An efficient backup-recovery technique to process large data in distributed key-value store

Abstract

As the demand for the high-speed processing of mass data increases, the use of in-memory systems is increasing. In-memory systems enable data to be accessed in memory, thereby allowing for its high-speed processing. However, as the size and volume of the data increases, its recovery speed from a replicated server gets slower. In this paper, we propose a backup-recovery technique allowing quick recovery by distributing and replicating data onto various slave servers and recovering them data from the simultaneously during disaster recovery. We realized the proposed technique using Redis, an open source distributed memory system. The results showed that the equal key distribution and recovery performance with the proposed technique was improved by 51.4%. Copyright 2015 ACM.