LSM Tree File System for Object Storage Write Amplification
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Solution Overview
Problem
Current object storage platforms are inefficient for data operations that involve small changes to large files due to high write amplification and the expense of transferring many small files, as they often require rewriting entire files or making multiple requests for small objects.
Innovation Solution
Implementing a log-structured merge (LSM) tree file system on top of object storage platforms, which uses sorted data tables with payload and index portions for efficient data storage and retrieval, allowing for immutable writes, low write amplification, and batching data writes to reduce costs, while enabling features like compression, encryption, and checksum verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If object storage platform is used for storing data, then storage capacity and cost-effectiveness are improved, but write amplification increases and data retrieval efficiency deteriorates
Solution Approach 1:
The patent segments data into sorted data tables with separate index portions and payload portions. Each sorted data table stores data in a structured format with keys mapped to their locations, enabling efficient retrieval without scanning entire datasets. This segmentation resolves the contradiction by organizing data in a way that maintains high storage capacity while improving retrieval efficiency through targeted access.
Solution Approach 2:
The patent introduces an LSM tree file system as an intermediary layer between the object storage platform and user applications. This intermediary implements sorted data tables with indexes that mediate between the raw object storage and data retrieval operations, transforming the storage platform into a more efficient data access system while preserving the underlying storage capacity.
2Quantity of substance
If object storage platform is used for storing data, then storage cost is reduced, but write amplification increases when overwriting data
Solution Approach 1:
The patent applies preliminary action by pre-sorting data and maintaining sorted data tables before writing to object storage. Data is organized into sorted structures with indexes created in advance, allowing for efficient updates and overwrites without requiring complete rewrites. This preliminary organization reduces write amplification while maintaining cost-effective storage.
Solution Approach 2:
The patent changes the organizational parameters of data storage by implementing sorted data tables with specific key-value structures and index mappings. By transforming raw data into sorted formats with metadata indexes, the system enables more efficient write operations and reduces write amplification while preserving the cost benefits of object storage.
3Adaptability or versatility
If many small files are stored on object storage platform, then data diversity is improved, but data transfer cost increases due to multiple requests
Solution Approach 1:
The patent merges multiple small files into sorted data tables that are organized by key ranges. Related small files are combined into structured tables with shared indexes, reducing the number of separate requests needed. This merging maintains data diversity while reducing transfer costs by consolidating access patterns.
Solution Approach 2:
The sorted data table structure serves multiple functions: it stores diverse small files, provides efficient indexing, enables batched reads, and supports various query patterns. This multi-functional structure reduces the need for separate operations on individual small files, thereby reducing data transfer costs while maintaining adaptability.
4Productivity
If LSM tree file system is implemented, then write efficiency is improved, but system complexity increases
Solution Approach 1:
The LSM tree file system implements self-service through automatic sorting, indexing, and compaction operations. The system autonomously manages the complexity of maintaining sorted data tables and indexes without requiring manual intervention, thereby improving write efficiency while containing system complexity through automation.
Data Source
AI summary
The disclosure herein describes providing and accessing data on an object storage platform using a log-structured merge (LSM) tree file system. The LSM tree file system on the object storage platform includes sorted data tables, each sorted data table including a payload portion and an index portion. Data is written to the LSM tree file system in at least one new sorted data table. Data is ready by identifying a data location of the data based on index portions of the sorted data tables and reading the data from a sorted data table associated with the identified data location. The use of the LSM tree file system on the object storage platform provides an efficient means for interacting with the data stored thereon.