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FAST ‘08:

Storage Failures. Dvir Olansky. FAST ‘08: L.N. Bairavasundaram , G. R. Goodson, B. Schroeder, A. C. Arpaci-Dusseau and R. H. Arpaci-Dusseau : An Analysis of Data Corruption in the Storage Stack.

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FAST ‘08:

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  1. Storage Failures Dvir Olansky FAST ‘08: L.N. Bairavasundaram, G. R. Goodson, B. Schroeder, A. C. Arpaci-Dusseau and R. H. Arpaci-Dusseau: An Analysis of Data Corruption in the Storage Stack. W. Jiang, C. Hu, A. Kanevsky, and Y.Zhou: Are Disks the Dominant Contributor for Storage Failures?A Comprehensive Study of Storage Subsystem Failure Characteristics Advanced Topics in Storage Systems Spring 2013

  2. Outline • Problem Addressed • Main Findings • Storage System Architecture • Results • Conclusions and Implications

  3. Problem Addressed Storage failures from a system perspective: • Silent Data Corruptions. • Failures of storage system components besides disks. • Statistical properties of storage system failures.

  4. Main Findings • Disk failures contribute to only 20-55% of storage system failures. • Storage failures are not independent. • Storage failures show strong spatial and temporal locality.

  5. Storage System Architecture

  6. Storage System Architecture

  7. Nearline Vs. Enterprise Disks • Enterprise Disks– Fiber Channel Interface Disks. • Low-end, Med-Range, High-end. • Nearline Disks – ATA Interface (mostly SATA).

  8. Corruption Detection Mechanisms • Storage system does not knowingly propagate corrupt data to the user under any circumstance. • Data Integrity Segments in each File System block.

  9. NetAppAutoSupport Database • Built-in, low-overhead mechanism to log important system events to a central repository. • Over 1.5M disks included in about 39,000 storage systems for a period of over 40 months. • Unprecedented sample size. • Both papers rely on this database.

  10. Results Enterprise Nearline

  11. Results

  12. Results • Corrupt ES disks develop many more checksum mismatches than corrupt NL disks.

  13. Results • Checksum mismatches within the same disk are not independent:

  14. Results

  15. Results

  16. Results • Much if the observed spatial locality is due to consecutive disk blocks developing corruption.

  17. Results Theoretical

  18. Conclusions and Implications • Employ redundancy mechanisms to tolerate storage system component failures – Not only disks! • f.e. physical interconnect multipathing reduce AFR by 30-40%

  19. Conclusions and Implications • Redundant data structures should be stored distant from each other.

  20. Conclusions and Implications • Temporal and spatial locality can be leveraged for smarter scrubbing. • Trigger a scrub before it’s next scheduled time, when probability of corruption is high. • Selective scrubbing of an area of the disk that’s likely to be affected.

  21. Conclusions and Implications • Replacing ES disk on the first detection of corruption makes sense. • Replacement cost may not be a huge factor since the probability of the first corruption is low.

  22. Thank You

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