Random-Access Engine for Compacted Data Files
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Solution Overview
Problem
Current data storage technologies face challenges in efficiently managing and accessing compacted data due to limitations in random access capabilities, leading to inefficiencies in data retrieval and storage as data demand continues to grow exponentially.
Innovation Solution
A system and method for random-access manipulation of compacted data files using an adaptive method selection, which includes a random-access engine that transforms the codebook into a hierarchical representation and traverses it to facilitate data manipulation processes, and an estimator module that utilizes cardinality estimation to determine starting codewords for searching compacted data files.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is compacted to increase storage capacity, then storage efficiency is improved, but random access capability deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing metadata about the compacted data structure, including codeword boundaries and hierarchical indexes, before random access operations are performed. This allows the system to quickly locate and access specific data regions without decompressing entire files, resolving the contradiction between compacted storage and random access capability
Solution Approach 2:
The patent introduces an intermediary layer (metadata structure and hierarchical index) between the compacted data and the access operations. This intermediary contains pre-computed information about data locations and structures, enabling efficient random access to compacted data without requiring full decompression, thus maintaining both storage efficiency and access capability
2Ease of operation
If entire compacted files are decompressed for data manipulation, then data accessibility is improved, but processing time and energy consumption increase
Solution Approach 1:
The patent extracts and utilizes only the necessary portions of compacted data for specific operations by leveraging metadata and hierarchical indexes. Instead of decompressing entire files, the system extracts and processes only the relevant data segments, significantly reducing processing time and energy consumption while maintaining data accessibility
Solution Approach 2:
The patent applies partial action by performing data manipulation operations on selectively decompressed portions of compacted files rather than the entire file. The hierarchical index enables the system to decompress and process only the specific data regions needed for the current operation, avoiding the time and energy costs of full file decompression
3Quantity of substance
If traditional compression methods are used, then storage efficiency is improved, but data retrieval efficiency deteriorates
Solution Approach 1:
The patent segments the compacted data into hierarchical structures with associated metadata that enables efficient navigation and retrieval. By organizing compacted data into manageable segments with pre-computed indexes, the system maintains high storage efficiency while dramatically improving data retrieval efficiency through selective access to specific segments
Solution Approach 2:
The patent adds a hierarchical dimension to traditional compression by introducing multiple levels of indexing and metadata structures. This additional dimensional organization allows the system to maintain compacted storage while enabling efficient data retrieval through the hierarchical navigation path, transforming the flat compression structure into a multi-dimensional access architecture
Data Source
AI summary
A system and method for random-access manipulation of compacted data files with adaptive method selection, 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, transforming the codebook into a hierarchical representation and traversing the representation scanning for specific codewords associated with a data query request. In an embodiment, an estimator module may be 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.