1. File Systems Implementation

2. 2 Goals for Today Filesystem Implementation Structure for –Storing files –Directories –Managing free space –Shared files –Links –Consistency –Journaling –Performance Some Implementations –Log structured file system (LFS) –Distributed FS’s (NFS/AFS)

3. 3 File System Implementation How exactly are file systems implemented? Comes down to: how do we represent –Volumes –Directories (link file names to file “structure”) –The list of blocks containing the data –Other information such as access control list or permissions, owner, time of access, etc? And, can we be smart about layout?

4. 4 File Control Block FCB has all the information about the file –Linux systems call these i-node structures

5. 5 Implementing File Operations Create a file: –Find space in the file system, add directory entry. Open file –System call specifying name of file. –system searches directory structure to find file. –System keeps current file position pointer to the location where next write/read occurs –System call returns file descriptor (a handle) to user process Writing in a file: –System call specifying file descriptor and information to be written –Writes information at location pointed by the files current pointer Reading a file: –System call specifying file descriptor and number of bytes to read (and possibly where in memory to stick contents).

6. 6 Implementing File Operations Repositioning within a file: –System call specifying file descriptor and new location of current pointer –(also called a file seek even though does not interact with disk) Closing a file: –System call specifying file descriptor –Call removes current file position pointer and file descriptor associated with process and file Deleting a file: –Search directory structure for named file, release associated file space and erase directory entry Truncating a file: –Keep attributes the same, but reset file size to 0, and reclaim file space.

7. 7 Other file operations Most FS require an open() system call before using a file. OS keeps an in-memory table of open files, so when a reading or writing is requested, they refer to entries in this table via a file descriptor. On finishing with a file, a close() system call is necessary. (creating & deleting files typically works on closed files) What happens when multiple files can open the file at the same time?

8. 8 Multiple users of a file OS typically keeps two levels of internal tables: Per-process table –Information about the use of the file by the user (e.g. current file position pointer) System wide table –Gets created by first process which opens the file –Location of file on disk –Access dates –File size –Count of how many processes have the file open (used for deletion)

9. 9 Files Open and Read

10. 10 Virtual File Systems Virtual File Systems (VFS) provide an object-oriented way of implementing file systems. VFS allows the same system call interface (the API) to be used for different types of file systems. The API is to the VFS interface, rather than any specific type of file system.

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12. 12 File System Layout File System is stored on disks –Disk is divided into 1 or more partitions –Sector 0 of disk called Master Boot Record –End of MBR has partition table (start & end address of partitions) First block of each partition has boot block –Loaded by MBR and executed on boot

13. 13 Storing Files Files can be allocated in different ways: Contiguous allocation –All bytes together, in order Linked Structure –Each block points to the next block Indexed Structure –An index block contains pointer to many other blocks Rhetorical Questions -- which is best? –For sequential access? Random access? –Large files? Small files? Mixed?

14. 14 Implementing Files Contiguous Allocation: allocate files contiguously on disk

15. 15 Contiguous Allocation Pros: –Simple: state required per file is start block and size –Performance: entire file can be read with one seek Cons: –Fragmentation: external is bigger problem –Usability: user needs to know size of file Used in CDROMs, DVDs

16. 16 Linked List Allocation Each file is stored as linked list of blocks –First word of each block points to next block –Rest of disk block is file data

17. 17 Linked List Allocation Pros: –No space lost to external fragmentation –Disk only needs to maintain first block of each file Cons: –Random access is costly –Overheads of pointers

18. 18 MS-DOS File System Implement a linked list allocation using a table –Called File Allocation Table (FAT) –Take pointer away from blocks, store in this table –Can cache FAT in-memory

19. 19 FAT Discussion Pros: –Entire block is available for data –Random access is faster since entire FAT is in memory Cons: –Entire FAT should be in memory For 20 GB disk, 1 KB block size, FAT has 20 million entries If 4 bytes used per entry  80 MB of main memory required for FS

20. 20 Indexed Allocation Index block contains pointers to each data block Pros? –Space (max open files * size per I-node) Cons? –what if file expands beyond I-node address space?

21. 21 UFS - Unix File System

22. 22 Unix inodes If data blocks are 4K … –First 48K reachable from the inode –Next 4MB available from single-indirect –Next 4GB available from double-indirect –Next 4TB available through the triple-indirect block Any block can be found with at most 3 disk accesses

23. 23 Implementing Directories When a file is opened, OS uses path name to find dir –Directory has information about the file’s disk blocks Whole file (contiguous), first block (linked-list) or I-node –Directory also has attributes of each file Directory: map ASCII file name to file attributes & location 2 options: entries have all attributes, or point to file I-node

24. 24 Implementing Directories What if files have large, variable-length names? Solution: –Limit file name length, say 255 chars, and use previous scheme Pros: Simple Cons: wastes space –Directory entry comprises fixed and variable portion Fixed part starts with entry size, followed by attributes Variable part has the file name Pros: saves space Cons: holes on removal, page fault on file read, word boundaries –Directory entries are fixed in length, pointer to file name in heap Pros: easy removal, no space wasted for word boundaries Cons: manage heap, page faults on file names

25. 25 Managing file names: Example

26. 26 Directory Search Simple Linear search can be slow Alternatives: –Use a per-directory hash table Could use hash of file name to store entry for file Pros: faster lookup Cons: More complex management –Caching: cache the most recent searches Look in cache before searching FS

27. 27 Shared Files If B wants to share a file owned by C –One Solution: copy disk addresses in B’s directory entry –Problem: modification by one not reflected in other user’s view

28. 28 Sharing Files: Solutions 2 approaches: –Use i-nodes to store file information in directories (hard link) Cons: –What happens if owner deletes file? –Symbolic links: B links to C’s file by creating a file in its directory The new Link file contains path name of file being linked Cons: read overhead

29. 29 Hard vs Soft Links File nameInode# Inode Foo.txt2433 Hard.lnk2433 Inode #2433

30. 30 Hard vs Soft Links Foo.txt2433 Soft.lnk43234 Inode #2433 Inode #43234 /path/to/Foo.txt..and then redirects to Inode #2433 at open() time..

31. 31 Managing Free Disk Space 2 approaches to keep track of free disk blocks –Linked list and bitmap approach

32. 32 Tracking free space Storing free blocks in a Linked List –Only one block need to be kept in memory –Bad scenario: Solution (c) Storing bitmaps –Lesser storage in most cases –Allocated disk blocks are closer to each other

33. 33 Disk Space Management Files stored as fixed-size blocks What is a good block size? (sector, track, cylinder?) –If 131,072 bytes/track, rotation time 8.33 ms, seek time 10 ms –To read k bytes block: 10+ 4.165 + (k/131072)*8.33 ms –Median file size: 2 KB Block size

34. 34 Managing Disk Quotas Sys admin gives each user max space –Open file table has entry to Quota table –Soft limit violations result in warnings –Hard limit violations result in errors –Check limits on login

35. 35 Efficiency and Performance Efficiency dependent on: –disk allocation and directory algorithms –types of data kept in file’s directory entry Performance –disk cache – separate section of main memory for frequently used blocks –free-behind and read-ahead – techniques to optimize sequential access –improve PC performance by dedicating section of memory as virtual disk, or RAM disk

36. 36 File System Consistency System crash before modified files written back –Leads to inconsistency in FS –fsck (UNIX) & scandisk (Windows) check FS consistency Algorithm: –Build 2 tables, each containing counter for all blocks (init to 0) 1 st table checks how many times a block is in a file 2 nd table records how often block is present in the free list –>1 not possible if using a bitmap –Read all i-nodes, and modify table 1 –Read free-list and modify table 2 –Consistent state if block is either in table 1 or 2, but not both

37. 37 A changing problem Consistency used to be very hard –Problem was that driver implemented C-SCAN and this could reorder operations –For example Delete file X in inode Y containing blocks A, B, C Now create file Z re-using inode Y and block C –Problem is that if I/O is out of order and a crash occurs we could see a scramble E.g. C in both X and Z… or directory entry for X is still there but points to inode now in use for file Z

38. 38 Inconsistent FS examples (a)Consistent (b)missing block 2: add it to free list (c)Duplicate block 4 in free list: rebuild free list (d)Duplicate block 5 in data list: copy block and add it to one file

39. 39 Check Directory System Use a per-file table instead of per-block Parse entire directory structure, starting at the root –Increment the counter for each file you encounter –This value can be >1 due to hard links –Symbolic links are ignored Compare counts in table with link counts in the i-node –If i-node count > our directory count (wastes space) –If i-node count < our directory count (catastrophic)

40. 40 Log Structured File Systems Log structured (or journaling) file systems record each update to the file system as a transaction All transactions are written to a log – A transaction is considered committed once it is written to the log –However, the file system may not yet be updated

41. 41 Log Structured File Systems The transactions synchronously written to the log are subsequently asynchronously written to the file system – When the file system is modified, the transaction is removed from the log If the file system crashes, all remaining transactions in the log must still be performed E.g. ReiserFS, XFS, NTFS, etc..

42. 42 FS Performance Access to disk is much slower than access to memory –Optimizations needed to get best performance 3 possible approaches: caching, prefetching, disk layout Block or buffer cache: –Read/write from and to the cache.

43. 43 Block Cache Replacement Which cache block to replace? –Could use any page replacement algorithm –Possible to implement perfect LRU Since much lesser frequency of cache access Move block to front of queue –Perfect LRU is undesirable. We should also answer: Is the block essential to consistency of system? Will this block be needed again soon? When to write back other blocks? –Update daemon in UNIX calls sync system call every 30 s –MS-DOS uses write-through caches

44. 44 Other Approaches Pre-fetching or Block Read Ahead –Get a block in cache before it is needed (e.g. next file block) –Need to keep track if access is sequential or random Reducing disk arm motion –Put blocks likely to be accessed together in same cylinder Easy with bitmap, possible with over-provisioning in free lists –Modify i-node placements

45. Other File Systems: LFS, NFS, and AFS

46. 46 Announcements Homework due today Pick up prelim from homework center Prelim II will be Thursday, November 20th

47. 47 Goals for Today Discuss specific file systems –both local and remote Log-structured file system (LFS) Distributed file systems (DFS) –Network file system (NFS) –Andrew file system (AFS)

48. 48 Log-Structured File Systems The trend: CPUs are faster, RAM & caches are bigger –So, a lot of reads do not require disk access –Most disk accesses are writes  pre-fetching not very useful –Worse, most writes are small  10 ms overhead for 50 µs write –Example: to create a new file: i-node of directory needs to be written Directory block needs to be written i-node for the file has to be written Need to write the file –Delaying these writes could hamper consistency Solution: LFS to utilize full disk bandwidth

49. 49 LFS Basic Idea Structure the disk a log –Periodically, all pending writes buffered in memory are collected in a single segment –The entire segment is written contiguously at end of the log Segment may contain i-nodes, directory entries, data –Start of each segment has a summary –If segment around 1 MB, then full disk bandwidth can be utilized Note, i-nodes are now scattered on disk –Maintain i-node map (entry i points to i-node i on disk) –Part of it is cached, reducing the delay in accessing i-node This description works great for disks of infinite size

50. 50 LFS vs. UFS file1 file2 dir1dir2 Unix File System file1file2 dir1 dir2 Log-Structured File System Log inode directory data inode map Blocks written to create two 1-block files: dir1/file1 and dir2/file2, in UFS and LFS

51. 51 LFS Cleaning Finite disk space implies that the disk is eventually full –Fortunately, some segments have stale information –A file overwrite causes i-node to point to new blocks Old ones still occupy space Solution: LFS Cleaner thread compacts the log –Read segment summary, and see if contents are current File blocks, i-nodes, etc. –If not, the segment is marked free, and cleaner moves forward –Else, cleaner writes content into new segment at end of the log –The segment is marked as free! Disk is a circular buffer, writer adds contents to the front, cleaner cleans content from the back

52. 52 Distributed File Systems Goal: view a distributed system as a file system –Storage is distributed –Web tries to make world a collection of hyperlinked documents Issues not common to usual file systems –Naming transparency –Load balancing –Scalability –Location and network transparency –Fault tolerance We will look at some of these today

53. 53 Transfer Model Upload/download Model: –Client downloads file, works on it, and writes it back on server –Simple and good performance Remote Access Model: –File only on server; client sends commands to get work done

54. 54 Naming transparency Naming is a mapping from logical to physical objects Ideally client interface should be transparent –Not distinguish between remote and local files –/machine/path or mounting remote FS in local hierarchy are not transparent A transparent DFS hides the location of files in system 2 forms of transparency: –Location transparency: path gives no hint of file location /server1/dir1/dir2/x tells x is on server1, but not where server1 is –Location independence: move files without changing names Separate naming hierarchy from storage devices hierarchy

55. 55 File Sharing Semantics Sequential consistency: reads see previous writes –Ordering on all system calls seen by all processors –Maintained in single processor systems –Can be achieved in DFS with one file server and no caching

56. 56 Caching Keep repeatedly accessed blocks in cache –Improves performance of further accesses How it works: –If needed block not in cache, it is fetched and cached –Accesses performed on local copy –One master file copy on server, other copies distributed in DFS –Cache consistency problem: how to keep cached copy consistent with master file copy Where to cache? –Disk: Pros: more reliable, data present locally on recovery –Memory: Pros: diskless workstations, quicker data access, –Servers maintain cache in memory

57. 57 File Sharing Semantics Other approaches: –Write through caches: immediately propagate changes in cache files to server Reliable but poor performance –Delayed write: Writes are not propagated immediately, probably on file close Session semantics (AFS): write file back on close Alternative (NFS): scan cache periodically and flush modified blocks Better performance but poor reliability –File Locking: The upload/download model locks a downloaded file Other processes wait for file lock to be released

58. 58 Network File System (NFS) Developed by Sun Microsystems in 1984 –Used to join FSes on multiple computers as one logical whole Used commonly today with UNIX systems Assumptions –Allows arbitrary collection of users to share a file system –Clients and servers might be on different LANs –Machines can be clients and servers at the same time Architecture: –A server exports one or more of its directories to remote clients –Clients access exported directories by mounting them The contents are then accessed as if they were local

59. 59 Example

60. 60 NFS Mount Protocol Client sends path name to server with request to mount –Not required to specify where to mount If path is legal and exported, server returns file handle –Contains FS type, disk, i-node number of directory, security info –Subsequent accesses from client use file handle Mount can be either at boot or automount –Using automount, directories are not mounted during boot –OS sends a message to servers on first remote file access –Automount is helpful since remote dir might not be used at all Mount only affects the client view!

61. 61 NFS Protocol Supports directory and file access via remote procedure calls (RPCs) All UNIX system calls supported other than open & close Open and close are intentionally not supported –For a read, client sends lookup message to server –Server looks up file and returns handle –Unlike open, lookup does not copy info in internal system tables –Subsequently, read contains file handle, offset and num bytes –Each message is self-contained Pros: server is stateless, i.e. no state about open files Cons: Locking is difficult, no concurrency control

62. 62 NFS Implementation Three main layers: System call layer: –Handles calls like open, read and close Virtual File System Layer: –Maintains table with one entry (v-node) for each open file –v-nodes indicate if file is local or remote If remote it has enough info to access them For local files, FS and i-node are recorded NFS Service Layer: –This lowest layer implements the NFS protocol

63. 63 NFS Layer Structure

64. 64 How NFS works? Mount: –Sys ad calls mount program with remote dir, local dir –Mount program parses for name of NFS server –Contacts server asking for file handle for remote dir –If directory exists for remote mounting, server returns handle –Client kernel constructs v-node for remote dir –Asks NFS client code to construct r-node for file handle Open: –Kernel realizes that file is on remotely mounted directory –Finds r-node in v-node for the directory –NFS client code then opens file, enters r-node for file in VFS, and returns file descriptor for remote node

65. 65 Cache coherency Clients cache file attributes and data –If two clients cache the same data, cache coherency is lost Solutions: –Each cache block has a timer (3 sec for data, 30 sec for dir) Entry is discarded when timer expires –On open of cached file, its last modify time on server is checked If cached copy is old, it is discarded –Every 30 sec, cache time expires All dirty blocks are written back to the server

66. 66 Andrew File System (AFS) Named after Andrew Carnegie and Andrew Mellon –Transarc Corp. and then IBM took development of AFS –In 2000 IBM made OpenAFS available as open source Features: –Uniform name space –Location independent file sharing –Client side caching with cache consistency –Secure authentication via Kerberos –Server-side caching in form of replicas –High availability through automatic switchover of replicas –Scalability to span 5000 workstations

67. 67 AFS Overview Based on the upload/download model –Clients download and cache files –Server keeps track of clients that cache the file –Clients upload files at end of session Whole file caching is central idea behind AFS –Later amended to block operations –Simple, effective AFS servers are stateful –Keep track of clients that have cached files –Recall files that have been modified

68. 68 AFS Details Has dedicated server machines Clients have partitioned name space: –Local name space and shared name space –Cluster of dedicated servers (Vice) present shared name space –Clients run Virtue protocol to communicate with Vice Clients and servers are grouped into clusters –Clusters connected through the WAN Other issues: –Scalability, client mobility, security, protection, heterogeneity

69. 69 AFS: Shared Name Space AFS’s storage is arranged in volumes –Usually associated with files of a particular client AFS dir entry maps vice files/dirs to a 96-bit fid –Volume number –Vnode number: index into i-node array of a volume –Uniquifier: allows reuse of vnode numbers Fids are location transparent –File movements do not invalidate fids Location information kept in volume-location database –Volumes migrated to balance available disk space, utilization –Volume movement is atomic; operation aborted on server crash

70. 70 AFS: Operations and Consistency AFS caches entire files from servers –Client interacts with servers only during open and close OS on client intercepts calls, and passes it to Venus –Venus is a client process that caches files from servers –Venus contacts Vice only on open and close Does not contact if file is already in the cache, and not invalidated –Reads and writes bypass Venus Works due to callback: –Server updates state to record caching –Server notifies client before allowing another client to modify –Clients lose their callback when someone writes the file Venus caches dirs and symbolic links for path translation

71. 71 AFS Implementation Client cache is a local directory on UNIX FS –Venus and server processes access file directly by UNIX i-node Venus has 2 caches, one for status & one for data –Uses LRU to keep them bounded in size

72. 72 Summary LFS: –Local file system –Optimize writes NFS: –Simple distributed file system protocol. No open/close –Stateless server Has problems with cache consistency, locking protocol AFS: –More complicated distributed file system protocol –Stateful server session semantics: consistency on close