Data redundancy provides resilience in large-scale storage clusters, but imposes significant cost overhead. Substantial space-savings can be realized by tuning redundancy schemes to observed disk failure rates. However, prior design proposals for such tuning are unusable in real-world clusters, because the IO load of transitions between schemes overwhelms the storage infrastructure (termed transition overload). This paper analyzes traces for millions of disks from production systems at Google, NetApp, and Backblaze to expose and understand transition overload as a roadblock to disk-adaptive redundancy: transition IO under existing approaches can consume 100% cluster IO continuously for several weeks. Building on the insights drawn, we present PACEMAKER, a low-overhead disk-adaptive redundancy orchestrator. PACEMAKER mitigates transition overload by (1) proactively organizing data layouts to make future transitions efficient, and (2) initiating transitions proactively in a manner that avoids urgency while not compromising on space-savings. Evaluation of PACEMAKER with traces from four large (110K-450K disks) production clusters show that the transition IO requirement decreases to never needing more than 5% cluster IO bandwidth (0.2-0.4% on average). PACEMAKER achieves this while providing overall space-savings of 14-20% and never leaving data under-protected. We also describe and experiment with an integration of PACEMAKER into HDFS.
翻译:数据冗余在大型存储群集中提供了弹性数据冗余,但带来了巨大的成本管理。 大量空间节约可以通过调整冗余计划以适应磁盘故障率来实现。 但是,这种调整的事先设计提案在现实世界群集中是无法使用的,因为IO计划之间的过渡负荷超过了存储基础设施的负荷(过渡超负荷)。 本文分析了谷歌、 NetApp 和 Backblaze 生产系统中数百万张磁盘的痕迹,以避免紧迫感和理解过渡过量成为磁盘故障的路障。 根据现有办法,过渡性IOO可以连续消耗100 % 集聚集IO数周时间。 根据所得出的见解,我们提出PACEMAKER, 是一个低超版磁盘适应性磁盘冗余调调调调调调乐管弦乐团。 PACMAKR 减轻了过渡性超载力, 包括:(1) 积极主动地组织数据布局,以使未来过渡性数据结构高效,(2) 主动启动过渡性过渡性过渡,同时避免影响空间节约。 对PACKERERR的四大(K-50-20K) 生产组的微(IA-MERM) 也在I-M-MERM-M-M-M-M-M-M-MDERM-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-M-S-S-S-S-S-S-S-S-BAR-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-NL-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-N-