HashTag Erasure Codes: From Theory to Practice

TL;DR

HashTag Erasure Codes (HTECs) are a practical high-rate MDS code that significantly reduce repair bandwidth and I/O operations in distributed storage, outperforming existing MSR codes especially for multiple failures.

Contribution

This paper introduces HashTag Erasure Codes (HTECs), a new class of high-rate MDS codes optimized for storage, reliability, and repair efficiency, with practical Hadoop implementation.

Findings

HTECs achieve the lowest data-read and transfer among MDS codes.

HTECs reduce repair bandwidth for multiple failures.

Practical Hadoop implementation demonstrates high potential.

Abstract

Minimum-Storage Regenerating (MSR) codes have emerged as a viable alternative to Reed-Solomon (RS) codes as they minimize the repair bandwidth while they are still optimal in terms of reliability and storage overhead. Although several MSR constructions exist, so far they have not been practically implemented mainly due to the big number of I/O operations. In this paper, we analyze high-rate MDS codes that are simultaneously optimized in terms of storage, reliability, I/O operations, and repair-bandwidth for single and multiple failures of the systematic nodes. The codes were recently introduced in \cite{7463553} without any specific name. Due to the resemblance between the hashtag sign \# and the procedure of the code construction, we call them in this paper \emph{HashTag Erasure Codes (HTECs)}. HTECs provide the lowest data-read and data-transfer, and thus the lowest repair time for an arbitrary sub-packetization level $\alpha$, where $\alpha \leq r^{\lceil \sfrac{k}{r} \rceil}$, among all existing MDS codes for distributed storage including MSR codes. The repair process is linear and highly parallel. Additionally, we show that HTECs are the first high-rate MDS codes that reduce the repair bandwidth for more than one failure. Practical implementations of HTECs in Hadoop release 3.0.0-alpha2 demonstrate their great potentials.