In rust, there is such a thing as an AtomicBool. It is defined as:
A boolean type which can be safely shared between threads.
I understand that if you're using a boolean to implement a thread lock, to be used from multiple threads to control access to a resource, doing something like:
// Acquire the lock
if thread_lock == false:
thread_lock = true
...
// Release the lock
thread_lock = false
Is definitely not thread safe. Both threads can read the thread_lock variable at the same time, see that it's unlocked (false), set it to true, and both think they have exclusive access to the thread.
With a proper thread lock, you need a boolean where, when you try to set it, one of two things will happen:
Trying to acquire a lock can fail if another thread already has a lock
Trying to acquire a lock will block until no other threads have a lock
I don't know if Rust has a concept like this, but I know Python's threading.Lock does exactly that.
As far as I can tell, this is NOT the scenario that an AtomicBool addresses. An AtomicBool has a load() method, and a store() method. Neither return a Result<bool> type (implying the operation can't fail), and as far as I can tell, neither do any kind of blocking.
What exactly does an AtomicBool protect us from? Why can we not use a regular bool from different threads (other than the fact that the compiler won't let us)?
The only thing I can think of is that when one thread is writing the bits into memory, another might try to read those bits at the same time. A bool is 8 bits. If 4 of the 8 bits were written when the other thread tries to read the data, the data read will be 4 bits of the old value, and 4 bits of the new value. Is this the problem being addressed? Can this happen? It doesn't seem like even in that scenario, a bool would need to be atomic, since of the 8 bits, only one bit matters, which will either be a 0 or a 1.
What exactly does an AtomicBool protect us from? Why can we not use a regular bool from different threads (other than the fact that the compiler won't let us)?
Anything that might go wrong, whether you can think of it or not. I hate to follow this up with something I can think of, because it doesn't matter. The rules say it's not guaranteed to work and that should end it. Thinking you have to think of a way it can fail or it can't fail is just wrong.
But here's one way:
// Release the lock
thread_lock = false
Say this particular CPU doesn't have a particularly good way to set a boolean to false without using a register but does have a good single operation that negates a boolean and tests if it's zero without using a register. On this CPU, in conditions of register pressure, this might get optimized to:
Negate thread_lock and test if it's zero.
If the copy of thread_lock was false, negate thread_lock again.
What happens if in-betweens steps 1 and 2 another thread observes thread_lock to be true even though it was false going into this operation and will be false when it's done?
The thread lock in Rust is Mutex. It is typically used to provide multi-thread mutable access to a value (which is usually the reason why you want to lock between threads), but you can also use it to lock an empty tuple Mutex<()> to lock on nothing. I can't think of good reasons that you need to lock threads without needing to lock on particular values, though; for example if you want to write to a log file from multiple threads, you might want to have a Mutex<fs::File> like this:
let file = Arc::new(Mutex::new(fs::File::create("write.log")?));
for _ in 0..10 {
let file = Arc::clone(&file);
thread::spawn(move |file| {
// do other stuff
let mut guard = file.lock();
guard.write_all(b"stuff").unwrap();
drop(guard);
// do other stuff
Ok(())
})
}
For atomic values, usually the most important primitives are not load and store but compare_and_exchange, etc. Atomics can be thought as "lightweight" mutexes that only contain primitive data, but you perform all operations you want in a single call instead of acquiring and releasing it in two separate operations. Furthermore, mutexes can actually be implemented based on an AtomicBool if the operating system doesn't support it, like the following code:
struct MyMutex(AtomicBool);
impl MyMutex {
fn try_lock(&self) -> Result<(), ()> {
let result = self.0.compare_exchange(false, true, Ordering::SeqCst);
if result {
Ok(()) // we have acquired the lock
} else {
Err(()) // someone else is holding the lock
}
}
fn release(&self) {
self.0.store(false, Ordering::Release);
}
}
You can share any value that is Sync from multiple threads, provided that you can deal with the lifetime properly. For example, the following compiles without any unsafe code:
fn process(b: &'static bool) {
if b { do_something () }
else { do_something_else() }
}
fn main() {
let boxed = Box::new(true);
let refed: &'static bool = my_bool.leak();
for _ in 0..10 {
thread::spawn(move || process(refed));
}
}
You can also do this with non-'static references with the sufficient tools, such as wrapping them in Arcs, etc.
A bool is 8 bits. If 4 of the 8 bits were written when the other thread tries to read the data, the data read will be 4 bits of the old value, and 4 bits of the new value.
This cannot happen in Rust. Rust enforces ownership and borrowing very strictly. You can't even have two mutable references to the same value on the same thread, much less on different threads.
Multiple mutable references to the same value is always Undefined Behaviour in Rust; there are no exceptions to this strict rule. By declaring that a reference is mutable, the compiler is allowed to do various optimizations on your code assuming that we are the unique place that can read/write the value; not other threads, not other functions, not even other variables (if a: &mut bool and let b = &mut *a, you can't use a before b is dropped). You will have much worse problems than writing different bits concurrently if you have multiple mutable pointers.
(By the way, "writing bits" to the same value is not a correct way of thinking it; it's much more complicated than "writing bits" in modern CPUs even without Rust's borrow checking rules)
TL;DR: If you don't have the unsafe keyword anyway in your code, you don't need to worry about race conditions. Rust is a very memory-safe language where memory bugs are mostly checked at compile time.
When I spawn a thread in Rust, I get a JoinHandle, which is good for... joining (a blocking operation), and not much else. How can I check if a child thread has exited (i.e., JoinHandle.join() would not block) from the parent thread? Bonus points if you know how to kill a child thread.
I imagine you could do this by creating a channel, sending something to the child, and catching errors, but that seems like needless complexity and overhead.
As of Rust 1.7, there's no API in the standard library to check if a child thread has exited without blocking.
A portable workaround would be to use channels to send a message from the child to the parent to signal that the child is about to exit. Receiver has a non-blocking try_recv method. When try_recv does receive a message, you can then use join() on the JoinHandle to retrieve the thread's result.
There are also unstable platform-specific extension traits that let you obtain the raw thread handle. You'd then have to write platform-specific code to test whether the thread has exited or not.
If you think this feature should be in Rust's standard library, you can submit an RFC (be sure to read the README first!).
Bonus points if you know how to kill a child thread.
Threads in Rust are implemented using native OS threads. Even though the operating system might provide a way to kill a thread, it's a bad idea to do so, because the resources that the thread allocated will not be cleaned up until the process ends.
The short answer is not possible yet. But this is not the point that should really be addressed.
Bonus points if you know how to kill a child thread.
NEVER
Even in languages that do support killing threads (see Java here), it is recommended not to.
A thread's execution is generally coded with explicit points of interactions, and there are often implicit assumptions that no other interruption will occur.
The most egregious example is of course resources: the naive "kill" method would be to stop executing the thread; this would mean not releasing any resource. You may think about memory, it's the least of your worries. Imagine, instead, all the Mutex that are not unlocked and will create deadlocks later...
The other option would be to inject a panic in the thread, which would cause unwinding. However, you cannot just start unwinding at any point! The program would have to define safe points at which injecting a panic would be guaranteed to be safe (injecting it at any other point means potentially corrupting shared objects); how to define such safe points and inject the panic there is an open research problem in native languages, especially those executed on systems W^X (where memory pages are either Writable or Executable but never both).
In summary, there is no known way to safely (both memory-wise and functionality-wise) kill a thread.
It's possible, friends. Use refcounters which Rust will drop on end or panic. 100% safe. Example:
use std::time::Duration;
use std::sync::Arc;
use std::sync::atomic::{AtomicBool, Ordering};
use std::thread;
fn main() {
// Play with this flag
let fatal_flag = true;
let do_stop = true;
let working = Arc::new(AtomicBool::new(true));
let control = Arc::downgrade(&working);
thread::spawn(move || {
while (*working).load(Ordering::Relaxed) {
if fatal_flag {
panic!("Oh, my God!");
} else {
thread::sleep(Duration::from_millis(20));
println!("I'm alive!");
}
}
});
thread::sleep(Duration::from_millis(50));
// To stop thread
if do_stop {
match control.upgrade() {
Some(working) => (*working).store(false, Ordering::Relaxed),
None => println!("Sorry, but thread died already."),
}
}
thread::sleep(Duration::from_millis(50));
// To check it's alive / died
match control.upgrade() {
Some(_) => println!("Thread alive!"),
None => println!("Thread ends!"),
}
}
Gist: https://gist.github.com/DenisKolodin/edea80f2f5becb86f718c330219178e2
At playground: https://play.rust-lang.org/?gist=9a0cf161ba0bbffe3824b9db4308e1fb&version=stable&backtrace=0
UPD: I've created thread-control crate which implements this approach: https://github.com/DenisKolodin/thread-control
I think Arc can be used to solve this problem
If the thread exits, the reference counter is reduced by one
As of rust 1.61.0, there is an is_finished method.
https://doc.rust-lang.org/stable/std/thread/struct.JoinHandle.html#method.is_finished
It seems to be a common idiom in Rust to spawn off a thread for blocking IO so you can use non-blocking channels:
use std::sync::mpsc::channel;
use std::thread;
use std::net::TcpListener;
fn main() {
let (accept_tx, accept_rx) = channel();
let listener_thread = thread::spawn(move || {
let listener = TcpListener::bind(":::0").unwrap();
for client in listener.incoming() {
if let Err(_) = accept_tx.send(client.unwrap()) {
break;
}
}
});
}
The problem is, rejoining threads like this depends on the spawned thread "realizing" that the receiving end of the channel has been dropped (i.e., calling send(..) returns Err(_)):
drop(accept_rx);
listener_thread.join(); // blocks until listener thread reaches accept_tx.send(..)
You can make dummy connections for TcpListeners, and shutdown TcpStreams via a clone, but these seem like really hacky ways to clean up such threads, and as it stands, I don't even know of a hack to trigger a thread blocking on a read from stdin to join.
How can I clean up threads like these, or is my architecture just wrong?
One simply cannot safely cancel a thread reliably in Windows or Linux/Unix/POSIX, so it isn't available in the Rust standard library.
Here is an internals discussion about it.
There are a lot of unknowns that come from cancelling threads forcibly. It can get really messy. Beyond that, the combination of threads and blocking I/O will always face this issue: you need every blocking I/O call to have timeouts for it to even have a chance of being interruptible reliably. If one can't write async code, one needs to either use processes (which have a defined boundary and can be ended by the OS forcibly, but obviously come with heavier weight and data sharing challenges) or non-blocking I/O which will land your thread back in an event loop that is interruptible.
mio is available for async code. Tokio is a higher level crate based on mio which makes writing non-blocking async code even more straight forward.
I've always been told to puts locks around variables that multiple threads will access, I've always assumed that this was because you want to make sure that the value you are working with doesn't change before you write it back
i.e.
mutex.lock()
int a = sharedVar
a = someComplexOperation(a)
sharedVar = a
mutex.unlock()
And that makes sense that you would lock that. But in other cases I don't understand why I can't get away with not using Mutexes.
Thread A:
sharedVar = someFunction()
Thread B:
localVar = sharedVar
What could possibly go wrong in this instance? Especially if I don't care that Thread B reads any particular value that Thread A assigns.
It depends a lot on the type of sharedVar, the language you're using, any framework, and the platform. In many cases, it's possible that assigning a single value to sharedVar may take more than one instruction, in which case you may read a "half-set" copy of the value.
Even when that's not the case, and the assignment is atomic, you may not see the latest value without a memory barrier in place.
MSDN Magazine has a good explanation of different problems you may encounter in multithreaded code:
Forgotten Synchronization
Incorrect Granularity
Read and Write Tearing
Lock-Free Reordering
Lock Convoys
Two-Step Dance
Priority Inversion
The code in your question is particularly vulnerable to Read/Write Tearing. But your code, having neither locks nor memory barriers, is also subject to Lock-Free Reordering (which may include speculative writes in which thread B reads a value that thread A never stored) in which side-effects become visible to a second thread in a different order from how they appeared in your source code.
It goes on to describe some known design patterns which avoid these problems:
Immutability
Purity
Isolation
The article is available here
The main problem is that the assignment operator (operator= in C++) is not always guaranteed to be atomic (not even for primitive, built in types). In plain English, that means that assignment can take more than a single clock cycle to complete. If, in the middle of that, the thread gets interrupted, then the current value of the variable might be corrupted.
Let me build off of your example:
Lets say sharedVar is some object with operator= defined as this:
object& operator=(const object& other) {
ready = false;
doStuff(other);
if (other.value == true) {
value = true;
doOtherStuff();
} else {
value = false;
}
ready = true;
return *this;
}
If thread A from your example is interrupted in the middle of this function, ready will still be false when thread B starts to run. This could mean that the object is only partially copied over, or is in some intermediate, invalid state when thread B attempts to copy it into a local variable.
For a particularly nasty example of this, think of a data structure with a removed node being deleted, then interrupted before it could be set to NULL.
(For some more information regarding structures that don't need a lock (aka, are atomic), here is another question that talks a bit more about that.)
This could go wrong, because threads can be suspended and resumed by the thread scheduler, so you can't be sure about the order these instructions are executed. It might just as well be in this order:
Thread B:
localVar = sharedVar
Thread A:
sharedVar = someFunction()
In which case localvar will be null or 0 (or some completeley unexpected value in an unsafe language), probably not what you intended.
Mutexes actually won't fix this particular issue by the way. The example you supply does not lend itself well for parallelization.
A semaphore is a programming concept that is frequently used to solve multi-threading problems. My question to the community:
What is a semaphore and how do you use it?
Think of semaphores as bouncers at a nightclub. There are a dedicated number of people that are allowed in the club at once. If the club is full no one is allowed to enter, but as soon as one person leaves another person might enter.
It's simply a way to limit the number of consumers for a specific resource. For example, to limit the number of simultaneous calls to a database in an application.
Here is a very pedagogic example in C# :-)
using System;
using System.Collections.Generic;
using System.Text;
using System.Threading;
namespace TheNightclub
{
public class Program
{
public static Semaphore Bouncer { get; set; }
public static void Main(string[] args)
{
// Create the semaphore with 3 slots, where 3 are available.
Bouncer = new Semaphore(3, 3);
// Open the nightclub.
OpenNightclub();
}
public static void OpenNightclub()
{
for (int i = 1; i <= 50; i++)
{
// Let each guest enter on an own thread.
Thread thread = new Thread(new ParameterizedThreadStart(Guest));
thread.Start(i);
}
}
public static void Guest(object args)
{
// Wait to enter the nightclub (a semaphore to be released).
Console.WriteLine("Guest {0} is waiting to entering nightclub.", args);
Bouncer.WaitOne();
// Do some dancing.
Console.WriteLine("Guest {0} is doing some dancing.", args);
Thread.Sleep(500);
// Let one guest out (release one semaphore).
Console.WriteLine("Guest {0} is leaving the nightclub.", args);
Bouncer.Release(1);
}
}
}
The article Mutexes and Semaphores Demystified by Michael Barr is a great short introduction into what makes mutexes and semaphores different, and when they should and should not be used. I've excerpted several key paragraphs here.
The key point is that mutexes should be used to protect shared resources, while semaphores should be used for signaling. You should generally not use semaphores to protect shared resources, nor mutexes for signaling. There are issues, for instance, with the bouncer analogy in terms of using semaphores to protect shared resources - you can use them that way, but it may cause hard to diagnose bugs.
While mutexes and semaphores have some similarities in their implementation, they should always be used differently.
The most common (but nonetheless incorrect) answer to the question posed at the top is that mutexes and semaphores are very similar, with the only significant difference being that semaphores can count higher than one. Nearly all engineers seem to properly understand that a mutex is a binary flag used to protect a shared resource by ensuring mutual exclusion inside critical sections of code. But when asked to expand on how to use a "counting semaphore," most engineers—varying only in their degree of confidence—express some flavor of the textbook opinion that these are used to protect several equivalent resources.
...
At this point an interesting analogy is made using the idea of bathroom keys as protecting shared resources - the bathroom. If a shop has a single bathroom, then a single key will be sufficient to protect that resource and prevent multiple people from using it simultaneously.
If there are multiple bathrooms, one might be tempted to key them alike and make multiple keys - this is similar to a semaphore being mis-used. Once you have a key you don't actually know which bathroom is available, and if you go down this path you're probably going to end up using mutexes to provide that information and make sure you don't take a bathroom that's already occupied.
A semaphore is the wrong tool to protect several of the essentially same resource, but this is how many people think of it and use it. The bouncer analogy is distinctly different - there aren't several of the same type of resource, instead there is one resource which can accept multiple simultaneous users. I suppose a semaphore can be used in such situations, but rarely are there real-world situations where the analogy actually holds - it's more often that there are several of the same type, but still individual resources, like the bathrooms, which cannot be used this way.
...
The correct use of a semaphore is for signaling from one task to another. A mutex is meant to be taken and released, always in that order, by each task that uses the shared resource it protects. By contrast, tasks that use semaphores either signal or wait—not both. For example, Task 1 may contain code to post (i.e., signal or increment) a particular semaphore when the "power" button is pressed and Task 2, which wakes the display, pends on that same semaphore. In this scenario, one task is the producer of the event signal; the other the consumer.
...
Here an important point is made that mutexes interfere with real time operating systems in a bad way, causing priority inversion where a less important task may be executed before a more important task because of resource sharing. In short, this happens when a lower priority task uses a mutex to grab a resource, A, then tries to grab B, but is paused because B is unavailable. While it's waiting, a higher priority task comes along and needs A, but it's already tied up, and by a process that isn't even running because it's waiting for B. There are many ways to resolve this, but it most often is fixed by altering the mutex and task manager. The mutex is much more complex in these cases than a binary semaphore, and using a semaphore in such an instance will cause priority inversions because the task manager is unaware of the priority inversion and cannot act to correct it.
...
The cause of the widespread modern confusion between mutexes and semaphores is historical, as it dates all the way back to the 1974 invention of the Semaphore (capital "S", in this article) by Djikstra. Prior to that date, none of the interrupt-safe task synchronization and signaling mechanisms known to computer scientists was efficiently scalable for use by more than two tasks. Dijkstra's revolutionary, safe-and-scalable Semaphore was applied in both critical section protection and signaling. And thus the confusion began.
However, it later became obvious to operating system developers, after the appearance of the priority-based preemptive RTOS (e.g., VRTX, ca. 1980), publication of academic papers establishing RMA and the problems caused by priority inversion, and a paper on priority inheritance protocols in 1990, 3 it became apparent that mutexes must be more than just semaphores with a binary counter.
Mutex: resource sharing
Semaphore: signaling
Don't use one for the other without careful consideration of the side effects.
Mutex: exclusive-member access to a resource
Semaphore: n-member access to a resource
That is, a mutex can be used to syncronize access to a counter, file, database, etc.
A sempahore can do the same thing but supports a fixed number of simultaneous callers. For example, I can wrap my database calls in a semaphore(3) so that my multithreaded app will hit the database with at most 3 simultaneous connections. All attempts will block until one of the three slots opens up. They make things like doing naive throttling really, really easy.
Consider, a taxi that can accommodate a total of 3(rear)+2(front) persons including the driver. So, a semaphore allows only 5 persons inside a car at a time.
And a mutex allows only 1 person on a single seat of the car.
Therefore, Mutex is to allow exclusive access for a resource (like an OS thread) while a Semaphore is to allow access for n number of resources at a time.
#Craig:
A semaphore is a way to lock a
resource so that it is guaranteed that
while a piece of code is executed,
only this piece of code has access to
that resource. This keeps two threads
from concurrently accesing a resource,
which can cause problems.
This is not restricted to only one thread. A semaphore can be configured to allow a fixed number of threads to access a resource.
Semaphore can also be used as a ... semaphore.
For example if you have multiple process enqueuing data to a queue, and only one task consuming data from the queue. If you don't want your consuming task to constantly poll the queue for available data, you can use semaphore.
Here the semaphore is not used as an exclusion mechanism, but as a signaling mechanism.
The consuming task is waiting on the semaphore
The producing task are posting on the semaphore.
This way the consuming task is running when and only when there is data to be dequeued
There are two essential concepts to building concurrent programs - synchronization and mutual exclusion. We will see how these two types of locks (semaphores are more generally a kind of locking mechanism) help us achieve synchronization and mutual exclusion.
A semaphore is a programming construct that helps us achieve concurrency, by implementing both synchronization and mutual exclusion. Semaphores are of two types, Binary and Counting.
A semaphore has two parts : a counter, and a list of tasks waiting to access a particular resource. A semaphore performs two operations : wait (P) [this is like acquiring a lock], and release (V)[ similar to releasing a lock] - these are the only two operations that one can perform on a semaphore. In a binary semaphore, the counter logically goes between 0 and 1. You can think of it as being similar to a lock with two values : open/closed. A counting semaphore has multiple values for count.
What is important to understand is that the semaphore counter keeps track of the number of tasks that do not have to block, i.e., they can make progress. Tasks block, and add themselves to the semaphore's list only when the counter is zero. Therefore, a task gets added to the list in the P() routine if it cannot progress, and "freed" using the V() routine.
Now, it is fairly obvious to see how binary semaphores can be used to solve synchronization and mutual exclusion - they are essentially locks.
ex. Synchronization:
thread A{
semaphore &s; //locks/semaphores are passed by reference! think about why this is so.
A(semaphore &s): s(s){} //constructor
foo(){
...
s.P();
;// some block of code B2
...
}
//thread B{
semaphore &s;
B(semaphore &s): s(s){} //constructor
foo(){
...
...
// some block of code B1
s.V();
..
}
main(){
semaphore s(0); // we start the semaphore at 0 (closed)
A a(s);
B b(s);
}
In the above example, B2 can only execute after B1 has finished execution. Let's say thread A comes executes first - gets to sem.P(), and waits, since the counter is 0 (closed). Thread B comes along, finishes B1, and then frees thread A - which then completes B2. So we achieve synchronization.
Now let's look at mutual exclusion with a binary semaphore:
thread mutual_ex{
semaphore &s;
mutual_ex(semaphore &s): s(s){} //constructor
foo(){
...
s.P();
//critical section
s.V();
...
...
s.P();
//critical section
s.V();
...
}
main(){
semaphore s(1);
mutual_ex m1(s);
mutual_ex m2(s);
}
The mutual exclusion is quite simple as well - m1 and m2 cannot enter the critical section at the same time. So each thread is using the same semaphore to provide mutual exclusion for its two critical sections. Now, is it possible to have greater concurrency? Depends on the critical sections. (Think about how else one could use semaphores to achieve mutual exclusion.. hint hint : do i necessarily only need to use one semaphore?)
Counting semaphore: A semaphore with more than one value. Let's look at what this is implying - a lock with more than one value?? So open, closed, and ...hmm. Of what use is a multi-stage-lock in mutual exclusion or synchronization?
Let's take the easier of the two:
Synchronization using a counting semaphore: Let's say you have 3 tasks - #1 and 2 you want executed after 3. How would you design your synchronization?
thread t1{
...
s.P();
//block of code B1
thread t2{
...
s.P();
//block of code B2
thread t3{
...
//block of code B3
s.V();
s.V();
}
So if your semaphore starts off closed, you ensure that t1 and t2 block, get added to the semaphore's list. Then along comes all important t3, finishes its business and frees t1 and t2. What order are they freed in? Depends on the implementation of the semaphore's list. Could be FIFO, could be based some particular priority,etc. (Note : think about how you would arrange your P's and V;s if you wanted t1 and t2 to be executed in some particular order, and if you weren't aware of the implementation of the semaphore)
(Find out : What happens if the number of V's is greater than the number of P's?)
Mutual Exclusion Using counting semaphores: I'd like you to construct your own pseudocode for this (makes you understand things better!) - but the fundamental concept is this : a counting semaphore of counter = N allows N tasks to enter the critical section freely. What this means is you have N tasks (or threads, if you like) enter the critical section, but the N+1th task gets blocked (goes on our favorite blocked-task list), and only is let through when somebody V's the semaphore at least once. So the semaphore counter, instead of swinging between 0 and 1, now goes between 0 and N, allowing N tasks to freely enter and exit, blocking nobody!
Now gosh, why would you need such a stupid thing? Isn't the whole point of mutual exclusion to not let more than one guy access a resource?? (Hint Hint...You don't always only have one drive in your computer, do you...?)
To think about : Is mutual exclusion achieved by having a counting semaphore alone? What if you have 10 instances of a resource, and 10 threads come in (through the counting semaphore) and try to use the first instance?
I've created the visualization which should help to understand the idea. Semaphore controls access to a common resource in a multithreading environment.
ExecutorService executor = Executors.newFixedThreadPool(7);
Semaphore semaphore = new Semaphore(4);
Runnable longRunningTask = () -> {
boolean permit = false;
try {
permit = semaphore.tryAcquire(1, TimeUnit.SECONDS);
if (permit) {
System.out.println("Semaphore acquired");
Thread.sleep(5);
} else {
System.out.println("Could not acquire semaphore");
}
} catch (InterruptedException e) {
throw new IllegalStateException(e);
} finally {
if (permit) {
semaphore.release();
}
}
};
// execute tasks
for (int j = 0; j < 10; j++) {
executor.submit(longRunningTask);
}
executor.shutdown();
Output
Semaphore acquired
Semaphore acquired
Semaphore acquired
Semaphore acquired
Could not acquire semaphore
Could not acquire semaphore
Could not acquire semaphore
Sample code from the article
A semaphore is an object containing a natural number (i.e. a integer greater or equal to zero) on which two modifying operations are defined. One operation, V, adds 1 to the natural. The other operation, P, decreases the natural number by 1. Both activities are atomic (i.e. no other operation can be executed at the same time as a V or a P).
Because the natural number 0 cannot be decreased, calling P on a semaphore containing a 0 will block the execution of the calling process(/thread) until some moment at which the number is no longer 0 and P can be successfully (and atomically) executed.
As mentioned in other answers, semaphores can be used to restrict access to a certain resource to a maximum (but variable) number of processes.
A hardware or software flag. In multi tasking systems , a semaphore is as variable with a value that indicates the status of a common resource.A process needing the resource checks the semaphore to determine the resources status and then decides how to proceed.
Semaphores are act like thread limiters.
Example: If you have a pool of 100 threads and you want to perform some DB operation. If 100 threads access the DB at a given time, then there may be locking issue in DB so we can use semaphore which allow only limited thread at a time.Below Example allow only one thread at a time. When a thread call the acquire() method, it will then get the access and after calling the release() method, it will release the acccess so that next thread will get the access.
package practice;
import java.util.concurrent.Semaphore;
public class SemaphoreExample {
public static void main(String[] args) {
Semaphore s = new Semaphore(1);
semaphoreTask s1 = new semaphoreTask(s);
semaphoreTask s2 = new semaphoreTask(s);
semaphoreTask s3 = new semaphoreTask(s);
semaphoreTask s4 = new semaphoreTask(s);
semaphoreTask s5 = new semaphoreTask(s);
s1.start();
s2.start();
s3.start();
s4.start();
s5.start();
}
}
class semaphoreTask extends Thread {
Semaphore s;
public semaphoreTask(Semaphore s) {
this.s = s;
}
#Override
public void run() {
try {
s.acquire();
Thread.sleep(1000);
System.out.println(Thread.currentThread().getName()+" Going to perform some operation");
s.release();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
So imagine everyone is trying to go to the bathroom and there's only a certain number of keys to the bathroom. Now if there's not enough keys left, that person needs to wait. So think of semaphore as representing those set of keys available for bathrooms (the system resources) that different processes (bathroom goers) can request access to.
Now imagine two processes trying to go to the bathroom at the same time. That's not a good situation and semaphores are used to prevent this. Unfortunately, the semaphore is a voluntary mechanism and processes (our bathroom goers) can ignore it (i.e. even if there are keys, someone can still just kick the door open).
There are also differences between binary/mutex & counting semaphores.
Check out the lecture notes at http://www.cs.columbia.edu/~jae/4118/lect/L05-ipc.html.
This is an old question but one of the most interesting uses of semaphore is a read/write lock and it has not been explicitly mentioned.
The r/w locks works in simple fashion: consume one permit for a reader and all permits for writers.
Indeed, a trivial implementation of a r/w lock but requires metadata modification on read (actually twice) that can become a bottle neck, still significantly better than a mutex or lock.
Another downside is that writers can be started rather easily as well unless the semaphore is a fair one or the writes acquire permits in multiple requests, in such case they need an explicit mutex between themselves.
Further read:
Mutex is just a boolean while semaphore is a counter.
Both are used to lock part of code so it's not accessed by too many threads.
Example
lock.set()
a += 1
lock.unset()
Now if lock was a mutex, it means that it will always be locked or unlocked (a boolean under the surface) regardless how many threads try access the protected snippet of code. While locked, any other thread would just wait until it's unlocked/unset by the previous thread.
Now imagine if instead lock was under the hood a counter with a predefined MAX value (say 2 for our example). Then if 2 threads try to access the resource, then lock would get its value increased to 2. If a 3rd thread then tried to access it, it would simply wait for the counter to go below 2 and so on.
If lock as a semaphore had a max of 1, then it would be acting exactly as a mutex.
A semaphore is a way to lock a resource so that it is guaranteed that while a piece of code is executed, only this piece of code has access to that resource. This keeps two threads from concurrently accesing a resource, which can cause problems.