基于大数据技术的非关系型数据库分布式存储
摘 要
随着信息技术的迅猛发展，数据量呈爆炸式增长，传统关系型数据库在处理海量、非结构化数据时面临诸多挑战。为此，本研究聚焦于基于大数据技术的非关系型数据库分布式存储，旨在构建一种高效、可扩展且具备高容错性的分布式存储系统。通过深入分析NoSQL数据库的特点与优势，结合Hadoop生态系统中的HDFS和MapReduce框架，提出了一种新型分布式存储架构。该架构采用分片机制将大规模数据集划分为多个子集，并利用一致性哈希算法实现数据均衡分布，同时引入多副本机制以确保数据可靠性。实验结果表明，在处理PB级数据量时，所提方案相较于传统方法具有更高的读写性能和更低的延迟，特别是在并发访问场景下表现尤为突出。此外，本研究还实现了自动故障检测与恢复功能，进一步增强了系统的稳定性和可用性。创新点在于融合了多种先进技术，不仅解决了海量数据存储问题，还为复杂查询提供了优化支持，为大数据环境下的非关系型数据库应用提供了新的思路和技术参考。
关键词：大数据技术；非关系型数据库；分布式存储
Abstract
With the rapid development of information technology and the explosive growth of data volumes, traditional relational databases face numerous challenges in handling massive and unstructured data. This study focuses on distributed storage systems based on big data technologies for non-relational databases, aiming to construct an efficient, scalable, and highly fault-tolerant distributed storage system. By thoroughly analyzing the characteristics and advantages of NoSQL databases, and integrating HDFS and MapReduce fr ameworks from the Hadoop ecosystem, a novel distributed storage architecture is proposed. This architecture employs sharding mechanisms to partition large-scale datasets into multiple subsets, utilizes consistent hashing algorithms for balanced data distribution, and introduces multi-replica mechanisms to ensure data reliability. Experimental results demonstrate that, when processing petabyte-scale data volumes, the proposed solution exhibits superior read and write performance and lower latency compared to traditional methods, particularly under concurrent access scenarios. Additionally, this research implements automatic fault detection and recovery functions, further enhancing system stability and availability. The innovation lies in the integration of various advanced technologies, not only addressing the issue of massive data storage but also providing optimized support for complex queries, offering new insights and technical references for non-relational database applications in big data environments.
Keywords: Big Data Technology；Non-Relational Database；Distributed Storage
目 录
摘 要 I
Abstract II
引言 1
一、非关系型数据库概述 1
（一）非关系型数据库类型 1
（二）发展历程与现状 2
（三）技术优势分析 2
二、大数据技术基础 2
（一）大数据特征解析 3
（二）关键技术组件 3
（三）存储需求分析 4
三、分布式存储架构设计 4
（一）架构模型选择 4
（二）数据分片策略 5
（三）一致性保障机制 5
四、性能优化与实践应用 5
（一）查询性能优化 5
（二）容错能力提升 6
（三）实际案例研究 6
结 论 7
致 谢 8
参考文献 9
摘 要
随着信息技术的迅猛发展，数据量呈爆炸式增长，传统关系型数据库在处理海量、非结构化数据时面临诸多挑战。为此，本研究聚焦于基于大数据技术的非关系型数据库分布式存储，旨在构建一种高效、可扩展且具备高容错性的分布式存储系统。通过深入分析NoSQL数据库的特点与优势，结合Hadoop生态系统中的HDFS和MapReduce框架，提出了一种新型分布式存储架构。该架构采用分片机制将大规模数据集划分为多个子集，并利用一致性哈希算法实现数据均衡分布，同时引入多副本机制以确保数据可靠性。实验结果表明，在处理PB级数据量时，所提方案相较于传统方法具有更高的读写性能和更低的延迟，特别是在并发访问场景下表现尤为突出。此外，本研究还实现了自动故障检测与恢复功能，进一步增强了系统的稳定性和可用性。创新点在于融合了多种先进技术，不仅解决了海量数据存储问题，还为复杂查询提供了优化支持，为大数据环境下的非关系型数据库应用提供了新的思路和技术参考。
关键词：大数据技术；非关系型数据库；分布式存储
Abstract
With the rapid development of information technology and the explosive growth of data volumes, traditional relational databases face numerous challenges in handling massive and unstructured data. This study focuses on distributed storage systems based on big data technologies for non-relational databases, aiming to construct an efficient, scalable, and highly fault-tolerant distributed storage system. By thoroughly analyzing the characteristics and advantages of NoSQL databases, and integrating HDFS and MapReduce fr ameworks from the Hadoop ecosystem, a novel distributed storage architecture is proposed. This architecture employs sharding mechanisms to partition large-scale datasets into multiple subsets, utilizes consistent hashing algorithms for balanced data distribution, and introduces multi-replica mechanisms to ensure data reliability. Experimental results demonstrate that, when processing petabyte-scale data volumes, the proposed solution exhibits superior read and write performance and lower latency compared to traditional methods, particularly under concurrent access scenarios. Additionally, this research implements automatic fault detection and recovery functions, further enhancing system stability and availability. The innovation lies in the integration of various advanced technologies, not only addressing the issue of massive data storage but also providing optimized support for complex queries, offering new insights and technical references for non-relational database applications in big data environments.
Keywords: Big Data Technology；Non-Relational Database；Distributed Storage
目 录
摘 要 I
Abstract II
引言 1
一、非关系型数据库概述 1
（一）非关系型数据库类型 1
（二）发展历程与现状 2
（三）技术优势分析 2
二、大数据技术基础 2
（一）大数据特征解析 3
（二）关键技术组件 3
（三）存储需求分析 4
三、分布式存储架构设计 4
（一）架构模型选择 4
（二）数据分片策略 5
（三）一致性保障机制 5
四、性能优化与实践应用 5
（一）查询性能优化 5
（二）容错能力提升 6
（三）实际案例研究 6
结 论 7
致 谢 8
参考文献 9
