Data Page Partitioning for Adaptive Compression Efficiency
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Solution Overview
Problem
Existing data compression methods do not efficiently utilize different compression techniques for various parts of a data page, leading to suboptimal compression efficiency and performance.
Innovation Solution
A method of partitional data compression that involves collecting statistical data for a data page, dividing it into parts, analyzing the data and statistical information to determine the most efficient compression method for each part, and then compressing the parts using those methods.
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, allowing different compression methods to be applied to different segments. This segmentation enables the system to optimize compression efficiency for each segment while maintaining manageable complexity through systematic processing of divided portions.
Solution Approach 2:
The patent applies different compression methods to different parts of the data page based on the characteristics of each part. This local quality approach ensures that each segment is compressed using the most appropriate method for its specific data properties, thereby improving overall compression efficiency without requiring uniform complexity across the entire page.
2Productivity
If multiple compression methods are applied to different parts of the data page, then compression efficiency improves, but the processing time and CPU overhead increase
Solution Approach 1:
The patent performs preliminary analysis of data page characteristics before applying compression methods. By collecting statistical data and determining the appropriate compression method in advance, the system avoids unnecessary processing during the actual compression phase, thereby reducing overall processing time while maintaining high compression efficiency.
Solution Approach 2:
The patent applies compression methods selectively to parts of the data page rather than uniformly to the entire page. This partial action approach focuses computational resources on segments where compression provides the most benefit, reducing overall processing time while achieving efficient compression where needed.
3Quantity of substance
If data is divided into parts and different compression methods are applied, then storage requirements are reduced, but the complexity of managing multiple compression methods increases
Solution Approach 1:
The patent segments the data page into multiple parts, each compressed using the most appropriate method for that segment. This segmentation reduces overall storage requirements by optimizing compression for each segment while managing complexity through systematic organization of the divided portions.
Solution Approach 2:
The patent changes compression parameters (such as compression ratio, method type) based on the characteristics of different data segments. This parameter adaptation allows the system to achieve reduced storage requirements by tailoring compression settings to each segment's properties while maintaining manageable complexity through rule-based parameter 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.