Rethink the Linearizability Constraints of Raft for Distributed Systems
Yangyang Wang, Zikai Wang, Yunpeng Chai, Xin Wang · IEEE Transactions on Knowledge and Data Engineering · 2023
With the deployment of modern hardware such as Flash-based SSDs and the high-speed network in distributed systems, the distributed consensus and consistency module (e.g., Raft) is typically the most time-consuming part. The reason lies in that Raft introduces some very strict constraints to ensure the linearizability. Therefore, in this paper, we rethink these constraints in-depth and find that some of them are not necessary, and can be broken to accelerate the performance significantly without breaking the linear consistency for distributed systems. An improved distributed consensus algorithm calledBUC-Raft(Breaking Unnecessary Constraints of Raft) is proposed in this paper and implemented in an industry-level distributed system. The experimental results suggest that both the write and the read performance can be accelerated significantly by BUC-Raft.