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Distributed File Systems

Distributed File Systems. Sarah Diesburg Operating Systems COP 4610. Distributed File System. Provides transparent access to files stored on a remote disk Recurrent themes of design issues Failure handling Performance optimizations Cache consistency. No Client Caching.

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Distributed File Systems

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  1. Distributed File Systems Sarah Diesburg Operating Systems COP 4610

  2. Distributed File System • Provides transparent access to files stored on a remote disk • Recurrent themes of design issues • Failure handling • Performance optimizations • Cache consistency

  3. No Client Caching • Use RPC to forward every file system request to the remote server • open, seek, read, write Server cache: X read write Client A cache: Client B cache:

  4. No Client Caching + Server always has a consistent view of the file system - Poor performance - Server is a single point of failure

  5. Network File System (NFS) • Uses client caching to reduce network load • Built on top of RPC Server cache: X Client A cache: X Client B cache: X

  6. Network File System (NFS) + Performance better than no caching - Has to handle failures - Has to handle consistency

  7. Failure Modes • If the server crashes • Uncommitted data in memory are lost • Current file positions may be lost • The client may ask the server to perform unacknowledged operations again • If a client crashes • Modified data in the client cache may be lost

  8. NFS Failure Handling 1. Write-through caching 2. Stateless protocol: the server keeps no state about the client • read open, seek, read, close • No server recovery after a failure 3. Idempotent operations: repeated operations get the same result • No static variables

  9. NFS Failure Handling 4. Transparent failures to clients • Two options • The client waits until the server comes back • The client can return an error to the user application • Do you check the return value of close?

  10. NFS Weak Consistency Protocol • A write updates the server immediately • Other clients poll the server periodically for changes • No guarantees for multiple writers

  11. NFS Summary + Simple and highly portable - May become inconsistent sometimes • Does not happen very often

  12. Andrew File System (AFS) • Developed at CMU • Design principles • Files are cached on each client’s disks • NFS caches only in clients’ memory • Callbacks: The server records who has the copy of a file • Write-back cache on file close. The server then tells all clients that own an old copy. • Session semantics: Updates are only visible on close

  13. AFS Illustrated Server cache: X Client A Client B

  14. read X AFS Illustrated callback list of X client A Server cache: X Client A Client B read X

  15. read X AFS Illustrated callback list of X client A Server cache: X Client A cache: X Client B read X

  16. read X AFS Illustrated callback list of X client A Server cache: X Client A cache: X Client B read X

  17. read X AFS Illustrated callback list of X client A client B Server cache: X Client A cache: X Client B read X

  18. read X AFS Illustrated callback list of X client A client B Server cache: X Client A cache: X Client B cache: X read X

  19. AFS Illustrated Server cache: X Client A cache: X Client B cache: X write X, X  X

  20. X  X AFS Illustrated Server cache: X Client A cache: X Client B cache: X close X

  21. X  X AFS Illustrated Server cache: X Client A cache: X Client B cache: X close X

  22. AFS Illustrated Server cache: X Client A cache: X Client B cache: X close X

  23. X AFS Illustrated Server cache: X Client A cache: X Client B cache: X open X

  24. X AFS Illustrated Server cache: X Client A cache: X Client B cache: X open X

  25. AFS Failure Handling • If the server crashes, it asks all clients to reconstruct the callback states

  26. AFS vs. NFS • AFS • Less server load due to clients’ disk caches • Not involved for read-only files • Both AFS and NFS • Server is a performance bottleneck • Single point of failure

  27. Serverless Network File Service (xFS) • Idea: construct a file system as a parallel program and exploit the high-speed LAN • Four major pieces • Cooperative caching • Write-ownership cache coherence • Software RAID • Distributed control

  28. Cooperative Caching • Uses remote memory to avoid going to disk • On a cache miss, check the local memory and remote memory, before checking the disk • Before discarding the last cached memory copy, send the content to remote memory if possible

  29. Cooperative Caching Client A cache: X Client B cache: Client C cache: Client D cache:

  30. X Cooperative Caching Client A cache: X Client B cache: Client C cache: Client D cache: read X

  31. X Cooperative Caching Client A cache: X Client B cache: Client C cache: X Client D cache: read X

  32. Write-Ownership Cache Coherence • Declares a client to be a owner of the file at writes • No one else can have a copy

  33. Write-Ownership Cache Coherence owner, read-write Client A cache: X Client B cache: Client C cache: Client D cache:

  34. Write-Ownership Cache Coherence owner, read-write Client A cache: X Client B cache: Client C cache: Client D cache: read X

  35. X Write-Ownership Cache Coherence read-only Client A cache: X Client B cache: Client C cache: Client D cache: read X

  36. X Write-Ownership Cache Coherence read-only Client A cache: X Client B cache: Client C cache: X Client D cache: read-only

  37. Write-Ownership Cache Coherence read-only Client A cache: X Client B cache: Client C cache: X Client D cache: read-only write X

  38. Write-Ownership Cache Coherence Client A cache: Client B cache: Client C cache: X Client D cache: owner, read-write write X

  39. Other components • Software RAID • Stripe data redundantly over multiple disks • Distributed control • File system managers are spread across all machines

  40. xFS Summary • Built on small, unreliable components • Data, metadata, and control can live on any machine • If one machine goes down, everything else continues to work • When machines are added, xFS starts to use their resources

  41. xFS Summary - Complexity and associated performance degradation - Hard to upgrade software while keeping everything running

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