CS 4284 Systems Capstone
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1 CS 4284 Systems Capstone Disks & File Systems Godmar Back
2 Filesystems
3 Files vs Disks File Abstraction Byte oriented Names Access protection Consistency guarantees Disk Abstraction Block oriented Block #s No protection No guarantees beyond block write
4 Filesystem Requirements Naming Should be flexible, e.g., allow multiple names for same files Support hierarchy for easy of use Persistence Want to be sure data has been written to disk in case crash occurs Sharing/Protection Want to restrict who has access to files Want to share files with other users
5 FS Requirements (cont d) Speed & Efficiency for different access patterns Sequential access Random access Sequential is most common & Random next Other pattern is Keyed access (not usually provided by OS) Minimum Space Overhead Disk space needed to store metadata is lost for user data Twist: all metadata that is required to do translation must be stored on disk Translation scheme should minimize number of additional accesses for a given access pattern Harder than, say page tables where we assumed page tables themselves are not subject to paging!
6 Filesystems Software Architecture (including in-memory data structures)
7 Overview File Operations: create(), unlink(), open(), read(), write(), close() File System Buffer Cache Device Driver Uses names for files Views files as sequence of bytes Must implement translation (file name, file offset) (disk id, disk sector, sector offset) Must manage free space on disk Uses disk id + sector indices
8 Per-process file descriptor table PCB The Big Picture Data structures to keep track of open files struct file inode + position + struct dir inode + position struct inode Open file table? Buffer Cache Cached data and metadata in buffer cache File Data Directory Data File Descriptors (inodes) Filesystem Information On-Disk Data Structures
9 Steps in Opening & Reading a File Lookup (via directory) find on-disk file descriptor s block number Find entry in open file table (struct inode list in Pintos) Create one if none, else increment ref count Find where file data is located By reading on-disk file descriptor Read data & return to user
10 Open File Table inode represents file at most 1 in-memory instance per unique file #number of openers & other properties file represents one or more processes using an file With separate offsets for byte-stream dir represents an open directory file Generally: None of data in OFT is persistent Reflects how processes are currently using files Lifetime of objects determined by open/close Reference counting is used
11 File Descriptors ( inodes ) Term inode can refer to 3 things: 1. in-memory inode Store information about an open file, such as how many openers, corresponds to on-disk file descriptor 2. on-disk inode Region on disk, entry in file descriptor table, that stores persistent information about a file who owns it, where to find its data blocks, etc. 3. on-disk inode, when cached in buffer cache A bytewise copy of 2. in memory Q.: Should in-memory inode store a pointer to cached on-disk inode? (Answer: No.)
12 Filesystems On-Disk Data Structures and Allocation Strategies
13 Filesystem Information Contains superblock stores information such as size of entire filesystem, etc. Location of file descriptor table & free map Free Block Map Bitmap used to find free blocks Typically cached in memory Superblock & free map often replicated in different positions on disk Free Block Map Super Block
14 File Allocation Strategies Contiguous allocation Linked files Indexed files Multi-level indexed files
15 Contiguous Allocation File A File B Idea: allocate files in contiguous blocks File Descriptor = (first block, length) Good sequential & random access Problems: hard to extend files may require expensive compaction external fragmentation analogous to segmentation-based VM Pintos s baseline implementation does this
16 Linked Files File A Part 1 File B Part 1 File A Part 2 File B Part 2 Idea: implement linked list either with variable sized blocks or fixed sized blocks ( clusters ) Solves fragmentation problem, but now need lots of seeks for sequential accesses and random accesses unreliable: lose first block, may lose file Solution: keep linked list in memory DOS: FAT File Allocation Table
17 FAT stored at beginning of disk & replicated for redundancy FAT cached in memory Size: n-bit entries, m-bit blocks 2^(m+n) limit n=12, 16, 28 m=9 15 (0.5KB-32KB) As disk size grows, m & n must grow Growth of n means larger in-memory table Filename Length First Block a 2 1 b 4 3 c 3 12 d 1 4 DOS FAT
18 DOS FAT Scalability Limits FAT-12 uses 12 bit entries, max of 4096 clusters FAT-16: clusters, FAT-32 uses 28bits, so theoretical max of 2^28 (1 Gi) clusters Floppy disk, say 1.4MB; FAT-12, 1K clusters, need 1,400 entries, 2 bytes each -> 2.8KB Modern disk, say ~500 GB (~2^41 bytes) At 4 KB cluster size, would need 2^29 entries. Each entry at 4 bytes, would need 2^31 bytes, or 2GB, RAM just to hold the FAT. At 32 KB cluster size, would need only 1/8, but still 256MB RAM to hold FAT; simple operations, such as determining how much space is free on disk, require reading entire FAT
19 Blocksize Trade-Offs Chart above assumes all files are 2KB in size (observed median file size is about 2KB) Larger blocks: faster reads (because seeks are amortized & more bytes per transfer) More wastage (2KB file in 32KB block means 15/16 th are unused) Source: Tanenbaum, Modern Operating Systems
20 Indexed Allocation File A Index File A Part 1 File A Part 2 File A Part 3 Single-index: specify maximum filesize, create index array, then note blocks in index Random access ok one translation step Sequential access requires more seeks depending on contiguous allocation Drawback: hard to grow beyond maximum
21 Direct Blocks Indirect Block Double Indirect Block Triple Indirect Block N FLI SLI TLI Multi-Level Indices 1 2 N index index 2 index 3 index 2 N+1 Used in Unix & (possibly) Pintos (P4) index index index N+I N+I+1 N+I+I 2
22 Logical View (Per File) offset in file Inode Data Index Index Physical View (On Disk) (ignoring other files) sector numbers on disk
23 Logical View (Per File) offset in file Inode Data Index Index 2 Physical View (On Disk) (ignoring other files) sector numbers on disk
24 Multi-Level Indices If filesz < N * BLKSIZE, can store all information in direct block array Biased in favor of small files (ok because most files are small ) Assume index block stores I entries If filesz < (I + N) * BLKSIZE, 1 indirect block suffices Q.: What s the maximum size before we need triple-indirect block? Q.: What s the per-file overhead (best case, worst case?)
25 Extents Index-tree based scheme avoids external fragmentation, and is efficient for small files, but incurs relatively high meta-data overhead for large files Extents can improve that store (bnum, length) pair to denote that file occupies blocks [bnum,, bnum+length-1] But complicates offset -> sector translation Used in ext4.
26 Storing Inodes Unix v7, BSD 4.3 Superblock I 0 I 1 I 2 I 3 I 4.. Rest of disk for files & directories FFS (BSD 4.4) CG i SB1 I 0 I 1 Files SB2 I 3 I 4.. Files SB3 I 8 I 9.. Files Cylindergroups have superblock+bitmap+inode list+file space Try to allocate file & inode in same cylinder group to improve access locality
27 Positioning Inodes Putting inodes in fixed place makes finding inodes easier Can refer to them simply by inode number After crash, there is no ambiguity as to what are inodes vs. what are regular files Disadvantage: limits the number of files per filesystem at creation time Use df ih on Linux/ext3 to see how many inodes are used/free
28 Filesystems Directories and Name Resolution
29 Directories Need to find file descriptor (inode), given a name Approaches: Single directory (old PCs), Two-level approaches with 1 directory per user Now exclusively hierarchical approaches: File system forms a tree (or DAG) How to tell regular file from directory? Set a bit in the inode Data Structures Linear list of (inode, name) pairs B-Trees that map name -> inode Combinations thereof
30 inode # Using Linear Lists offset 0 23 multi-oom 15 sample.txt Advantage: (relatively) simple to implement Disadvantages: Scan makes lookup (& delete!) really slow for large directories Could cause fragmentation (though not a problem in practice)
31 Using B+-Trees Advantages: Scalable to large number of files: in growth, in lookup time Disadvantage: Complex Overhead for small directories (some filesystems switch to B+-Tree only for large directories) Note: some filesystems use B+-Tree not only for directory files, but for block indexes as well. HFS s catalog single B+-Tree that stores inodes + directories. Also done in NTFS, XFS & Reiserfs, ZFS, and Btrfs Source: Wikipedia)
32 Absolute Paths How to resolve a path name such as /usr/bin/ls? Split into tokens using / separator Find inode corresponding to root directory (how? Use fixed inode # for root) (*) Look up usr in root directory, find inode If not last component in path, check that inode is a directory. Go to (*), looking for next comp If last component in path, check inode is of desired type, return
33 Name Resolution Must have a way to scan an entire directory without other processes interfering -> need a lock function But don t need to hold lock on /usr when scanning /usr/bin Directories can only be removed if they re empty Requires synchronization also Most OS cache translations in namei cache maps absolute pathnames to inode Must keep namei cache consistent if files are deleted
34 Current Directory Relative pathnames are resolved relative to current directory Provides default context Every process has one in Unix/Pintos chdir(2) changes current directory cd tmp; ls; pwd vs (cd tmp; ls); pwd lookup algorithm the same, except starts from current dir process should keep current directory open current directory inherited from parent
35 Hard & Soft Links Provides aliases (different names) for a file Hard links: (Unix: ln) Two independent directory entries have the same inode number, refer to same file Inode contains a reference count Disadvantage: alias only possible with same filesystem Soft links: (Unix: ln s) Special type of file (noted in inode); content of file is absolute or relative pathname stored inside inode instead of direct block list Windows: junctions & shortcuts
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