基于SSD-SMR混合存储的LSM树键值存储系统的性能优化 (Performance Optimization of LSM Tree Key-value Storage System Based on SSD-SMR Hybrid Storage)

Yangyang Wang, Haocheng Wei, Yunpeng Chai

Abstract: Because of the higher requirements on the scalability,performance,and cost for storage systems proposed by big data,Shingled Magnetic Recording (SMR) disks are widely used in big data storage systems due to the high storage density and low cost.However,since the random write performance of SMR disks are usually weak,the hybrid storage consisted of both SMR disks and the fast Flash-based Solid State Drives (SSDs) can promote the performance significantly.Meanwhile,the write-optimized Log-Structured Merge (LSM) Tree-based key-valuestorage system have been widely used in many NoSQL systems,such as BigTable,Cassandra,HBase,etc.Therefore,how to construct a fast LSM tree key-value storage system based on SSD-SMR hybrid storage is a research problem with great practical significance.This paper first modeled the performance model of LSM tree key-value storage system based on SSD-SMR hybrid sto-rage,and then designed a performance-optimized LSM tree key-value storage system and implemented it based on Le-velDB.The evaluation results indicate that the system based on SSD-SMR hybrid storage improves the random-write performance by 20% and improves random-read performance by 6 times coupled with only a very small SSD (i.e.,0.4%~2% of disk capacity) compared with the HDD-based solution.