Partitioned Data Compression for Page-Level Method Selection
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Solution Overview
Problem
Current data compression methods lack efficiency in selecting the most appropriate compression technique for each part of a data page, leading to suboptimal compression performance and varying CPU usage across different data components.
Innovation Solution
A method for partitional data compression that involves collecting statistical data, dividing data pages into parts, analyzing the compression efficiency of multiple methods for each part, and selecting the most efficient compression method for each part to compress the data page effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single compression method is applied to the entire data page, then the compression process is simple and fast, but the compression efficiency is suboptimal
Solution Approach 1:
The patent divides a data page into multiple parts or segments, and applies different compression methods to different segments based on their characteristics. This segmentation allows the system to optimize compression efficiency for each segment while maintaining manageable complexity through systematic analysis and selection processes.
Solution Approach 2:
The patent implements local quality by selecting compression methods tailored to specific data segments rather than applying a uniform method across the entire page. Each segment receives a compression method optimized for its local characteristics, improving overall compression efficiency while the system manages complexity through automated analysis and selection.
2Productivity
If multiple compression methods are analyzed for each data part, then the compression efficiency improves, but the CPU usage and processing time increase
Solution Approach 1:
The patent performs preliminary analysis of data segments to identify their characteristics before applying compression methods. By pre-analyzing and categorizing segments, the system avoids excessive CPU usage during the actual compression phase, as the selection of compression methods is predetermined based on segment characteristics.
Solution Approach 2:
The patent changes parameters such as segment size, analysis depth, and compression method selection criteria to optimize the balance between compression efficiency and CPU usage. By adjusting these parameters, the system can achieve high compression efficiency while controlling the computational resources required for analysis and method selection.
Data Source
AI summary
A system collects statistical data for a data page, divides the data page into parts, analyzes the data page and the statistical data, based on compression efficiency of one or more compression methods for each part of each page, to determine a compression method for each part of page, and compresses, based on the analyzing, the parts of the data page.