We propose repair pipelining , a technique that speeds up the repair performance in general erasure-coded storage. By carefully scheduling the repair of failed data in small-size units across storage nodes in a pipelined manner, repair pipelining reduces the single-block repair time to approximately the same as the normal read time for a single block in homogeneous environments. We further design different extensions of repair pipelining algorithms for heterogeneous environments and multi-block repair operations. We implement a repair pipelining prototype, called ECPipe , and integrate it as a middleware system into two versions of Hadoop Distributed File System (HDFS) (namely, HDFS-RAID and HDFS-3) as well as Quantcast File System. Experiments on a local testbed and Amazon EC2 show that repair pipelining significantly improves the performance of degraded reads and full-node recovery over existing repair techniques.

中文翻译：

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擦除编码存储的修复流水线：算法和评估

我们建议修复流水线，一种在一般纠删码存储中加快修复性能的技术。通过以流水线方式仔细调度跨存储节点的小单元故障数据的修复，修复流水线将单块修复时间减少到与同构环境中单个块的正常读取时间大致相同。我们进一步为异构环境和多块修复操作设计了修复流水线算法的不同扩展。我们实现了一个修复流水线原型，称为ECPipe，并将其作为中间件系统集成到两个版本的Hadoop分布式文件系统（HDFS）（即HDFS-RAID和HDFS-3）以及Quantcast文件系统中。在本地测试平台和 Amazon EC2 上的实验表明，与现有修复技术相比，修复管道显着提高了降级读取和全节点恢复的性能。