On the Effectiveness of Polynomial Realization of Reed-Solomon Codes for Storage Systems

There are different ways to realize Reed Solomon (RS) codes. While in the storage community, using the generator matrices to implement RS codes is more popular, in the coding theory community the generator polynomials are typically used to realize RS codes. Prominent exceptions include HDFS-RAID, which uses generator polynomial based erasure codes, and extends the Apache Hadoops file system. In this paper we evaluate the performance of an implementation of polynomial realization of Reed-Solomon codes, along with our optimized version of it, against that of a widely-used library (Jerasure) that implements the main matrix realization alternatives. Our experimental study shows that despite significant performance gains yielded by our optimizations, the polynomial implementations performance is constantly inferior to those of matrix realization alternatives in general, and that of Cauchy bit matrices in particular.

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

Erasure codes are an integral part of many distributed storage systems aimed at Big Data, since they provide high fault-tolerance for low overheads. However, traditional erasure codes are inefficient on reading stored data in degraded environments (when nodes might be unavailable), and on replenishing lost data (vital for long term resilience). Consequently, novel codes optimized to cope with distributed storage system nuances are vigorously being researched. In this paper, we take an engineering alternative, exploring the use of simple and mature techniques -juxtaposing a standard erasure code with RAID-4 like parity. We carry out an analytical study to determine the efficacy of this approach over traditional as well as some novel codes. We build upon this study to design CORE, a general storage primitive that we integrate into HDFS. We benchmark this implementation in a proprietary cluster and in EC2. Our experiments show that compared to traditional erasure codes, CORE uses 50% less bandwidth and is up to 75% faster while recovering a single failed node, while the gains are respectively 15% and 60% for double node failures.