SST File Compaction Priority for ZNS SSD Zone Reclamation
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Solution Overview
Problem
The existing data compaction mechanisms for Log-Structured Merge-Tree (LSM-Tree) storage structures, such as RocksDB or LevelDB, do not efficiently prioritize SST file compaction based on overlapping key ranges and zone attributes, leading to suboptimal zone reclamation and reduced storage space utilization in ZNS SSDs.
Innovation Solution
A method and device for compacting SST files in a ZNS SSD, which determines the compaction priority of SST files based on their key overlapping ratios and zone attributes, allowing for the efficient selection and compaction of SST files that maximize zone reclamation and storage space utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If SST files are compacted without considering key overlapping ratios and zone attributes, then the compaction process is simple, but zone reclamation efficiency is reduced and storage space utilization decreases
Solution Approach 1:
The patent changes the parameters used for compaction decision-making from simple FIFO or size-based selection to a multi-parameter evaluation system that includes key overlapping ratios and zone attributes. This allows the system to prioritize SST files that will maximize zone reclamation when compacted, directly improving zone reclamation efficiency while managing complexity through structured parameter evaluation.
Solution Approach 2:
The patent implements a feedback mechanism where the compaction priority determination is based on evaluating key overlapping ratios between SST files and their potential target zones, along with zone attributes such as available space and usage patterns. This feedback loop enables the system to dynamically adjust compaction priorities to optimize zone reclamation efficiency rather than following a fixed compaction order.
2Quantity of substance
If SST files are compacted without priority-based selection, then the compaction operation is faster to initiate, but storage space utilization is reduced due to suboptimal zone reclamation
Solution Approach 1:
The patent changes the selection criteria for compaction from arbitrary or simple metrics to a parameter-based priority system that evaluates key overlapping ratios and zone attributes. This ensures that the SST files selected for compaction are those that will result in the greatest storage space utilization improvement through efficient zone reclamation, directly addressing the quantity of usable storage space.
Solution Approach 2:
The patent performs preliminary evaluation of key overlapping ratios and zone attributes before initiating compaction operations. By pre-calculating and prioritizing SST files based on their potential to improve storage space utilization, the system avoids unnecessary compaction operations and ensures that each compaction event contributes maximally to space reclamation, reducing wasted time on ineffective operations.
3Object-generated harmful factors
If existing compaction mechanisms are used, then implementation is straightforward, but host-based garbage collection is increased and write amplification is minimized poorly
Solution Approach 1:
The patent changes the compaction mechanism from simple sequential or size-based processing to a priority-based system that evaluates key overlapping ratios and zone attributes. This optimized approach reduces write amplification by ensuring that compaction operations are performed on SST files that will most effectively reclaim zones, thereby reducing the need for subsequent host-based garbage collection operations and minimizing redundant write operations.
Solution Approach 2:
The patent implements feedback-based priority determination where the compaction process continuously evaluates key overlapping ratios and zone attributes to identify the most beneficial SST files for compaction. This feedback mechanism reduces harmful write amplification effects by directing compaction resources toward operations that will most effectively reduce the need for host-based garbage collection, creating a self-optimizing compaction process.
Data Source
AI summary
A compaction method and device for SST files are provided. The method includes identifying one or more first SST files and one or more second SST files, obtaining priority information based on a key overlapping ratio between the one or more first SST files and one or more second SST files, obtaining attribute information of zones corresponding to the one or more first SST files and the one or more second SST files, and performing compaction on a first SST file, among the one or more first SST files based the priority information.