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Erasure codes are an integral part of many distributed storage systems aimedat Big Data, since they provide high fault-tolerance for low overheads.However, traditional erasure codes are inefficient on reading stored data indegraded environments (when nodes might be unavailable), and on replenishinglost data (vital for long term resilience). Consequently, novel codes optimizedto cope with distributed storage system nuances are vigorously beingresearched. In this paper, we take an engineering alternative, exploring theuse of simple and mature techniques -juxtaposing a standard erasure code withRAID-4 like parity. We carry out an analytical study to determine the efficacyof this approach over traditional as well as some novel codes. We build uponthis study to design CORE, a general storage primitive that we integrate intoHDFS. We benchmark this implementation in a proprietary cluster and in EC2. Ourexperiments show that compared to traditional erasure codes, CORE uses 50% lessbandwidth and is up to 75% faster while recovering a single failed node, whilethe gains are respectively 15% and 60% for double node failures.

The CORE Storage Primitive: Cross-Object Redundancy for Efficient Data Repair & Access in Erasure Coded Storage