Compressed K-ary Tree Search Structure
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Solution Overview
Problem
Existing database compression methods are inefficient, requiring multiple hash table lookups and lacking speed in search operations, especially for frequently accessed values.
Innovation Solution
A computer system converts a database into a compressed k-ary tree structure, which is then converted into directly indexed arrays for rapid searching, eliminating the need for hash table lookups and improving search speed by using mathematical operations to traverse memory locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional hash table lookup methods are used for database searching, then data can be stored in a simple format, but search operations become time-consuming and slow
Solution Approach 1:
The patent pre-computes and stores the compressed k-ary tree structure during database initialization or maintenance periods. This preliminary action transforms the raw database into an optimized search structure beforehand, so that subsequent search operations can proceed rapidly without performing complex computations in real-time, thus resolving the contradiction between simple storage and fast search.
Solution Approach 2:
The patent replaces the traditional hash table lookup mechanism with a mathematically-based k-ary tree traversal system. Instead of using hash functions and pointer chasing, the system uses mathematical operations on array indices to directly compute node positions, substituting a mechanical lookup process with a more efficient mathematical computation approach that achieves up to 40x speedup.
2Quantity of substance
If compression techniques are applied to reduce memory usage, then storage efficiency improves, but search operation complexity increases
Solution Approach 1:
The patent changes the fundamental parameters of the data structure by organizing compressed data into a k-ary tree format with specific mathematical properties. By adjusting the tree depth, branching factor (k), and array indexing scheme, the system achieves optimal balance between compression ratio and search efficiency, transforming a complex compression problem into a manageable mathematical structure that enables fast searches.
3Measurement precision
If multiple hash table lookups are required for searching, then data accuracy can be maintained, but the number of operations increases
Solution Approach 1:
The patent extracts the essential search functionality from the complex multi-step hash table lookup process and consolidates it into a single unified k-ary tree traversal operation. By taking out the redundant lookup steps and replacing them with direct mathematical index computation, the system maintains search accuracy while dramatically reducing the number of operations required, achieving up to 40x improvement in productivity.
Data Source
AI summary
An improved search engine reorganizes an input database containing a set of values into a searchable tree structure having nodes of information with pointers to child nodes. The searchable tee structure is then converted into a searchable array structure that uses mathematical operations to rapidly traverse through elements of the array using mathematical formula to reach different memory locations instead of requiring pointer lookups.