities
Solution Approach 2:
The unified dictionary structure serves multiple functions simultaneously - it acts as both an encoding dictionary and a decoding dictionary. By making the dictionary multi-functional, the system eliminates redundant structures and reduces the overhead associated with maintaining separate encoding and decoding dictionaries, while still providing both encoding and decoding operations
2Productivity
If separate encoding and decoding dictionaries are maintained, then encoding and decoding operations can be performed, but computing resources are wasted and scalability is poor
Solution Approach 1:
By merging separate encoding and decoding dictionaries into a single unified dictionary, the patent reduces the total computational resources required for dictionary maintenance, synchronization, and management. This consolidation eliminates redundant operations and reduces the energy/computing resources wasted while maintaining full encoding and decoding operational capabilities
3Ease of operation
If separate encoding and decoding dictionaries are used in distributed systems, then encoding and decoding functions are provided, but synchronization and partitioning complexity increases
Solution Approach 1:
The patent merges encoding and decoding dictionaries into a single unified structure that can be consistently maintained across distributed system nodes. This unified approach simplifies synchronization protocols and partitioning strategies compared to managing two separate dictionary structures, reducing the complexity of distributed system operations while preserving encoding and decoding functionalities
Data Source
AI summary
Techniques related to relational dictionaries are disclosed. In some embodiments, one or more non-transitory storage media store a sequence of instructions which, when executed by one or more computing devices, cause performance of a method. The method involves storing a code dictionary comprising a set of tuples. The code dictionary is a database table defined by a database dictionary and comprises columns that are each defined by the database dictionary. The set of tuples maps a set of codes to a set of tokens. The set of tokens are stored in a column of unencoded database data. The method further involves generating encoded database data based on joining the unencoded database data with the set of tuples. Furthermore, the method involves generating decoding database data based on joining the encoded database data with the set of tuples.