Spider Codes: Practical Erasure Codes For Distributed Storage Systems

Distributed storage systems use erasure codes to reliably store data with a small storage overhead. To further improve system performance, some novel erasure codes introduce new features such as the regenerating property or symbol locality, enabling these codes to have optimal repair times and optimal degraded read performance. Unfortunately, the introduction of these new features often exacerbates the performance of other system metrics such as encoding throughput, data reliability, and storage overhead, among others. In this paper we describe the intricate relationships between erasure code properties and system-level performance metrics, showing the different trade-offs distributed storage designers need to face. We also present Spider Codes, a new erasure code achieving a practical trade-off between the different system-level performance metrics.