Signaling to the Threads to Stop Listening for Jobs
With all the changes we've made, our code compiles without any warnings. However, the bad news is that this code doesn't function the way we want it to yet. The key is the logic in the closures run by the threads of the Worker instances: at the moment, we call join, but that won't shut down the threads, because they loop forever looking for jobs. If we try to drop our ThreadPool with our current implementation of drop, the main thread will block forever, waiting for the first thread to finish.
To fix this problem, we'll need a change in the ThreadPool drop implementation and then a change in the Worker loop.
First we'll change the ThreadPool drop implementation to explicitly drop the sender before waiting for the threads to finish. Listing 20-23 shows the changes to ThreadPool to explicitly drop sender. We use the same Option and take technique as we did with the thread to be able to move sender out of ThreadPool.
Filename: src/lib.rs
pub struct ThreadPool {
workers: Vec<Worker>,
sender: Option<mpsc::Sender<Job>>,
}
--snip--
impl ThreadPool {
pub fn new(size: usize) -> ThreadPool {
--snip--
ThreadPool {
workers,
sender: Some(sender),
}
}
pub fn execute<F>(&self, f: F)
where
F: FnOnce() + Send + 'static,
{
let job = Box::new(f);
self.sender
.as_ref()
.unwrap()
.send(job)
.unwrap();
}
}
impl Drop for ThreadPool {
fn drop(&mut self) {
1 drop(self.sender.take());
for worker in &mut self.workers {
println!("Shutting down worker {}", worker.id);
if let Some(thread) = worker.thread.take() {
thread.join().unwrap();
}
}
}
}
Listing 20-23: Explicitly dropping sender before joining the Worker threads
Dropping sender [1] closes the channel, which indicates no more messages will be sent. When that happens, all the calls to recv that the Worker instances do in the infinite loop will return an error. In Listing 20-24, we change the Worker loop to gracefully exit the loop in that case, which means the threads will finish when the ThreadPool drop implementation calls join on them.
Filename: src/lib.rs
impl Worker {
fn new(
id: usize,
receiver: Arc<Mutex<mpsc::Receiver<Job>>>,
) -> Worker {
let thread = thread::spawn(move || loop {
let message = receiver.lock().unwrap().recv();
match message {
Ok(job) => {
println!(
"Worker {id} got a job; executing."
);
job();
}
Err(_) => {
println!(
"Worker {id} shutting down."
);
break;
}
}
});
Worker {
id,
thread: Some(thread),
}
}
}
Listing 20-24: Explicitly breaking out of the loop when recv returns an error
To see this code in action, let's modify main to accept only two requests before gracefully shutting down the server, as shown in Listing 20-25.
Filename: src/main.rs
fn main() {
let listener = TcpListener::bind("127.0.0.1:7878").unwrap();
let pool = ThreadPool::new(4);
for stream in listener.incoming().take(2) {
let stream = stream.unwrap();
pool.execute(|| {
handle_connection(stream);
});
}
println!("Shutting down.");
}
Listing 20-25: Shutting down the server after serving two requests by exiting the loop
You wouldn't want a real-world web server to shut down after serving only two requests. This code just demonstrates that the graceful shutdown and cleanup is in working order.
The take method is defined in the Iterator trait and limits the iteration to the first two items at most. The ThreadPool will go out of scope at the end of main, and the drop implementation will run.
Start the server with cargo run, and make three requests. The third request should error, and in your terminal you should see output similar to this:
$ cargo run
Compiling hello v0.1.0 (file:///projects/hello)
Finished dev [unoptimized + debuginfo] target(s) in 1.0s
Running `target/debug/hello`
Worker 0 got a job; executing.
Shutting down.
Shutting down worker 0
Worker 3 got a job; executing.
Worker 1 disconnected; shutting down.
Worker 2 disconnected; shutting down.
Worker 3 disconnected; shutting down.
Worker 0 disconnected; shutting down.
Shutting down worker 1
Shutting down worker 2
Shutting down worker 3
You might see a different ordering of Worker IDs and messages printed. We can see how this code works from the messages: Worker instances 0 and 3 got the first two requests. The server stopped accepting connections after the second connection, and the Drop implementation on ThreadPool starts executing before Worker 3 even starts its job. Dropping the sender disconnects all the Worker instances and tells them to shut down. The Worker instances each print a message when they disconnect, and then the thread pool calls join to wait for each Worker thread to finish.
Notice one interesting aspect of this particular execution: the ThreadPool dropped the sender, and before any Worker received an error, we tried to join Worker 0. Worker 0 had not yet gotten an error from recv, so the main thread blocked, waiting for Worker 0 to finish. In the meantime, Worker 3 received a job and then all threads received an error. When Worker 0 finished, the main thread waited for the rest of the Worker instances to finish. At that point, they had all exited their loops and stopped.
Congrats! We've now completed our project; we have a basic web server that uses a thread pool to respond asynchronously. We're able to perform a graceful shutdown of the server, which cleans up all the threads in the pool. See https://www.nostarch.com/Rust2021 to download the full code for this chapter for reference.
We could do more here! If you want to continue enhancing this project, here are some ideas:
- Add more documentation to
ThreadPool and its public methods.
- Add tests of the library's functionality.
- Change calls to
unwrap to more robust error handling.
- Use
ThreadPool to perform some task other than serving web requests.
- Find a thread pool crate on https://crates.io and implement a similar web server using the crate instead. Then compare its API and robustness to the thread pool we implemented.
