Storage System Compression Read Performance Balance
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Solution Overview
Problem
Existing data storage systems face challenges in balancing data compression and read performance, as conventional compression techniques often fail to effectively utilize similarity between data chunks to improve compression efficiency while maintaining efficient data access.
Innovation Solution
The proposed solution involves partitioning data into chunks, determining their similarity based on sketches or features, and reorganizing them to store similar chunks together, allowing for enhanced compression by standard compressors while preserving metadata for reconstruction and optimizing storage layout to balance compression efficiency with read performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data chunks are reorganized to store similar chunks together to improve compression efficiency, then compression rate is improved, but read performance deteriorates due to increased I/O operations and data movement overhead
Solution Approach 1:
The patent segments data into chunks and creates multiple compression regions with different organization strategies. Hot data chunks are placed in one region while cold data chunks are placed in another, allowing the system to optimize compression for cold data without impacting read performance for hot data.
Solution Approach 2:
The patent applies different storage organization strategies to different portions of data based on their access characteristics. Frequently accessed data maintains its original sequential layout for optimal read performance, while infrequently accessed data is reorganized by similarity to maximize compression efficiency.
2Productivity
If a large redundancy window is used to find more internal redundancy for better compression, then compression efficiency is improved, but computation time and memory usage increase
Solution Approach 1:
The patent applies compression transformation only to data chunks that are infrequently accessed (cold data), rather than transforming all data. This partial application of the compression technique achieves the benefits of improved compression efficiency while avoiding the computational overhead of processing all data.
Solution Approach 2:
The system performs data transformation in advance during off-peak times when data is written or during maintenance windows, so that the computationally intensive similarity-based reorganization is completed before read operations occur, eliminating the impact on read performance.
Data Source
AI summary
Techniques for balancing data compression and read performance of data chunks of a storage system are described herein. According to one embodiment, similar data chunks are identified based on sketches of a plurality of data chunks stored in the storage system. A first portion of the similar data chunks as a first group is associated with a first storage area. The first storage area is associated with one or more data chunks that are dissimilar to the first group but are likely accessed together. The first group of the similar data chunks and its associated dissimilar data chunks are compressed and stored in the first storage area.