摘 要
随着信息技术的迅猛发展，数据量呈爆炸式增长，传统存储系统在处理海量数据时面临诸多挑战，如存储容量有限、数据访问效率低等。为此，本研究旨在设计与实现一种适用于大数据环境下的分布式存储系统，以解决上述问题并提高数据管理能力。该系统基于Hadoop架构，采用Erasure Code冗余编码技术替代传统的三副本机制，在保证数据可靠性的前提下有效降低了存储开销；同时引入一致性哈希算法优化节点选择策略，确保数据分布均匀且易于扩展。通过构建多级缓存机制，实现了对热数据的快速响应，显著提升了读写性能。实验结果表明，所设计的分布式存储系统在面对大规模数据集时能够稳定运行，相较于现有方案具有更高的吞吐量和更低的延迟，特别是在高并发场景下优势明显。此外，该系统还具备良好的容错性和可维护性，当部分节点故障时可自动恢复数据完整性。总之，本研究提出的分布式存储系统为大数据处理提供了高效可靠的解决方案，其创新性的技术手段对于推动相关领域的发展具有重要意义。
关键词：分布式存储系统；Erasure Code冗余编码；一致性哈希算法；大数据处理；多级缓存机制
Abstract
With the rapid development of information technology, data volumes are experiencing explosive growth, posing numerous challenges to traditional storage systems when handling massive datasets, such as limited storage capacity and low data access efficiency. To address these issues and enhance data management capabilities, this study aims to design and implement a distributed storage system tailored for big data environments. The system is based on the Hadoop architecture and employs Erasure Code redundancy encoding technology instead of the traditional triple-replica mechanism, effectively reducing storage overhead while ensuring data reliability. Additionally, the Consistent Hashing algorithm is introduced to optimize node selection strategies, ensuring even data distribution and ease of scalability. A multi-level caching mechanism has been constructed to achieve rapid responses to hot data, significantly improving read and write performance. Experimental results demonstrate that the designed distributed storage system can operate stably with large-scale datasets, exhibiting higher throughput and lower latency compared to existing solutions, particularly in high-concurrency scenarios. Moreover, the system possesses excellent fault tolerance and maintainability, automatically restoring data integrity when partial nodes fail. In summary, the proposed distributed storage system provides an efficient and reliable solution for big data processing, and its innovative technical approaches hold significant implications for advancing relevant fields.
Keywords：Distributed Storage System；Erasure Code Redundancy Encoding；Consistent Hashing Algorithm；Big Data Processing；Multi-level Caching Mechanism
目 录
摘 要 I
Abstract II
引 言 1
第一章 大数据存储需求分析 2
1.1 大数据特征与挑战 2
1.2 存储系统性能要求 2
1.3 分布式架构优势 3
第二章 分布式存储系统架构设计 5
2.1 系统总体架构 5
2.2 数据分片策略 5
2.3 数据冗余机制 6
第三章 关键技术实现 8
3.1 一致性哈希算法 8
3.2 数据同步方法 8
3.3 故障恢复机制 9
第四章 系统性能优化 11
4.1 存储效率提升 11
4.2 并发访问控制 11
4.3 资源动态调度 12
结 论 14
参考文献 15
致 谢 16
