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一种基于LSM树的键值存储系统性能优化方法 被引量:6
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作者 王海涛 李战怀 +1 位作者 张晓 赵晓南 《计算机研究与发展》 EI CSCD 北大核心 2019年第8期1792-1802,共11页
目前,键值(key-value, KV)存储系统在众多数据密集型的应用系统中发挥着关键作用,例如页面索引、电子商务以及云存储系统等.在各种键值存储系统中,基于日志结构合并(log-structured merge, LSM)树的KV存储系统获得了广泛的应用.主要原... 目前,键值(key-value, KV)存储系统在众多数据密集型的应用系统中发挥着关键作用,例如页面索引、电子商务以及云存储系统等.在各种键值存储系统中,基于日志结构合并(log-structured merge, LSM)树的KV存储系统获得了广泛的应用.主要原因是基于LSM树的KV存储系统能够将随机写操作转化为顺序写操作,从而提升数据写性能.然而,这些存储系统也存在一些严重的性能问题.一方面,KV存储系统利用预写日志机制来保证写入数据的原子性和安全性,以便在系统发生故障时进行恢复,造成了数据的写放大.同时,日志的频繁更新也引入了严重的元数据负载,导致了额外的性能开销.另一方面,KV存储系统通常利用通用文件系统存储数据,而通用文件系统中许多KV存储系统不需要的功能和属性也会造成一定的性能开销.为了减小这些开销、提升KV存储系统写入性能,提出了RocksFS,一个针对基于LSM树的KV存储系统优化的文件系统.针对KV存储系统的负载模式简化文件系统结构,去除通用文件系统引入的负载,同时优化预写日志的存储结构和更新流程以减小其更新负载,提升写入性能.最后在普通硬盘和固态硬盘上,基于流行的KV存储系统RocksDB验证了该方法的有效性,结果显示相对于通用文件系统,RocksFS能够将小块KV数据写入和更新性能提高约8倍. 展开更多
关键词 LSM树 键值存储 文件系统 预写日志 写性能
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MyWAL:performance optimization by removing redundant input/output stack in key-value store
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作者 Xiao ZHANG Mengyu LI +2 位作者 Michael NGULUBE Yonghao CHEN Yiping ZHAO 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2023年第7期980-993,共14页
Based on a log-structured merge(LSM)tree,the key-value(KV)storage system can provide high reading performance and optimize random writing performance.It is widely used in modern data storage systems like e-commerce,on... Based on a log-structured merge(LSM)tree,the key-value(KV)storage system can provide high reading performance and optimize random writing performance.It is widely used in modern data storage systems like e-commerce,online analytics,and real-time communication.An LSM tree stores new KV data in the memory and flushes to disk in batches.To prevent data loss in memory if there is an unexpected crash,RocksDB appends updating data in the write-ahead log(WAL)before updating the memory.However,synchronous WAL significantly reduces writing performance.In this paper,we present a new WAL mechanism named MyWAL.It directly manages raw devices(or partitions)instead of saving data on a traditional file system.These can avoid useless metadata updating and write data sequentially on disks.Experimental results show that MyWAL can significantly improve the data writing performance of RocksDB compared to the traditional WAL for small KV data on solid-state disks(SSDs),as much as five to eight times faster.On non-volatile memory express soild-state drives(NVMe SSDs)and non-volatile memory(NVM),MyWAL can improve data writing performance by 10%–30%.Furthermore,the results of YCSB(Yahoo!Cloud Serving Benchmark)show that the latency decreased by 50%compared with SpanDB. 展开更多
关键词 Key-value(KV)store log-structured merge(LSM)tree Non-volatile memory(NVM) Non-volatile memory express soild-state drive(NVMe SSD) write-ahead log(wal)
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