Operating System Transaction Management

sangman kim michael z lee alan m dunn owen n.w
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Explore the challenges and solutions related to operating system transaction management, including fine-grained locking, system transactions, and middleware state sharing. Learn about TxOS and its improvements in system transactions for enhanced performance and reliability.

  • Transaction Management
  • Operating System
  • TxOS
  • Middleware
  • System Transactions

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  1. Sangman Kim, Michael Z. Lee, Alan M. Dunn, Owen S. Hofmann, XuanWang, Emmett Witchel, Donald E. Porter 1

  2. Fine-grained locking - Bug-prone, hard to maintain - OS provides poor support Parallelism Coarse-grained locking - Reduced resource utilization Maintainability 2

  3. Server Applications working with OS API Parallelism System Transaction Server Applications working with OS API Maintainability 3

  4. TxOS provides operating system transaction [Porter et al., SOSP2009] Transaction for OS objects (e.g., files, pipes) Middleware state sharing with multithreading System transaction in TxOS Application TxOS system calls Middleware state sharing JVM Linux TxOS TxOS 4

  5. TxOS provides operating system transaction [Porter et al., SOSP 2009] Transaction for OS objects (e.g., files , pipes) Synchronization in legacy code Application TxOS system calls Middleware state sharing JVM Synchronization primitives TxOS 5

  6. TxOS provides operating system transaction [Porter et al., SOSP 2009] Transaction for OS objects (e.g., files, pipes) TxOS+: Improved system transactions At most 40 application line changes Up to 88% throughput improvement Application TxOS system calls Middleware state sharing JVM Synchronization primitives TxOS+: pause/resume, commit ordering, and more TxOS TxOS+ 6

  7. Background: system transaction System transactions in action Challenges for rewriting applications Implementation and evaluation 7

  8. Transaction Interface and semantics System calls: xbegin(), xend(), xabort() ACID semantics Atomic all or nothing Consistent one consistent state to another Isolated updates as if only one concurrent transaction Durable committed transactions on disk Optimistic concurrency control Fix synchronization issues with OS APIs 8

  9. Lazy versioning: speculative copy for data inode i inum lock xbegin(); write(f, buf); xend(); inode header Conflict! Commit Abort size mode Copy of inode data inode data TxOS requires no special hardware 9

  10. Background: system transaction System transactions in action Challenges for rewriting applications Implementation and evaluation 10

  11. Parallelizing applications that synchronize on OS state Example 1: State-machine replication Constraint: Deterministic state update Example 2: IMAP Email Server Constraint: Consistent file system operations 11

  12. Core component of fault tolerant services e.g., Chubby, Zookeeper, Autopilot Replicas execute the same sequence of operations Often single-threaded to avoid non-determinism Ordered transaction Makes parallel OS state updates deterministic Applications determine commit order of transactions 12

  13. Everyone has concurrent email clients Desktop, laptop, tablets, phones, .... Need concurrent access to stored emails Brief history of email storage formats mbox: single file, file locking Lockless Maildir Dovecot Maildir: return of file locking 13

  14. mbox Single file mailbox of email messages ~/.mbox From MAILER-DAEMON Wed Apr 11 09:32:28 2012 From: Sangman Kim <sangmank@cs.utexas.edu> To: EuroSys 2012 audience Subject: mbox needs file lock. Maildir hides message. .. From MAILER-DAEMON Wed Apr 11 09:34:51 2012 From: Sangman Kim <sangmank@cs.utexas.edu> To: EuroSys 2012 audience Subject: System transactions good, file locks bad! . Synchronization with file-locking One of fcntl(), flock(), lock file (.mbox.lock) Very coarse-grained locking 14

  15. Maildir: Lockless alternative to mbox Directories of message files Each file contains a message Directory access with no synchronization (originally) Message filenames contain flags Maildir/cur 00000000.00201.host:2,T Trashed 00001000.00305.host:2,R Replied 00002000.02619.host:2,T Trashed Seen 00010000.08919.host:2,S Seen 00015000.10019.host:2,S 15

  16. PROCESS 1 (LISTING) PROCESS 2 (MARKING) while (f = readdir( Maildir/cur )): if (access( 043:2,S )): print f.name rename( 043:2,S , 043:2,R ) Maildir/cur directory 021:2,S 043:2,S 052:2,S 061:2,S 018:2,S Seen Seen Seen Seen Seen 16

  17. PROCESS 1 (LISTING) PROCESS 2 (MARKING) while (f = readdir( Maildir/cur )): if (access( 043:2,S )): print f.name rename( 043:2,S , 043:2,R ) Maildir/cur directory 021:2,S 043:2,S 052:2,S 061:2,S 018:2,S Seen 043:2,R Replied Seen Seen Seen Seen Process 1 Result 018:2,S 021:2,S 052:2,S 061:2,S Message missing! 17

  18. Maildir synchronization Lockless certain anomalous situations may result Courier IMAP manpage File locks Per-directory coarse-grained locking Complexity of Maildir, performance of mbox System transactions 18

  19. PROCESS 1 (MARKING) PROCESS 2 (MESSAGE LISTING) xbegin() xbegin() xbegin() xbegin() if (access( XXX:2,S )): while (f = readdir( Maildir/cur )): rename( XXX:2,S , print f.name xend() XXX:2,R )xend() xend() xend() Consistent directory accesses with better parallelism 19

  20. Background: system transaction System transactions in action Challenges for rewriting applications Implementation and evaluation 20

  21. 1. Middleware state sharing 2. Deterministic parallel update for system state 3. Composing with other synchronization primitives 21

  22. Problem with memory management Multiple threads share the same heap In Transaction Middleware (libc) Thread 1 Thread 2 Heap xbegin(); p1 = malloc(); p1 p2 = malloc(); xabort(); mmap() Kernel *p2 = 1; Transactional object for heap 22

  23. Problem with memory management Multiple threads share the same heap In Transaction Middleware (libc) Thread 1 Thread 2 Heap xbegin(); p1 = malloc(); p1 p2 unmapped p2 = malloc(); xabort(); Kernel *p2 = 1; FAULT! Transactional object for heap Certain middleware actions should not roll back 23

  24. USER-INITIATED ACTION MIDDLEWARE-INITIATED User changes system state Most file accesses Most synchronization System state changed as side effect of user action malloc() memory mapping Java garbage collection Dynamic linking Middleware state shared among user threads Can t just roll back! 24

  25. Transaction pause/resume Expose state changes by middleware-initiated actions to other threads Additional system calls xpause(), xresume() Limited complexity increase We used pause/resume 8 times in glibc, 4 times in JVM Only used in application for debugging 25

  26. Java code JVM Execution SysTransaction.begin(); xbegin(); files = dir.list(); files = dir.list(); xpause() VM operations (garbage collection) SysTransaction.end(); xresume() xend(); 26

  27. 17,000 lines of kernel changes Transactionalizing file descriptor table Handling page lock for disk I/O Memory protection Optimization with directory caching Reorganizing data structure and more Details in the paper 27

  28. Background: system transaction System transactions in action Challenges for rewriting applications Implementation and evaluation 28

  29. Implemented in UpRight BFT library Fault tolerant routing backend Graph stored in a file Compute shortest path Edge add/remove Ordered transactions for deterministic update 29

  30. Component Total LOC Changed LOC Routing application Upright Library 1,006 18 (1.8%) 22,767 174 (0.7%) JVM 496,305 384 (0.0008%) glibc 1,027,399 826 (0.0008%) 30

  31. 4000 TxOS, dense 3500 Linux,dense 3000 Work to add/delete edges small compared to scheduling overhead TxOS,sparse Throughput (req/s) 2500 Linux,sparse 2000 Dense graph: 88% tput 1500 1000 500 0 Sparse graph: 11% tput 0 10 20 30 40 50 60 70 80 90 100 Write ratio (%) BFT graph server 31

  32. Dovecot mail server Uses directory lock files for maildir accesses Locking is replaced with system transactions Changed LoC: 40 out of 138,723 Benchmark: Parallel IMAP clients Each client executes operations on a random message Read: message read Write: message creation/deletion 1500 messages total 32

  33. Dovecot benchmark with 4 clients 90 Tput Improvement (%) 80 70 60 50 Better block scheduling enhances write performance 40 30 20 10 0 0 10 25 50 100 Write ratio (%) 33

  34. System transactions parallelize tricky server applications Parallel Dovecot maildir operations Parallel BFT state update System transaction improves throughput with few application changes Up to 88% throughput improvement At most 40 changed lines of application code 34

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