Inline Tree Data Structure for High-Speed Dataset Search
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Solution Overview
Problem
Conventional electronic data structures such as spreadsheets and relational databases become unwieldy and inefficient for large datasets, leading to slow search and retrieval operations, despite offering flexibility in data management.
Innovation Solution
The implementation of an inline tree data structure, which is a highly compressed binary data structure generated from a conventional data structure using a dedicated conversion program, allowing for fast search and filter operations by storing the dataset in a binary file that occupies less than 1 to 2 bytes per field per record, enabling the entire dataset to be loaded into random access memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional electronic data structures such as spreadsheets and relational databases are used to store large datasets, then flexibility in data management is maintained, but search and retrieval operations become slow and inefficient
Solution Approach 1:
The patent transforms data from conventional text-based formats into a binary data structure with fundamentally different parameters. Each data field is encoded as a fixed-length binary string with a specific byte order (most significant byte first), and the entire structure uses fixed-width numeric representations. This parameter transformation enables direct binary comparison operations that are vastly faster than text-based searching, while the rigid structure eliminates the flexibility issues of conventional databases.
Solution Approach 2:
The patent replaces the mechanical interpretation and comparison processes of conventional text-based data structures with direct binary arithmetic operations. The binary encoding allows search operations to use simple bitwise comparisons and arithmetic calculations instead of character-by-character text processing, substituting a complex mechanical text-processing system with an efficient binary computational system.
2Quantity of substance
If datasets are stored in conventional data structures, then data management flexibility is preserved, but the data size becomes unwieldy and occupies excessive storage space
Solution Approach 1:
The patent changes the fundamental parameters of data representation from variable-length text strings to fixed-length binary encodings. Each data field uses a predetermined number of bytes with specific bit allocations, eliminating the variable-length overhead of text formats. This parameter standardization dramatically reduces storage requirements while enabling efficient binary operations for data manipulation and search.
Solution Approach 2:
The patent segments data into fixed-size binary records with standardized field layouts. Each record is divided into discrete binary fields with predetermined widths, allowing efficient packing and indexing. This segmentation enables the data to be stored in contiguous memory blocks, reducing storage overhead and improving access efficiency compared to conventional row-based table structures.
3Quantity of substance
If large datasets are stored in conventional data structures, then complete data retention is maintained, but loading the entire dataset into memory becomes impractical
Solution Approach 1:
The patent transforms the data structure into a compact binary format that minimizes memory footprint through fixed-length encodings and efficient byte ordering. This parameter optimization allows the entire dataset to fit into available memory resources, enabling in-memory processing of complete datasets that would otherwise require disk-based storage and incremental loading, thereby preventing any loss of information.
Data Source
AI summary
An inline tree data structure and one or more auxiliary data structure encode a multitude of data records of a dataset; data fields of the dataset define a tree hierarchy. The inline tree comprises one binary string for each data record that are all the same length, are arranged in an ordered sequence that corresponds to the tree hierarchy, and include an indicator string indicating position in the tree hierarchy of each data record relative to an immediately adjacent data record. A search program is guided through the dataset by interrogating each indicator string in the inline tree data structure so as to reduce unnecessary interrogation of data field values.