More on File Systems

More on FilesCS-4513, D-Term 2007 1

More on File Systems

CS-4513Distributed Computing Systems

(Slides include materials from Operating System Concepts, 7th ed., by Silbershatz, Galvin, & Gagne, Modern Operating Systems, 2nd ed., by Tanenbaum, and Distributed Systems: Principles & Paradigms, 2nd

ed. By Tanenbaum and Van Steen)


Mapping files to Virtual Memory

• Instead of “reading” from disk into virtual memory, why not simply use file as the swapping storage for certain VM pages?

• Called mapping

• Page tables in kernel point to disk blocks of the file


Memory-Mapped Files

• Memory-mapped file I/O allows file I/O to be treated as routine memory access by mapping a disk block to a page in memory

• A file is initially “read” using demand paging. A page-sized portion of the file is read from the file system into a physical page. Subsequent reads/writes to/from the file are treated as ordinary memory accesses.

• Simplifies file access by allowing application to simple access memory rather than be forced to use read() & write() calls to file system.


Memory-Mapped Files (continued)

• A tantalizingly attractive notion, but …

• Cannot use C/C++ pointers within mapped data structure

• Corrupted data structures likely to persist in file• Recovery after a crash is more difficult

• Don’t really save anything in terms of• Programming energy

• Thought processes

• Storage space & efficiency


Memory-Mapped Files (continued)

Nevertheless, the idea has its uses1. Simpler implementation of file operations

– read(), write() are memory-to-memory operations

– seek() is simply changing a pointer, etc…

– Called memory-mapped I/O

2. Shared Virtual Memory among processes


Shared Virtual Memory


Shared Virtual Memory (continued)

• Supported in – Windows XP– Apollo DOMAIN– Linux??

• Synchronization is the responsibility of the sharing applications– OS retains no knowledge– Few (if any) synchronization primitives

between processes in separate address spaces


Questions?


Problem

• Question:–– If mean time to failure of a disk drive is 100,000 hours,– and if your system has 100 identical disks,– what is mean time between drive replacement?

• Answer:–– 1000 hours (i.e., 41.67 days 6 weeks)

• I.e.:–– You lose 1% of your data every 6 weeks!

• But don’t worry – you can restore most of it from backup!


Can we do better?

• Yes, mirrored– Write every block twice, on two separate disks– Mean time between simultaneous failure of

both disks is >57,000 years

• Can we do even better?– E.g., use fewer extra disks?– E.g., get more performance?


RAID – Redundant Array of Inexpensive Disks

• Distribute a file system intelligently across multiple disks to– Maintain high reliability and availability– Enable fast recovery from failure– Increase performance


“Levels” of RAID

• Level 0 – non-redundant striping of blocks across disk

• Level 1 – simple mirroring

• Level 2 – striping of bytes or bits with ECC

• Level 3 – Level 2 with parity, not ECC

• Level 4 – Level 0 with parity block

• Level 5 – Level 4 with distributed parity blocks


RAID Level 0 – Simple Striping

• Each stripe is one or a group of contiguous blocks

• Block/group i is on disk (i mod n)

• Advantage– Read/write n blocks in parallel; n times bandwidth

• Disadvantage– No redundancy at all. System MBTF is 1/n disk MBTF!

stripe 8stripe 4stripe 0





RAID Level 1– Striping and Mirroring

• Each stripe is written twice• Two separate, identical disks

• Block/group i is on disks (i mod 2n) & (i+n mod 2n)• Advantages

– Read/write n blocks in parallel; n times bandwidth– Redundancy: System MBTF = (Disk MBTF)2 at twice the cost– Failed disk can be replaced by copying

• Disadvantage– A lot of extra disks for much more reliability than we need










RAID Levels 2 & 3

• Bit- or byte-level striping

• Requires synchronized disks• Highly impractical

• Requires fancy electronics • For ECC calculations

• Not used; academic interest only

• See Silbershatz, §12.7.3 (pp. 471-472)


Observation

• When a disk or stripe is read incorrectly,

we know which one failed!

• Conclusion:– A simple parity disk can provide very high

reliability• (unlike simple parity in memory)


RAID Level 4 – Parity Disk

• parity 0-3 = stripe 0 xor stripe 1 xor stripe 2 xor stripe 3• n stripes plus parity are written/read in parallel• If any disk/stripe fails, it can be reconstructed from others

– E.g., stripe 1 = stripe 0 xor stripe 2 xor stripe 3 xor parity 0-3

• Advantages– n times read bandwidth– System MBTF = (Disk MBTF)2 at 1/n additional cost– Failed disk can be reconstructed “on-the-fly” (hot swap)– Hot expansion: simply add n + 1 disks all initialized to zeros

• However– Writing requires read-modify-write of parity stripe only 1x write

bandwidth.





parity 8-11parity 4-7parity 0-3


RAID Level 5 – Distributed Parity

• Parity calculation is same as RAID Level 4• Advantages & Disadvantages – Mostly same as RAID Level 4• Additional advantages

– avoids beating up on parity disk– Some writes in parallel (if no contention for parity drive)

• Writing individual stripes (RAID 4 & 5)– Read existing stripe and existing parity– Recompute parity– Write new stripe and new parity

stripe 12stripe 8stripe 4stripe 0

parity 12-15stripe 9stripe 5stripe 1

stripe 13parity 8-11stripe 6stripe 2

stripe 14stripe 10parity 4-7stripe 3

stripe 15stripe 11stripe 7parity 0-3


RAID 4 & 5

• Very popular in data centers– Corporate and academic servers

• Built-in support in Windows XP and Linux– Connect a group of disks to fast SCSI port (320

MB/sec bandwidth)– OS RAID support does the rest!

• Other RAID variations also available


New Topic


Incomplete Operations

• Problem – how to protect against disk write operations that don’t finish– Power or CPU failure in the middle of a block– Related series of writes interrupted before all

are completed

• Examples:– Database update of charge and credit– RAID 1, 4, 5 failure between redundant writes


Solution (part 1) – Stable Storage

• Write everything twice to separate disks• Be sure 1st write does not invalidate previous 2nd copy

• RAID 1 is okay; RAID 4/5 not okay!

• Read blocks back to validate; then report completion

• Reading both copies• If 1st copy okay, use it – i.e., newest value

• If 2nd copy different or bad, update it with 1st copy

• If 1st copy is bad; update it with 2nd copy – i.e., old value


Stable Storage (continued)

• Crash recovery• Scan disks, compare corresponding blocks• If one is bad, replace with good one• If both good but different, replace 2nd with 1st copy

• Result:–• If 1st block is good, it contains latest value• If not, 2nd block still contains previous value

• An abstraction of an atomic disk write of a single block

• Uninterruptible by power failure, etc.


What about more complex disk operations?

• E.g., File create operation involves• Allocating free blocks

• Constructing and writing i-node– Possibly multiple i-node blocks

• Reading and updating directory

• Update Free list and store back onto disk

• What if system crashes with the sequence only partly completed?

• Answer: inconsistent data structures on disk


Solution (Part 2) –Log-Structured File System

• Make changes to cached copies in memory• Collect together all changed blocks

• Including i-nodes and directory blocks

• Write to log file (aka journal file)• A circular buffer on disk• Fast, contiguous write

• Update log file pointer in stable storage

• Offline: Play back log file to actually update directories, i-nodes, free list, etc.

• Update playback pointer in stable storage


Transaction Data Base Systems

• Similar techniques– Every transaction is recorded in log before

recording on disk– Stable storage techniques for managing log

pointers– One log exist is confirmed, disk can be updated

in place– After crash, replay log to redo disk operations


Journaling File Systems

• Linux ext3 file system

• Windows NTFS


Berkeley LFS — a slight variation

• Everything is written to log• i-nodes point to updated blocks in log• i-node cache in memory updated whenever i-node is written• Cleaner daemon follows behind to compact log

• Advantages:– LFS is always consistent– LFS performance

• Much better than Unix file system for small writes• At least as good for reads and large writes

• Tanenbaum, §6.3.8, pp. 428-430• Rosenblum & Ousterhout, Log-structured File System (pdf

)

• Note: not same as Linux LFS (large file system)


Example

i-node

modified blocksa

b c

Before

old i-node

old blocksa

b c

loga b c

new blocks

new i-node

After


Questions?

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