Fast Proactive Repair in Erasure-Coded Storage: Analysis, Design, and Implementation
Xiaolu Li, Keyun Cheng, Zhirong Shen, Patrick P. C. Lee
Abstract
Erasure coding offers a storage-efficient redundancy mechanism for maintaining data availability guarantees in large-scale storage clusters, yet it also incurs high performance overhead in failure repair. Recent developments in accurate disk failure prediction allow soon-to-fail (STF) nodes to be repaired in advance, thereby opening new opportunities for accelerating failure repair in erasure-coded storage. To this end, we present a fast proactive repair solution called <inline-formula><tex-math notation="LaTeX">${{\sf FastPR}}$</tex-math></inline-formula> , which carefully couples two repair methods, namely migration (i.e., relocating the chunks of an STF node) and reconstruction (i.e., decoding the chunks of an STF node through erasure coding), so as to fully parallelize the repair operation across the storage cluster. <inline-formula><tex-math notation="LaTeX">${{\sf FastPR}}$</tex-math></inline-formula> solves a bipartite maximum matching problem and schedules both migration and reconstruction in a parallel fashion. We show that <inline-formula><tex-math notation="LaTeX">${{\sf FastPR}}$</tex-math></inline-formula> significantly reduces the repair time over the baseline repair approaches for both Reed-Solomon codes and Azure's Local Reconstruction Codes via mathematical analysis, large-scale simulation, and Amazon EC2 experiments.