Random-Access Engine for Compacted Data Files
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Solution Overview
Problem
Current data storage technologies face challenges in efficiently storing and accessing large volumes of data due to limitations in physical storage capacity and data compression methods, which often result in degradation or loss of data. Additionally, existing data access methods become inefficient as data volumes grow, leading to bottlenecks in data processing pipelines and increased computational overload.
Innovation Solution
A system and method for random-access manipulation of compacted data files using a reference codebook, a random-access engine, a data deconstruction engine, and a data reconstruction engine. The system organizes the reference codebook into a hierarchical representation and traverses this representation to facilitate efficient data manipulation, encoding, and decoding, enabling direct access and modification of compacted data without decompressing the entire file.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data compression is used to increase storage capacity, then storage efficiency is improved, but random access capability deteriorates
Solution Approach 1:
The patent divides the compacted data file into multiple blocks, each with its own metadata containing offset information. This segmentation allows the system to access specific blocks without decompressing the entire file, thereby maintaining random access capability while using compression to increase storage capacity.
Solution Approach 2:
The patent introduces metadata as an intermediary layer between the compressed data and the access mechanism. This metadata contains offset information that enables direct access to specific portions of compressed data without full decompression, resolving the contradiction between compression efficiency and random access capability.
2Ease of operation
If traditional data access methods are used, then data can be accessed, but computational overload increases with growing data volumes
Solution Approach 1:
The patent extracts only the necessary metadata (offset information) needed for accessing specific data blocks, rather than processing or loading entire datasets into memory. This extraction approach enables efficient data access while significantly reducing computational overhead and energy consumption.
Solution Approach 2:
The patent performs preliminary organization of data into blocks with embedded metadata during the data writing phase. This preliminary action enables efficient random access later without requiring computational intensive operations at access time, reducing computational overload.
3Quantity of substance
If physical storage capacity is increased to meet demand, then storage capacity is improved, but device complexity and manufacturing challenges worsen
Solution Approach 1:
The patent changes the parameter of data representation by applying compression algorithms, transforming data into a more compact form. This parameter change effectively increases storage capacity without requiring additional physical storage devices, thereby avoiding the complexity and manufacturing challenges associated with scaling physical storage infrastructure.
Data Source
AI summary
A system and method for random-access manipulation of compacted data files, utilizing a reference codebook, a random-access engine, a data deconstruction engine, and a data deconstruction engine. The system may receive a data query pertaining to a data read or data write request, wherein the data file to be read from or written to is a compacted data file. A random-access engine may facilitate data manipulation processes by transforming the codebook into a hierarchical representation and then traversing the representation scanning for specific codewords associated with a data query request. In an embodiment, an estimator module is present and configured to utilize cardinality estimation to determine a starting codeword to begin searching the compacted data file for the data associated with the data query. The random-access engine may encode the data to be written, insert the encoded data into a compacted data file, and update the codebook as needed.