I have a huge application that needs to fork itself at some point. The application is multithreaded and has about 200MB of allocated memory. What I want to do now to ensure that the data allocated by the process wont get duplicated is to start a new thread and fork inside of this thread. From what I have read, only the thread that calls fork will be duplicated, but what will happen to the allocated memory? Will that still be there? The purpose of this is to restart the application with other startup parameters, when its forked, it will call main with my new parameters, thus getting hopefully a new process of the same program. Now before you ask: I cannot assure that the binary of that process will still be in the same place as when I started the process, otherwise I could just fork and exec whats in /proc/self/exe.
Threads are execution units inside the big bag of resources that a process is. A process is the whole thing that you can access from any thread in the process: all the threads, all the file descriptors, all the other resources. So memory is absolutely not tied to a thread, and forking from a thread has no useful effect. Everything still needs to be copied over since the point of forking is creating a new process.
That said, Linux has some tricks to make it faster. Copying 2 gigabytes worth of RAM is neither fast or efficient. So when you fork, Linux actually gives the new process the same memory (at first), but it uses the virtual memory system to mark it as copy-on-write: as soon as one process needs to write to that memory, the kernel intercepts it and allocates distinct memory so that the other process isn't affected.
Let me begin by saying I do not have in depth knowledge of Perl so please pardon me if there is something obvious that I have missed :)
In the system (running in Windows environment) that I am looking at, we have a perl process which has to download ~5000-6000 files. Since each file can be independently downloaded, we forked separate threads for each file. The thread is supposed to download the file and die. On running the process, I noticed that the memory of the process goes up to ~1.7 GB and then dies due to the memory limit of each process.
On searching and asking a few people, I came across this concept of circular referencing due to which the garbage collector will not free up memory. I searched a bit and found the Devel-Cycle package which can find out if there are any cycles in the object. I got this package and added a line to check if the main object in the process has any cycles. find_cycle came back with the following statement for each thread.
DBD::Oracle::db FIRSTKEY failed: handle 2 is owned by thread 256004 not current thread c0ea29c (handles can't be shared between threads and your driver may need a CLONE method added) at C:/Program Files/Perl/site/lib/Devel/Cycle.pm line 151.
I got to know that DB handles cannot be shared between threads. I looked at the code again and realised that after the fork happens, the child process does actually create a new DB handle (which I guess is why the process still continues to run fine till it reaches the memory limit). I guess there might be more db handles from the parent in the object that are not used by the child but are still referenced.
Questons that I have -
Is the circular reference the only reason for the problem or could there be other issues causing the process to use so much memory?
Could the sharing of the handle cause the blow up in memory (in other words is the shared DB handle causing the GC to not free up space)?
If it is indeed the shared DB handle, I guess I can just say $dbHandle = 0 to get rid of the reference (if $dbHabndle is referencing that particular handle). Am I correct here?
I am trying to go through the code to see where else there is a reference to the parent DB handle (and found at least one more reference). Is there any other way I can do this? Is there a method to print out all the properties of an object?
EDIT:
Not all threads (due to the perl fork call in windows) are spawned at the same time. It spawns a max of n number of threads (where n is a configurable number). Once a thread has finished its execution, the process spawns another thread. At this moment n is set to 10, however I had changed n to 1 (so only one extra thread is running at one time), and I still hit the memory limit.
edit: Turns out, this does not solve the Ops problem. Still might be helpful for a future reader.
We do not really know a lot about your situation and your program sounds quite complex to just fork it 6000 times to me. But i will still attempt to answer, please correct me if my assumptions are wrong.
It appears you are on Windows. It is important to note, that Windows has no fork() system call. And as you specifically note that you "fork", i just assume that you actually use that Perl command. On windows, this will try to emulate fork() as best as it can but what that basically means is, that all the forked processes you see, are in fact just threads within the original process, just pretending to be processes to you. To do this, they copy the complete interpreter state. See http://perldoc.perl.org/perlfork.html for more information. Especially the following part seems to apply to you:
Resource limits
In the eyes of the operating system, pseudo-processes created via the fork() emulation are simply threads in the same process. This means that any process-level limits imposed by the operating system apply to all pseudo-processes taken together. This includes any limits imposed by the operating system on the number of open file, directory and socket handles, limits on disk space usage, limits on memory size, limits on CPU utilization etc.
If you fork so many pseudo processes, you need a lot of memory as you also have to copy the interpreter state as often. And depending on the complexity of your program and how it is structured, that may very well be a non-trivial amount of memory.
And as http://msdn.microsoft.com/en-us/library/windows/desktop/aa366778%28v=vs.85%29.aspx tells us, the 1.7GB you mentioned, is not far away from the 2GB that some Windows versions impose on you as memory limit for a single process.
My wild guess would be, that you in fact just hit that limit by spawning all those many many threads, each with its own copy of the interpreter state and everything.
You will probably be off a lot better using some threading library instead of asking Perl to emulate individual processes for you. Needless to mention (i hope) that you do not really gain any advantage by having 6000 threads over lets say 16. If you try to have all of them do something at the same time, you will in fact most likely experience slowdowns, depending on how the threading is handled.
In addition to the comments already provided, I want to emphasize the point DeVadder made regarding the behavior of fork in Windows and that Perl threading is likely a better solution but are you sure that the DBD module is safe to be used by multiple processes / forks / threads, etc without setting some extra parameters?
I had a similar error when using the DBI module to access a SQLite DB in multi-processed code using the threads module. It was solved by setting the 'use_immediate_transaction' option for the database handle provided by DBI to 1. If you aren't familiar with how Perl threads work, they aren't threads, they create a copy of the interpreter and everything you have in memory at the time of their creation, but even if I made the database handle separately in each "thread" I would get 'database locked' and various other errors. Without some of these extra options DBD may not function correctly in a multiprocessed environment.
Also, why make 6000 forks, use thread::queue and the threads module, make a worker pool of a few workers (one per core?) and recycle the workers. You are doing alot of overhead every fork for no gain.
I'm writing a mono-thread memory heavy proof of concept application.
This application doesn't manipulate much data per se, will mainly load GBs of data and then do some data analysis on it.
I don't want to manage concurrency via MT implementation, don't want to have to implement locks (i.e. mutexes, spinlocks, ...) so I've decided this time around to use the dear old fork().
On Linux, where memory is CoW, I should be able to efficiently analyse same datasets without having to copy them explicitly and with simple parallel mono-thread logic (again, this is a proof of concept).
Now that I spawn child processes, with fork() is very easy to setup input parameters for a sub-task (sub-process in this case), but then I have to get back the results to the main process. And sometimes these results are 10s of GB large. All the IPC mechanisms I have in mind are:
PIPEs/Sockets (and then epoll equivalent to wait for results in a mono-thread fashion)
Hybrid PIPEs/Shared Memory (epoll equivalent to wait for results with reference to Shared Memory, then copy data from Shared Memory into parent process, destroy Shared Memory)
What else could I use? Apart the obvious "go multi-thread", I really would like to leverage the CoW and single-thread multi-process architecture for this proof of concept. Any ideas?
Thanks
After some experimenting the conclusion I got to is the following:
When a child process has to communicate with parent, before spawning such child process I create a segment of shared memory (i.e. 16 MB)
if coordination is needed a semaphore is created in sh mem segment
Then upon forking, I pipe2 with nonblocking sockets so child can notify parent when some data is available
The pipe fd is then used into epoll
epoll is used as Level Triggered so I can interleave requests if the child processes are really fast in sending data
The segment of shared memory is used to communicate data directly if the structures are pod or with simple template<...> binary read/write functions if those are not
I believe this is a good solution.
Cheers
You could also use a regular file.
Parent process could wait for the child process (to analyse the data on memory and then write to file its result and) to exit and once it does, you must be able to read data from the file. As you mentioned, input parameter is not a problem, you could just specify the file name to write to in one of the input parameters. This way, there is no locking required or except for wait() on exit status of child process.
I wonder if each of your child processes return 10s of GB large data, this way it is much better to use regular files, as you will have enough time to process each of the child process's result. But is this 10GBs data shared across child processes? If that was the case, you would have preferred to use locks, so I assume it isn't.
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed last year.
The community reviewed whether to reopen this question last year and left it closed:
Original close reason(s) were not resolved
Improve this question
I've recently heard a few people say that in Linux, it is almost always better to use processes instead of threads, since Linux is very efficient in handling processes, and because there are so many problems (such as locking) associated with threads. However, I am suspicious, because it seems like threads could give a pretty big performance gain in some situations.
So my question is, when faced with a situation that threads and processes could both handle pretty well, should I use processes or threads? For example, if I were writing a web server, should I use processes or threads (or a combination)?
Linux uses a 1-1 threading model, with (to the kernel) no distinction between processes and threads -- everything is simply a runnable task. *
On Linux, the system call clone clones a task, with a configurable level of sharing, among which are:
CLONE_FILES: share the same file descriptor table (instead of creating a copy)
CLONE_PARENT: don't set up a parent-child relationship between the new task and the old (otherwise, child's getppid() = parent's getpid())
CLONE_VM: share the same memory space (instead of creating a COW copy)
fork() calls clone(least sharing) and pthread_create() calls clone(most sharing). **
forking costs a tiny bit more than pthread_createing because of copying tables and creating COW mappings for memory, but the Linux kernel developers have tried (and succeeded) at minimizing those costs.
Switching between tasks, if they share the same memory space and various tables, will be a tiny bit cheaper than if they aren't shared, because the data may already be loaded in cache. However, switching tasks is still very fast even if nothing is shared -- this is something else that Linux kernel developers try to ensure (and succeed at ensuring).
In fact, if you are on a multi-processor system, not sharing may actually be beneficial to performance: if each task is running on a different processor, synchronizing shared memory is expensive.
* Simplified. CLONE_THREAD causes signals delivery to be shared (which needs CLONE_SIGHAND, which shares the signal handler table).
** Simplified. There exist both SYS_fork and SYS_clone syscalls, but in the kernel, the sys_fork and sys_clone are both very thin wrappers around the same do_fork function, which itself is a thin wrapper around copy_process. Yes, the terms process, thread, and task are used rather interchangeably in the Linux kernel...
Linux (and indeed Unix) gives you a third option.
Option 1 - processes
Create a standalone executable which handles some part (or all parts) of your application, and invoke it separately for each process, e.g. the program runs copies of itself to delegate tasks to.
Option 2 - threads
Create a standalone executable which starts up with a single thread and create additional threads to do some tasks
Option 3 - fork
Only available under Linux/Unix, this is a bit different. A forked process really is its own process with its own address space - there is nothing that the child can do (normally) to affect its parent's or siblings address space (unlike a thread) - so you get added robustness.
However, the memory pages are not copied, they are copy-on-write, so less memory is usually used than you might imagine.
Consider a web server program which consists of two steps:
Read configuration and runtime data
Serve page requests
If you used threads, step 1 would be done once, and step 2 done in multiple threads. If you used "traditional" processes, steps 1 and 2 would need to be repeated for each process, and the memory to store the configuration and runtime data duplicated. If you used fork(), then you can do step 1 once, and then fork(), leaving the runtime data and configuration in memory, untouched, not copied.
So there are really three choices.
That depends on a lot of factors. Processes are more heavy-weight than threads, and have a higher startup and shutdown cost. Interprocess communication (IPC) is also harder and slower than interthread communication.
Conversely, processes are safer and more secure than threads, because each process runs in its own virtual address space. If one process crashes or has a buffer overrun, it does not affect any other process at all, whereas if a thread crashes, it takes down all of the other threads in the process, and if a thread has a buffer overrun, it opens up a security hole in all of the threads.
So, if your application's modules can run mostly independently with little communication, you should probably use processes if you can afford the startup and shutdown costs. The performance hit of IPC will be minimal, and you'll be slightly safer against bugs and security holes. If you need every bit of performance you can get or have a lot of shared data (such as complex data structures), go with threads.
Others have discussed the considerations.
Perhaps the important difference is that in Windows processes are heavy and expensive compared to threads, and in Linux the difference is much smaller, so the equation balances at a different point.
Once upon a time there was Unix and in this good old Unix there was lots of overhead for processes, so what some clever people did was to create threads, which would share the same address space with the parent process and they only needed a reduced context switch, which would make the context switch more efficient.
In a contemporary Linux (2.6.x) there is not much difference in performance between a context switch of a process compared to a thread (only the MMU stuff is additional for the thread).
There is the issue with the shared address space, which means that a faulty pointer in a thread can corrupt memory of the parent process or another thread within the same address space.
A process is protected by the MMU, so a faulty pointer will just cause a signal 11 and no corruption.
I would in general use processes (not much context switch overhead in Linux, but memory protection due to MMU), but pthreads if I would need a real-time scheduler class, which is a different cup of tea all together.
Why do you think threads are have such a big performance gain on Linux? Do you have any data for this, or is it just a myth?
I think everyone has done a great job responding to your question. I'm just adding more information about thread versus process in Linux to clarify and summarize some of the previous responses in context of kernel. So, my response is in regarding to kernel specific code in Linux. According to Linux Kernel documentation, there is no clear distinction between thread versus process except thread uses shared virtual address space unlike process. Also note, the Linux Kernel uses the term "task" to refer to process and thread in general.
"There are no internal structures implementing processes or threads, instead there is a struct task_struct that describe an abstract scheduling unit called task"
Also according to Linus Torvalds, you should NOT think about process versus thread at all and because it's too limiting and the only difference is COE or Context of Execution in terms of "separate the address space from the parent " or shared address space. In fact he uses a web server example to make his point here (which highly recommend reading).
Full credit to linux kernel documentation
If you want to create a pure a process as possible, you would use clone() and set all the clone flags. (Or save yourself the typing effort and call fork())
If you want to create a pure a thread as possible, you would use clone() and clear all the clone flags (Or save yourself the typing effort and call pthread_create())
There are 28 flags that dictate the level of resource sharing. This means that there are over 268 million flavours of tasks that you can create, depending on what you want to share.
This is what we mean when we say that Linux does not distinguish between a process and a thread, but rather alludes to any flow of control within a program as a task. The rationale for not distinguishing between the two is, well, not uniquely defining over 268 million flavours!
Therefore, making the "perfect decision" of whether to use a process or thread is really about deciding which of the 28 resources to clone.
How tightly coupled are your tasks?
If they can live independently of each other, then use processes. If they rely on each other, then use threads. That way you can kill and restart a bad process without interfering with the operation of the other tasks.
To complicate matters further, there is such a thing as thread-local storage, and Unix shared memory.
Thread-local storage allows each thread to have a separate instance of global objects. The only time I've used it was when constructing an emulation environment on linux/windows, for application code that ran in an RTOS. In the RTOS each task was a process with it's own address space, in the emulation environment, each task was a thread (with a shared address space). By using TLS for things like singletons, we were able to have a separate instance for each thread, just like under the 'real' RTOS environment.
Shared memory can (obviously) give you the performance benefits of having multiple processes access the same memory, but at the cost/risk of having to synchronize the processes properly. One way to do that is have one process create a data structure in shared memory, and then send a handle to that structure via traditional inter-process communication (like a named pipe).
In my recent work with LINUX is one thing to be aware of is libraries. If you are using threads make sure any libraries you may use across threads are thread-safe. This burned me a couple of times. Notably libxml2 is not thread-safe out of the box. It can be compiled with thread safe but that is not what you get with aptitude install.
I'd have to agree with what you've been hearing. When we benchmark our cluster (xhpl and such), we always get significantly better performance with processes over threads. </anecdote>
The decision between thread/process depends a little bit on what you will be using it to.
One of the benefits with a process is that it has a PID and can be killed without also terminating the parent.
For a real world example of a web server, apache 1.3 used to only support multiple processes, but in in 2.0 they added an abstraction so that you can swtch between either. Comments seems to agree that processes are more robust but threads can give a little bit better performance (except for windows where performance for processes sucks and you only want to use threads).
For most cases i would prefer processes over threads.
threads can be useful when you have a relatively smaller task (process overhead >> time taken by each divided task unit) and there is a need of memory sharing between them. Think a large array.
Also (offtopic), note that if your CPU utilization is 100 percent or close to it, there is going to be no benefit out of multithreading or processing. (in fact it will worsen)
Threads -- > Threads shares a memory space,it is an abstraction of the CPU,it is lightweight.
Processes --> Processes have their own memory space,it is an abstraction of a computer.
To parallelise task you need to abstract a CPU.
However the advantages of using a process over a thread is security,stability while a thread uses lesser memory than process and offers lesser latency.
An example in terms of web would be chrome and firefox.
In case of Chrome each tab is a new process hence memory usage of chrome is higher than firefox ,while the security and stability provided is better than firefox.
The security here provided by chrome is better,since each tab is a new process different tab cannot snoop into the memory space of a given process.
Multi-threading is for masochists. :)
If you are concerned about an environment where you are constantly creating threads/forks, perhaps like a web server handling requests, you can pre-fork processes, hundreds if necessary. Since they are Copy on Write and use the same memory until a write occurs, it's very fast. They can all block, listening on the same socket and the first one to accept an incoming TCP connection gets to run with it. With g++ you can also assign functions and variables to be closely placed in memory (hot segments) to ensure when you do write to memory, and cause an entire page to be copied at least subsequent write activity will occur on the same page. You really have to use a profiler to verify that kind of stuff but if you are concerned about performance, you should be doing that anyway.
Development time of threaded apps is 3x to 10x times longer due to the subtle interaction on shared objects, threading "gotchas" you didn't think of, and very hard to debug because you cannot reproduce thread interaction problems at will. You may have to do all sort of performance killing checks like having invariants in all your classes that are checked before and after every function and you halt the process and load the debugger if something isn't right. Most often it's embarrassing crashes that occur during production and you have to pore through a core dump trying to figure out which threads did what. Frankly, it's not worth the headache when forking processes is just as fast and implicitly thread safe unless you explicitly share something. At least with explicit sharing you know exactly where to look if a threading style problem occurs.
If performance is that important, add another computer and load balance. For the developer cost of debugging a multi-threaded app, even one written by an experienced multi-threader, you could probably buy 4 40 core Intel motherboards with 64gigs of memory each.
That being said, there are asymmetric cases where parallel processing isn't appropriate, like, you want a foreground thread to accept user input and show button presses immediately, without waiting for some clunky back end GUI to keep up. Sexy use of threads where multiprocessing isn't geometrically appropriate. Many things like that just variables or pointers. They aren't "handles" that can be shared in a fork. You have to use threads. Even if you did fork, you'd be sharing the same resource and subject to threading style issues.
If you need to share resources, you really should use threads.
Also consider the fact that context switches between threads are much less expensive than context switches between processes.
I see no reason to explicitly go with separate processes unless you have a good reason to do so (security, proven performance tests, etc...)