SDC 2015 Santa Clara
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1 SDC 2015 Santa Clara Volker Lendecke Samba Team / SerNet
2 (2 / 17) SerNet Founded 1996 Offices in Göttingen and Berlin Topics: information security and data protection Specialized on Open Source Software Samba: Windows/Linux interoperability, clustering and private cloud SAMBA+: Samba for Enterprise Linux verinice.: Open Source ISMS Tool Firewalls and VPN solutions for mid-size and large corporations Old economy: no venture capital, no loans
3 (3 / 17) Overview General motivation for Samba s IPC Basic standard Posix IPC mechanisms Past Samba messaging implementation: tdb and signals Current mechanism: Unix Domain Datagram sockets Future developments
4 (4 / 17) Parallelism based on messages Wikipedia: An actor is a computational entity that, in response to a message it receives, can concurrently: send a finite number of messages to other actors; create a finite number of new actors; designate the behavior to be used for the next message it receives. There is no assumed sequence to the above actions and they could be carried out in parallel. Many languages embed message passing these days Erlang, Google go, Akka for JVM Some problems with threaded programming disappear with message-based parallelism Others of course get created :-)
5 (5 / 17) Why Inter *Process* Communication? Erlang, Go and others provide intra-os-process messages Threading based on OS threads plus VM threads All in one memory space Dependency on the virtual machine Distribution to processes possibly more reliable A crash in one OS process has less effect on others Better NUMA affinity Isolated memory maps Process architecture has helped Samba to go clustered Interoperability to other languages
6 (6 / 17) Samba architecture Traditional Unix architecture One listener process Every client gets its own worker process Helper Threads for asynchronous I/O Linux has no good general kernel-level aio Multi process single thread is vastly simpler than multi thread to us Samba has to communicate: The oplock break Process A needs to ask process B to release an oplock Architecture makes clustered SMB possible Multi-process enforces IPC discipline Going more async: Notifyd
7 (7 / 17)
8 (8 / 17) Unix Signals One of the oldest Unix IPC mechanism Asynchronous delivery Almost no information transferred Difficult to use together with threads If possible, receive signals in one thread only When used, not much can be done in a signal handler Posix lists only 135 functions as aync signal safe Watch out for EINTR result of most syscalls
9 (9 / 17) Shared Memory Same memory pages visible in multiple processes Blurs the distinction between threads and processes Fastest IPC mechanism No kernel involvement for data transfer Good for transferring mass data Limited use for message passing No good signalling mechanism Needs coordinated access Locks, Mutexes
10 (10 / 17) fcntl locks Advisory byte range locks Shared (F RDLCK) or exclusive (F WRLCK) locks Just an IPC mechanism: fcntl locks do not block read/write Weird semantics regarding duplicated file descriptors Closing any fd on a file loses locks on dup ed fds Very bad scaling fcntl locks maintained in a linked list Posix suggests deadlock detection locks are not per-file Linux has (had?) one big global spinlock for all fcntl lock operations Thundering herd when thousands of waiters are unblocked Automatic cleanup at process exit Lock waiters are not notified that a process crashed
11 (11 / 17) Process Shared Robust Mutexes pthread mutex t: pthread API to implement critical sections Originally intended for multiple threads within a single process Implementation under Linux with atomic operations No syscall in the non-contended case Waiting for a locked mutex uses a syscall PTHREAD PROCESS SHARED: Mutexes in shared memory Downside: If a mutex holder crashes, nobody can clean up PTHREAD MUTEX ROBUST: EOWNERDEAD When a mutex holder dies, a subsequent pthread mutex lock gets EOWNERDEAD Linux and Solaris only
12 (12 / 17) Samba Messaging Samba has a multi-writer key/value hash table: TDB Shared Memory Coordination via fcntl locks Where available: Process Shared Robust Mutexes Very fast for heavy concurrent small record updaters Messaging based on tdb: Every process has a record in a tdb as a mailbox Signalling via SIGUSR1 Simple, but bad under high load fcntl load brings system down With robust mutexes it is okay
13 (13 / 17) Unix Domain Datagram Sockets UDP on the local box Contrary to UDP, AF UNIX DGRAM sockets are reliable One socket per participating process Limited message size, sender must fragment FD passing possible via sendmsg() Asynchronous send into full queue: Poll with nonblocking send: High load by senders Blocking connected send scales well under Linux No thundering herd, contrary to thousands of writers into a pipe Well tuned for syslog via /dev/log Access to the socket dir can become a bottleneck
14 (14 / 17) Replace ctdb messaging All cluster communication goes through ctdbd Single Process, Single Threaded Only 1 CPU used for inter-node messaging Samba assumes reliable messaging Stream Socket, i.e. TCP between nodes TCP connection setup too expensive per message One proxy process per peer Open a normal Unix DGRAM socket Forward to another node Sender process decides which proxy to use
15 (15 / 17) Unix Domain Stream Sockets Datagram Sockets not overload-safe on FreeBSD ENOBUFS returned under overload Unlike Linux, FreeBSD can t do graceful blocking send Every message involves namespace operations Not truly scalable, requires a read lock on the socket directory File Descriptors are cheap epoll/kqueue designed to scale N M Stream Sockets between processes
16 (16 / 17) tmond How to pass stream socket fds? Every smbd listens on a stream socket connect() does not behave nicely under overload tmond provides a central hub Every messaging process connects() once Fresh stream to a peer: socketpair() and sendmsg() via tmond Process Monitoring via tmond Locks in user space: Wait for a process to go away, retry General replacement for ctdb watch us/ctdb unwatch
17 (17 / 17) Questions? vl@samba.org / vl@sernet.de
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Chapter 13: I/O Systems Chapter 13: I/O Systems I/O Hardware Application I/O Interface Kernel I/O Subsystem Transforming I/O Requests to Hardware Operations Streams Performance 13.2 Silberschatz, Galvin