Coupling Decentralized Key-Value Stores with Erasure Coding
Liangfeng Cheng, Yuchong Hu, Patrick P. C. Lee · 2019
Modern decentralized key-value stores often replicate and distribute data via consistent hashing for availability and scalability. Compared to replication, erasure coding is a promising redundancy approach that provides availability guarantees at much lower cost. However, when combined with consistent hashing, erasure coding incurs a lot of parity updates during scaling (i.e., adding or removing nodes) and cannot efficiently handle degraded reads caused by scaling. In this paper, we propose a novel erasure coding model called FragEC, which incurs no parity updates during scaling. We further extend consistent hashing with multiple hash rings to enable erasure coding to seamlessly address degraded reads during scaling. We realize our design as an in-memory key-value store called ECHash, and conduct testbed experiments on different scaling workloads in both local and cloud environments. We show that ECHash achieves better scaling performance (in terms of scaling throughput and degraded read latency during scaling) over the baseline erasure coding implementation, while maintaining high basic I/O and node repair performance.