Dynamic Compression Ratio Control for Database Backup
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Solution Overview
Problem
Traditional database backup systems use static compression ratios, leading to bottlenecks and inefficiencies due to varying system loads and data composition, which hinder optimal backup performance in terms of time and compression efficiency.
Innovation Solution
A system with multiple read threads and write threads, utilizing dynamic compression ratios adjusted by a controller based on real-time system performance parameters, such as wait times and CPU consumption, to optimize data compression and backup speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a static compression ratio is used during backup, then the backup process is simple to implement, but the backup performance is hindered due to bottlenecks and inefficiencies from varying system loads and data composition
Solution Approach 1:
The patent applies dynamics by transitioning from a static compression ratio to a dynamic compression ratio that automatically adjusts during the backup process. The system monitors real-time system performance parameters (CPU usage, memory availability, disk I/O speed) and data compression effectiveness, then dynamically modifies the compression ratio to optimize backup performance under varying loads and data characteristics.
Solution Approach 2:
The patent implements feedback by introducing a monitoring mechanism that continuously measures system performance parameters and compression effectiveness during backup operations. This feedback loop allows the system to detect bottlenecks and adjust compression ratios in real-time based on actual performance data, ensuring optimal backup speed and resource utilization.
2Quantity of substance
If a high compression ratio is used to reduce backup size, then storage space is conserved, but backup time increases due to the computational overhead of compression
Solution Approach 1:
The system dynamically adjusts the compression ratio based on real-time monitoring of system resources and backup progress. When system load is low and resources are available, the compression ratio increases to maximize space savings. When system load increases or bottlenecks are detected, the compression ratio is reduced to maintain optimal backup speed, thus balancing storage efficiency with time consumption.
Solution Approach 2:
The patent changes the compression ratio parameter dynamically during the backup process based on monitored system conditions. The system evaluates CPU utilization, memory availability, and disk I/O performance to determine the optimal compression level at any given moment, adjusting the parameter to achieve the best trade-off between backup file size and backup time.
3Quantity of substance
If compression is performed to save storage space, then resource consumption for storage is reduced, but system resources (CPU, memory) are consumed during compression
Solution Approach 1:
The system dynamically modulates compression intensity based on real-time system resource availability. When CPU and memory resources are abundant, the system applies higher compression ratios to maximize storage savings. When system resources are constrained or heavily utilized by other processes, the compression ratio is automatically reduced to minimize additional resource consumption, ensuring balanced resource utilization.
Solution Approach 2:
The patent monitors system resource consumption during compression operations and uses this feedback to adjust compression parameters. The monitoring mechanism tracks CPU usage, memory allocation, and compression speed, allowing the system to modulate compression intensity to maintain optimal resource utilization while achieving desired storage savings.
Data Source
AI summary
A system and method for backing up a database, where the system has read threads running simultaneously, write threads, and data buffers. Each read thread repeats the following operations until all the data is backed up: read a block of data from the database, compress the data using a dynamic compression ratio which is initialized and adjusted after every compression, write the data to an available data buffer until the data buffer is full, write to the next available data buffer once the data buffer is full, and determine a new compression ratio. A controller determines the new compression ratio using either a method that monitors the timing of system components and/or a method that monitors CPU consumption.