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An Analysis of Data Corruption in the Storage Stack
Lakshmi N. Bairavasundaram, University of Wisconsin—Madison; Garth Goodson, Network Appliance, Inc.; Bianca Schroeder, University of Toronto; Andrea C. Arpaci-Dusseau, and Remzi H. Arpaci-Dusseau, University of Wisconsin—Madison;
An important threat to reliable storage of data is silent data corruption. In order to develop suitable protection mechanisms against data corruption, it is essential to understand its characteristics. In this paper, we present the first large-scale study of data corruption. We analyze corruption instances recorded in production storage systems containing a total of million disk drives, over a period of months. We study three classes of corruption: checksum mismatches, identity discrepancies, and parity inconsistencies. We focus on checksum mismatches since they occur the most.
We find more than 400,000 instances of checksum mismatches over the 41-month period. We find many interesting trends among these instances including: (i) nearline disks (and their adapters) develop checksum mismatches an order of magnitude more often than enterprise class disk drives, (ii) checksum mismatches within the same disk are not independent events and they show high spatial and temporal locality, and (iii) checksum mismatches across different disks in the same storage system are not independent. We use our observations to derive lessons for corruption-proof system design.
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