Immutable KVS Tree for Reducing Write Amplification
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Solution Overview
Problem
LSM trees face issues such as significant write amplification, inefficient search performance, and limited write throughput due to their constant merging and sorted nature, leading to increased wear on SSDs and resource consumption.
Innovation Solution
The KVS tree employs a tree structure with temporally ordered key-value sets that are immutable, using a determinative mapping for child node placement and separating keys from values, allowing for efficient search and reduced write amplification through maintenance operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LSM trees use constant merging and sorted structure, then search efficiency is improved, but write amplification increases and SSD wear increases
Solution Approach 1:
The patent segments the tree structure into immutable key-value sets at different levels, where each level contains sorted data but merging is not constant. Instead of continuously merging sorted structures, the patent divides data into discrete immutable sets that are written once and never modified, reducing the frequency and cost of merge operations while preserving search efficiency through the hierarchical sorted structure.
Solution Approach 2:
The patent inverts the traditional LSM approach by making key-value sets immutable rather than mutable. Instead of continuously modifying and re-merging sorted structures, the system writes immutable sorted sets and uses compaction to manage space, reversing the conventional approach of frequent merges in favor of immutable writes with periodic compaction.
2Reliability
If LSM trees use constant merging operations, then data consistency is maintained, but write throughput is limited
Solution Approach 1:
The patent applies preliminary action by pre-sorting key-value pairs into immutable sets before writing to storage. The compaction process is triggered by predefined conditions (such as space utilization thresholds) rather than occurring continuously, allowing batches of writes to be accumulated and processed together, thereby improving throughput while maintaining consistency through the immutable nature of each write operation.
3Speed
If LSM trees maintain sorted structure, then search performance is improved, but resource consumption increases
Solution Approach 1:
The patent implements periodic action through compaction operations that are triggered by thresholds rather than occurring continuously. The sorted structure is maintained at write time within immutable key-value sets, and compaction periodically reorganizes space by merging immutable sets from different levels. This periodic approach reduces continuous resource consumption while preserving search performance through the maintained sorted hierarchy.
Data Source
AI summary
Systems and techniques for merge tree modifications for maintenance operations are described herein. A request for a KVS tree is received. Here, the KVS tree is a data structure including nodes and the nodes include a temporally ordered sequence of kvsets that store keys in sorted order. A parameter set for the KVS tree is received. The request is executed on the KVS tree by modifying operation of the KVS tree in accordance with the parameter.