摘要
在基于三副本策略的分布式存储系统中,当存储节点上的硬盘出现故障时,常见的处理方式是等待系统预设的时间.如果该故障硬盘超时未恢复,才开始恢复故障硬盘上的副本.这种处理方式存在的问题是,当三副本组中存在故障副本时,如果该副本组再有一个副本所在的硬盘发生故障,将导致系统无法继续提供服务,且不能自动恢复.本文提出一种基于日志副本的改进的Raft共识算法,即LR-Raft (log replica based Raft),日志副本没有完整状态机,可以快速加入集群,并参与投票与共识,提升了存在故障硬盘时系统的可用性;可以解决短时间内三副本中两个副本故障导致集群不可用和丢失数据的问题.实验结果表明,在副本组中引入日志副本后,与原Raft相比,LR-Raft在不同的工作负载下读写时延均明显降低,吞吐量显著提升.
In a distributed storage system based on a three-replica strategy,when a hard disk on the storage node fails,a common processing method is to wait for the system's preset time.If the faulty disk doesn't recover within the specified timeout,the recovery of the replicas on the faulty hard disk will begin.The issue with this handling approach is that when there is a faulty replica within the three-replica group,another disk failure in the same group will result in the system being unable to continue providing services and recover automatically.This study introduces an improved Raft consensus algorithm based on log replicas,namely log replica based Raft(LR-Raft).Log replicas do not have a complete state machine,allowing them to quickly join the cluster and participate in voting and consensus,thereby enhancing system availability in the presence of a faulty disk.It can address the problem of unavailability and data loss in the cluster caused by the failure of two replicas in a three-replica setup in a short period.The experimental results indicate that with the introduction of log replicas into the replica group,LR-Raft significantly reduces read and write latency and substantially improves throughput compared to the original Raft across various workloads.
作者
雷磊
胡晓鹏
黄岩
LEI Lei;HU Xiao-Peng;HUANG Yan(School of Computing and Artificial Intelligence,Southwest Jiaotong University,Chengdu 611756,China;Yunhe Enmo(Beijing)Information Technology Co.Ltd.,Beijing 100010,China)
出处
《计算机系统应用》
2024年第6期242-250,共9页
Computer Systems & Applications
基金
河北省自然科学基金(F2022105033)。
关键词
分布式存储系统
Raft共识算法
故障处理
日志副本
日志压缩优化
distributed storage system
Raft consensus algorithm
fault handling
log replica
log compression optimization
