Balancing Distributed Key-Value Stores with Efficient In-Network Redirecting

Abstract

Today’s cloud-based online services are underpinned by distributed key-value stores (KVSs). Keys and values are distributed across back-end servers in such scale-out systems. One primary real-life performance bottleneck occurs when storage servers suffer from load imbalance under skewed workloads. In this paper, we present KVSwitch, a centralized self-managing load balancer that leverages the power and flexibility of emerging programmable switches. The balance is achieved by dynamically predicting the hot items and by creating replication strategies according to KVS loading. To overcome the challenges in realizing KVSwitch given the limitations of the switch hardware, we decompose KVSwitch’s functions and carefully design them for the heterogeneous processors inside the switch. We prototype KVSwitch in a Tofino switch. Experimental results show that our solution can effectively keep the KVS servers balanced even under highly skewed workloads. Furthermore, KVSwitch only replicates 70 % of hot items and consumes 9.88 % of server memory rather than simply replicating all hot items to each server.