## Turning Our Single-Threaded Server into a Multithreaded Server

Right now, the server will process each request in turn, meaning it won’t process a second connection until the first is finished processing. If the server received more and more requests, this serial execution would be less and less optimal. If the server receives a request that takes a long time to process, subsequent requests will have to wait until the long request is finished, even if the new requests can be processed quickly. We’ll need to fix this, but first, we’ll look at the problem in action.

### Simulating a Slow Request in the Current Server Implementation

We’ll look at how a slow-processing request can affect other requests made to our current server implementation. Listing 20-10 implements handling a request to /sleep with a simulated slow response that will cause the server to sleep for 5 seconds before responding.

Filename: src/main.rs

    #![allow(unused_variables)]
    fn main() {
    use std::thread;
    use std::time::Duration;
    use std::io::prelude::*;
    use std::net::TcpStream;
    use std::fs::File;
    // --snip--

    fn handle_connection(mut stream: TcpStream) {
        let mut buffer = [0; 512];
        stream.read(&mut buffer).unwrap();
        // --snip--

        let get = b"GET / HTTP/1.1\r\n";
        let sleep = b"GET /sleep HTTP/1.1\r\n";

        let (status_line, filename) = if buffer.starts_with(get) {
            ("HTTP/1.1 200 OK\r\n\r\n", "hello.html")
        } else if buffer.starts_with(sleep) {
            thread::sleep(Duration::from_secs(5));
            ("HTTP/1.1 200 OK\r\n\r\n", "hello.html")
        } else {
            ("HTTP/1.1 404 NOT FOUND\r\n\r\n", "404.html")
        };

        // --snip--
    }
    }

Listing 20-10: Simulating a slow request by recognizing /sleep and sleeping for 5 seconds

This code is a bit messy, but it’s good enough for simulation purposes. We created a second request `sleep`, whose data our server recognizes. We added an `else if` after the `if` block to check for the request to /sleep. When that request is received, the server will sleep for 5 seconds before rendering the successful HTML page.

You can see how primitive our server is: real libraries would handle the recognition of multiple requests in a much less verbose way!

Start the server using `cargo run`. Then open two browser windows: one for http://127.0.0.1:7878/ and the other for http://127.0.0.1:7878/sleep. If you enter the / URI a few times, as before, you’ll see it respond quickly. But if you enter /sleep and then load /, you’ll see that / waits until `sleep` has slept for its full 5 seconds before loading.

There are multiple ways we could change how our web server works to avoid having more requests back up behind a slow request; the one we’ll implement is a thread pool.

### Improving Throughput with a Thread Pool

A thread pool is a group of spawned threads that are waiting and ready to handle a task. When the program receives a new task, it assigns one of the threads in the pool to the task, and that thread will process the task. The remaining threads in the pool are available to handle any other tasks that come in while the first thread is processing. When the first thread is done processing its task, it’s returned to the pool of idle threads, ready to handle a new task. A thread pool allows you to process connections concurrently, increasing the throughput of your server.

We’ll limit the number of threads in the pool to a small number to protect us from Denial of Service (DoS) attacks; if we had our program create a new thread for each request as it came in, someone making 10 million requests to our server could create havoc by using up all our server’s resources and grinding the processing of requests to a halt.

Rather than spawning unlimited threads, we’ll have a fixed number of threads waiting in the pool. As requests come in, they’ll be sent to the pool for processing. The pool will maintain a queue of incoming requests. Each of the threads in the pool will pop off a request from this queue, handle the request, and then ask the queue for another request. With this design, we can process `N` requests concurrently, where `N` is the number of threads. If each thread is responding to a long-running request, subsequent requests can still back up in the queue, but we’ve increased the number of long-running requests we can handle before reaching that point.

This technique is just one of many ways to improve the throughput of a web server. Other options you might explore are the fork/join model and the single-threaded async I/O model. If you’re interested in this topic, you can read more about other solutions and try to implement them in Rust; with a low-level language like Rust, all of these options are possible.

Before we begin implementing a thread pool, let’s talk about what using the pool should look like. When you’re trying to design code, writing the client interface first can help guide your design. Write the API of the code so it’s structured in the way you want to call it; then implement the functionality within that structure rather than implementing the functionality and then designing the public API.

Similar to how we used test-driven development in the project in Chapter 12, we’ll use compiler-driven development here. We’ll write the code that calls the functions we want, and then we’ll look at errors from the compiler to determine what we should change next to get the code to work.

#### Code Structure If We Could Spawn a Thread for Each Request

First, let’s explore how our code might look if it did create a new thread for every connection. As mentioned earlier, this isn’t our final plan due to the problems with potentially spawning an unlimited number of threads, but it is a starting point. Listing 20-11 shows the changes to make to `main` to spawn a new thread to handle each stream within the `for` loop.

Filename: src/main.rs

    use std::thread;
    use std::io::prelude::*;
    use std::net::TcpListener;
    use std::net::TcpStream;

    fn main() {
        let listener = TcpListener::bind("127.0.0.1:7878").unwrap();

        for stream in listener.incoming() {
            let stream = stream.unwrap();

            thread::spawn(|| {
                handle_connection(stream);
            });
        }
    }
    fn handle_connection(mut stream: TcpStream) {}

Listing 20-11: Spawning a new thread for each stream

As you learned in Chapter 16, `thread::spawn` will create a new thread and then run the code in the closure in the new thread. If you run this code and load /sleep in your browser, then / in two more browser tabs, you’ll indeed see that the requests to / don’t have to wait for /sleep to finish. But as we mentioned, this will eventually overwhelm the system because you’d be making new threads without any limit.

#### Creating a Similar Interface for a Finite Number of Threads

We want our thread pool to work in a similar, familiar way so switching from threads to a thread pool doesn’t require large changes to the code that uses our API. Listing 20-12 shows the hypothetical interface for a `ThreadPool` struct we want to use instead of `thread::spawn`.

Filename: src/main.rs

    use std::thread;
    use std::io::prelude::*;
    use std::net::TcpListener;
    use std::net::TcpStream;
    struct ThreadPool;
    impl ThreadPool {
       fn new(size: u32) -> ThreadPool { ThreadPool }
       fn execute<F>(&self, f: F)
           where F: FnOnce() + Send + 'static {}
    }

    fn main() {
        let listener = TcpListener::bind("127.0.0.1:7878").unwrap();
        let pool = ThreadPool::new(4);

        for stream in listener.incoming() {
            let stream = stream.unwrap();

            pool.execute(|| {
                handle_connection(stream);
            });
        }
    }
    fn handle_connection(mut stream: TcpStream) {}

Listing 20-12: Our ideal `ThreadPool` interface

We use `ThreadPool::new` to create a new thread pool with a configurable number of threads, in this case four. Then, in the `for` loop, `pool.execute` has a similar interface as `thread::spawn` in that it takes a closure the pool should run for each stream. We need to implement `pool.execute` so it takes the closure and gives it to a thread in the pool to run. This code won’t yet compile, but we’ll try so the compiler can guide us in how to fix it.

#### Building the `ThreadPool` Struct Using Compiler Driven Development

Make the changes in Listing 20-12 to src/main.rs, and then let’s use the compiler errors from `cargo check` to drive our development. Here is the first error we get:

    $ cargo check
       Compiling hello v0.1.0 (file:///projects/hello)
    error[E0433]: failed to resolve. Use of undeclared type or module `ThreadPool`
      --> src\main.rs:10:16
       |
    10 |     let pool = ThreadPool::new(4);
       |                ^^^^^^^^^^^^^^^ Use of undeclared type or module
       `ThreadPool`

    error: aborting due to previous error

Great! This error tells us we need a `ThreadPool` type or module, so we’ll build one now. Our `ThreadPool` implementation will be independent of the kind of work our web server is doing. So, let’s switch the `hello` crate from a binary crate to a library crate to hold our `ThreadPool` implementation. After we change to a library crate, we could also use the separate thread pool library for any work we want to do using a thread pool, not just for serving web requests.

Create a src/lib.rs that contains the following, which is the simplest definition of a `ThreadPool` struct that we can have for now:

Filename: src/lib.rs

    #![allow(unused_variables)]
    fn main() {
    pub struct ThreadPool;
    }

Then create a new directory, src/bin, and move the binary crate rooted in src/main.rs into src/bin/main.rs. Doing so will make the library crate the primary crate in the hello directory; we can still run the binary in src/bin/main.rs using `cargo run`. After moving the main.rs file, edit it to bring the library crate in and bring `ThreadPool` into scope by adding the following code to the top of src/bin/main.rs:

Filename: src/bin/main.rs

    use hello::ThreadPool;

This code still won’t work, but let’s check it again to get the next error that we need to address:

    $ cargo check
       Compiling hello v0.1.0 (file:///projects/hello)
    error[E0599]: no function or associated item named `new` found for type
    `hello::ThreadPool` in the current scope
     --> src/bin/main.rs:13:16
       |
    13 |     let pool = ThreadPool::new(4);
       |                ^^^^^^^^^^^^^^^ function or associated item not found in
       `hello::ThreadPool`

This error indicates that next we need to create an associated function named `new` for `ThreadPool`. We also know that `new` needs to have one parameter that can accept `4` as an argument and should return a `ThreadPool` instance. Let’s implement the simplest `new` function that will have those characteristics:

Filename: src/lib.rs

    #![allow(unused_variables)]
    fn main() {
    pub struct ThreadPool;

    impl ThreadPool {
        pub fn new(size: usize) -> ThreadPool {
            ThreadPool
        }
    }
    }

We chose `usize` as the type of the `size` parameter, because we know that a negative number of threads doesn’t make any sense. We also know we’ll use this 4 as the number of elements in a collection of threads, which is what the `usize` type is for, as discussed in the “Integer Types” section of Chapter 3.

Let’s check the code again:

    $ cargo check
       Compiling hello v0.1.0 (file:///projects/hello)
    warning: unused variable: `size`
     --> src/lib.rs:4:16
      |
    4 |     pub fn new(size: usize) -> ThreadPool {
      |                ^^^^
      |
      = note: #[warn(unused_variables)] on by default
      = note: to avoid this warning, consider using `_size` instead

    error[E0599]: no method named `execute` found for type `hello::ThreadPool` in the current scope
      --> src/bin/main.rs:18:14
       |
    18 |         pool.execute(|| {
       |              ^^^^^^^

Now we get a warning and an error. Ignoring the warning for a moment, the error occurs because we don’t have an `execute` method on `ThreadPool`. Recall from the “Creating a Similar Interface for a Finite Number of Threads” section that we decided our thread pool should have an interface similar to `thread::spawn`. In addition, we’ll implement the `execute` function so it takes the closure it’s given and gives it to an idle thread in the pool to run.

We’ll define the `execute` method on `ThreadPool` to take a closure as a parameter. Recall from the “Storing Closures Using Generic Parameters and the `Fn` Traits” section in Chapter 13 that we can take closures as parameters with three different traits: `Fn`, `FnMut`, and `FnOnce`. We need to decide which kind of closure to use here. We know we’ll end up doing something similar to the standard library `thread::spawn` implementation, so we can look at what bounds the signature of `thread::spawn` has on its parameter. The documentation shows us the following:

    pub fn spawn<F, T>(f: F) -> JoinHandle<T>
        where
            F: FnOnce() -> T + Send + 'static,
            T: Send + 'static

The `F` type parameter is the one we’re concerned with here; the `T` type parameter is related to the return value, and we’re not concerned with that. We can see that `spawn` uses `FnOnce` as the trait bound on `F`. This is probably what we want as well, because we’ll eventually pass the argument we get in `execute` to `spawn`. We can be further confident that `FnOnce` is the trait we want to use because the thread for running a request will only execute that request’s closure one time, which matches the `Once` in `FnOnce`.

The `F` type parameter also has the trait bound `Send` and the lifetime bound `'static`, which are useful in our situation: we need `Send` to transfer the closure from one thread to another and `'static` because we don’t know how long the thread will take to execute. Let’s create an `execute` method on `ThreadPool` that will take a generic parameter of type `F` with these bounds:

Filename: src/lib.rs

    #![allow(unused_variables)]
    fn main() {
    pub struct ThreadPool;
    impl ThreadPool {
        // --snip--

        pub fn execute<F>(&self, f: F)
            where
                F: FnOnce() + Send + 'static
        {

        }
    }
    }

We still use the `()` after `FnOnce` because this `FnOnce` represents a closure that takes no parameters and returns the unit type `()`. Just like function definitions, the return type can be omitted from the signature, but even if we have no parameters, we still need the parentheses.

Again, this is the simplest implementation of the `execute` method: it does nothing, but we’re trying only to make our code compile. Let’s check it again:

    $ cargo check
       Compiling hello v0.1.0 (file:///projects/hello)
    warning: unused variable: `size`
     --> src/lib.rs:4:16
      |
    4 |     pub fn new(size: usize) -> ThreadPool {
      |                ^^^^
      |
      = note: #[warn(unused_variables)] on by default
      = note: to avoid this warning, consider using `_size` instead

    warning: unused variable: `f`
     --> src/lib.rs:8:30
      |
    8 |     pub fn execute<F>(&self, f: F)
      |                              ^
      |
      = note: to avoid this warning, consider using `_f` instead

We’re receiving only warnings now, which means it compiles! But note that if you try `cargo run` and make a request in the browser, you’ll see the errors in the browser that we saw at the beginning of the chapter. Our library isn’t actually calling the closure passed to `execute` yet!

> Note: A saying you might hear about languages with strict compilers, such as Haskell and Rust, is “if the code compiles, it works.” But this saying is not universally true. Our project compiles, but it does absolutely nothing! If we were building a real, complete project, this would be a good time to start writing unit tests to check that the code compiles and has the behavior we want.

#### Validating the Number of Threads in `new`

We’ll continue to get warnings because we aren’t doing anything with the parameters to `new` and `execute`. Let’s implement the bodies of these functions with the behavior we want. To start, let’s think about `new`. Earlier we chose an unsigned type for the `size` parameter, because a pool with a negative number of threads makes no sense. However, a pool with zero threads also makes no sense, yet zero is a perfectly valid `usize`. We’ll add code to check that `size` is greater than zero before we return a `ThreadPool` instance and have the program panic if it receives a zero by using the `assert!` macro, as shown in Listing 20-13.

Filename: src/lib.rs

    #![allow(unused_variables)]
    fn main() {
    pub struct ThreadPool;
    impl ThreadPool {
        /// Create a new ThreadPool.
        ///
        /// The size is the number of threads in the pool.
        ///
        /// # Panics
        ///
        /// The `new` function will panic if the size is zero.
        pub fn new(size: usize) -> ThreadPool {
            assert!(size > 0);

            ThreadPool
        }

        // --snip--
    }
    }

Listing 20-13: Implementing `ThreadPool::new` to panic if `size` is zero

We’ve added some documentation for our `ThreadPool` with doc comments. Note that we followed good documentation practices by adding a section that calls out the situations in which our function can panic, as discussed in Chapter 14. Try running `cargo doc --open` and clicking the `ThreadPool` struct to see what the generated docs for `new` look like!

Instead of adding the `assert!` macro as we’ve done here, we could make `new` return a `Result` like we did with `Config::new` in the I/O project in Listing 12-9. But we’ve decided in this case that trying to create a thread pool without any threads should be an unrecoverable error. If you’re feeling ambitious, try to write a version of `new` with the following signature to compare both versions:

    pub fn new(size: usize) -> Result<ThreadPool, PoolCreationError> {

#### Creating Space to Store the Threads

Now that we have a way to know we have a valid number of threads to store in the pool, we can create those threads and store them in the `ThreadPool` struct before returning it. But how do we “store” a thread? Let’s take another look at the `thread::spawn` signature:

    pub fn spawn<F, T>(f: F) -> JoinHandle<T>
        where
            F: FnOnce() -> T + Send + 'static,
            T: Send + 'static

The `spawn` function returns a `JoinHandle<T>`, where `T` is the type that the closure returns. Let’s try using `JoinHandle` too and see what happens. In our case, the closures we’re passing to the thread pool will handle the connection and not return anything, so `T` will be the unit type `()`.

The code in Listing 20-14 will compile but doesn’t create any threads yet. We’ve changed the definition of `ThreadPool` to hold a vector of `thread::JoinHandle<()>` instances, initialized the vector with a capacity of `size`, set up a `for` loop that will run some code to create the threads, and returned a `ThreadPool` instance containing them.

Filename: src/lib.rs

    use std::thread;

    pub struct ThreadPool {
        threads: Vec<thread::JoinHandle<()>>,
    }

    impl ThreadPool {
        // --snip--
        pub fn new(size: usize) -> ThreadPool {
            assert!(size > 0);

            let mut threads = Vec::with_capacity(size);

            for _ in 0..size {
                // create some threads and store them in the vector
            }

            ThreadPool {
                threads
            }
        }

        // --snip--
    }

Listing 20-14: Creating a vector for `ThreadPool` to hold the threads

We’ve brought `std::thread` into scope in the library crate, because we’re using `thread::JoinHandle` as the type of the items in the vector in `ThreadPool`.

Once a valid size is received, our `ThreadPool` creates a new vector that can hold `size` items. We haven’t used the `with_capacity` function in this book yet, which performs the same task as `Vec::new` but with an important difference: it preallocates space in the vector. Because we know we need to store `size` elements in the vector, doing this allocation up front is slightly more efficient than using `Vec::new`, which resizes itself as elements are inserted.

When you run `cargo check` again, you’ll get a few more warnings, but it should succeed.

#### A `Worker` Struct Responsible for Sending Code from the `ThreadPool` to a Thread

We left a comment in the `for` loop in Listing 20-14 regarding the creation of threads. Here, we’ll look at how we actually create threads. The standard library provides `thread::spawn` as a way to create threads, and `thread::spawn` expects to get some code the thread should run as soon as the thread is created. However, in our case, we want to create the threads and have them wait for code that we’ll send later. The standard library’s implementation of threads doesn’t include any way to do that; we have to implement it manually.

We’ll implement this behavior by introducing a new data structure between the `ThreadPool` and the threads that will manage this new behavior. We’ll call this data structure `Worker`, which is a common term in pooling implementations. Think of people working in the kitchen at a restaurant: the workers wait until orders come in from customers, and then they’re responsible for taking those orders and filling them.

Instead of storing a vector of `JoinHandle<()>` instances in the thread pool, we’ll store instances of the `Worker` struct. Each `Worker` will store a single `JoinHandle<()>` instance. Then we’ll implement a method on `Worker` that will take a closure of code to run and send it to the already running thread for execution. We’ll also give each worker an `id` so we can distinguish between the different workers in the pool when logging or debugging.

Let’s make the following changes to what happens when we create a `ThreadPool`. We’ll implement the code that sends the closure to the thread after we have `Worker` set up in this way:

1. Define a `Worker` struct that holds an `id` and a `JoinHandle<()>`.
2. Change `ThreadPool` to hold a vector of `Worker` instances.
3. Define a `Worker::new` function that takes an `id` number and returns a `Worker` instance that holds the `id` and a thread spawned with an empty closure.
4. In `ThreadPool::new`, use the `for` loop counter to generate an `id`, create a new `Worker` with that `id`, and store the worker in the vector.

If you’re up for a challenge, try implementing these changes on your own before looking at the code in Listing 20-15.

Ready? Here is Listing 20-15 with one way to make the preceding modifications.

Filename: src/lib.rs

    #![allow(unused_variables)]
    fn main() {
    use std::thread;

    pub struct ThreadPool {
        workers: Vec<Worker>,
    }

    impl ThreadPool {
        // --snip--
        pub fn new(size: usize) -> ThreadPool {
            assert!(size > 0);

            let mut workers = Vec::with_capacity(size);

            for id in 0..size {
                workers.push(Worker::new(id));
            }

            ThreadPool {
                workers
            }
        }
        // --snip--
    }

    struct Worker {
        id: usize,
        thread: thread::JoinHandle<()>,
    }

    impl Worker {
        fn new(id: usize) -> Worker {
            let thread = thread::spawn(|| {});

            Worker {
                id,
                thread,
            }
        }
    }
    }

Listing 20-15: Modifying `ThreadPool` to hold `Worker` instances instead of holding threads directly

We’ve changed the name of the field on `ThreadPool` from `threads` to `workers` because it’s now holding `Worker` instances instead of `JoinHandle<()>` instances. We use the counter in the `for` loop as an argument to `Worker::new`, and we store each new `Worker` in the vector named `workers`.

External code (like our server in src/bin/main.rs) doesn’t need to know the implementation details regarding using a `Worker` struct within `ThreadPool`, so we make the `Worker` struct and its `new` function private. The `Worker::new` function uses the `id` we give it and stores a `JoinHandle<()>` instance that is created by spawning a new thread using an empty closure.

This code will compile and will store the number of `Worker` instances we specified as an argument to `ThreadPool::new`. But we’re still not processing the closure that we get in `execute`. Let’s look at how to do that next.

#### Sending Requests to Threads via Channels

Now we’ll tackle the problem that the closures given to `thread::spawn` do absolutely nothing. Currently, we get the closure we want to execute in the `execute` method. But we need to give `thread::spawn` a closure to run when we create each `Worker` during the creation of the `ThreadPool`.

We want the `Worker` structs that we just created to fetch code to run from a queue held in the `ThreadPool` and send that code to its thread to run.

In Chapter 16, you learned about channels—a simple way to communicate between two threads—that would be perfect for this use case. We’ll use a channel to function as the queue of jobs, and `execute` will send a job from the `ThreadPool` to the `Worker` instances, which will send the job to its thread. Here is the plan:

1. The `ThreadPool` will create a channel and hold on to the sending side of the channel.
2. Each `Worker` will hold on to the receiving side of the channel.
3. We’ll create a new `Job` struct that will hold the closures we want to send down the channel.
4. The `execute` method will send the job it wants to execute down the sending side of the channel.
5. In its thread, the `Worker` will loop over its receiving side of the channel and execute the closures of any jobs it receives.

Let’s start by creating a channel in `ThreadPool::new` and holding the sending side in the `ThreadPool` instance, as shown in Listing 20-16. The `Job` struct doesn’t hold anything for now but will be the type of item we’re sending down the channel.

Filename: src/lib.rs

    #![allow(unused_variables)]
    fn main() {
    use std::thread;
    // --snip--
    use std::sync::mpsc;

    pub struct ThreadPool {
        workers: Vec<Worker>,
        sender: mpsc::Sender<Job>,
    }

    struct Job;

    impl ThreadPool {
        // --snip--
        pub fn new(size: usize) -> ThreadPool {
            assert!(size > 0);

            let (sender, receiver) = mpsc::channel();

            let mut workers = Vec::with_capacity(size);

            for id in 0..size {
                workers.push(Worker::new(id));
            }

            ThreadPool {
                workers,
                sender,
            }
        }
        // --snip--
    }

    struct Worker {
        id: usize,
        thread: thread::JoinHandle<()>,
    }

    impl Worker {
        fn new(id: usize) -> Worker {
            let thread = thread::spawn(|| {});

            Worker {
                id,
                thread,
            }
        }
    }
    }

Listing 20-16: Modifying `ThreadPool` to store the sending end of a channel that sends `Job` instances

In `ThreadPool::new`, we create our new channel and have the pool hold the sending end. This will successfully compile, still with warnings.

Let’s try passing a receiving end of the channel into each worker as the thread pool creates the channel. We know we want to use the receiving end in the thread that the workers spawn, so we’ll reference the `receiver` parameter in the closure. The code in Listing 20-17 won’t quite compile yet.

Filename: src/lib.rs

    impl ThreadPool {
        // --snip--
        pub fn new(size: usize) -> ThreadPool {
            assert!(size > 0);

            let (sender, receiver) = mpsc::channel();

            let mut workers = Vec::with_capacity(size);

            for id in 0..size {
                workers.push(Worker::new(id, receiver));
            }

            ThreadPool {
                workers,
                sender,
            }
        }
        // --snip--
    }

    // --snip--

    impl Worker {
        fn new(id: usize, receiver: mpsc::Receiver<Job>) -> Worker {
            let thread = thread::spawn(|| {
                receiver;
            });

            Worker {
                id,
                thread,
            }
        }
    }

Listing 20-17: Passing the receiving end of the channel to the workers

We’ve made some small and straightforward changes: we pass the receiving end of the channel into `Worker::new`, and then we use it inside the closure.

When we try to check this code, we get this error:

    $ cargo check
       Compiling hello v0.1.0 (file:///projects/hello)
    error[E0382]: use of moved value: `receiver`
      --> src/lib.rs:27:42
       |
    27 |             workers.push(Worker::new(id, receiver));
       |                                          ^^^^^^^^ value moved here in
       previous iteration of loop
       |
       = note: move occurs because `receiver` has type
       `std::sync::mpsc::Receiver<Job>`, which does not implement the `Copy` trait

The code is trying to pass `receiver` to multiple `Worker` instances. This won’t work, as you’ll recall from Chapter 16: the channel implementation that Rust provides is multiple producer, single consumer. This means we can’t just clone the consuming end of the channel to fix this code. Even if we could, that is not the technique we would want to use; instead, we want to distribute the jobs across threads by sharing the single `receiver` among all the workers.

Additionally, taking a job off the channel queue involves mutating the `receiver`, so the threads need a safe way to share and modify `receiver`; otherwise, we might get race conditions (as covered in Chapter 16).

Recall the thread-safe smart pointers discussed in Chapter 16: to share ownership across multiple threads and allow the threads to mutate the value, we need to use `Arc<Mutex<T>>`. The `Arc` type will let multiple workers own the receiver, and `Mutex` will ensure that only one worker gets a job from the receiver at a time. Listing 20-18 shows the changes we need to make.

Filename: src/lib.rs

    #![allow(unused_variables)]
    fn main() {
    use std::thread;
    use std::sync::mpsc;
    use std::sync::Arc;
    use std::sync::Mutex;
    // --snip--

    pub struct ThreadPool {
        workers: Vec<Worker>,
        sender: mpsc::Sender<Job>,
    }
    struct Job;

    impl ThreadPool {
        // --snip--
        pub fn new(size: usize) -> ThreadPool {
            assert!(size > 0);

            let (sender, receiver) = mpsc::channel();

            let receiver = Arc::new(Mutex::new(receiver));

            let mut workers = Vec::with_capacity(size);

            for id in 0..size {
                workers.push(Worker::new(id, Arc::clone(&receiver)));
            }

            ThreadPool {
                workers,
                sender,
            }
        }

        // --snip--
    }

    struct Worker {
        id: usize,
        thread: thread::JoinHandle<()>,
    }

    impl Worker {
        fn new(id: usize, receiver: Arc<Mutex<mpsc::Receiver<Job>>>) -> Worker {
            // --snip--
            let thread = thread::spawn(|| {
               receiver;
            });

            Worker {
                id,
                thread,
            }
        }
    }
    }

Listing 20-18: Sharing the receiving end of the channel among the workers using `Arc` and `Mutex`

In `ThreadPool::new`, we put the receiving end of the channel in an `Arc` and a `Mutex`. For each new worker, we clone the `Arc` to bump the reference count so the workers can share ownership of the receiving end.

With these changes, the code compiles! We’re getting there!

#### Implementing the `execute` Method

Let’s finally implement the `execute` method on `ThreadPool`. We’ll also change `Job` from a struct to a type alias for a trait object that holds the type of closure that `execute` receives. As discussed in the “Creating Type Synonyms with Type Aliases” section of Chapter 19, type aliases allow us to make long types shorter. Look at Listing 20-19.

Filename: src/lib.rs

    #![allow(unused_variables)]
    fn main() {
    // --snip--
    pub struct ThreadPool {
        workers: Vec<Worker>,
        sender: mpsc::Sender<Job>,
    }
    use std::sync::mpsc;
    struct Worker {}

    type Job = Box<dyn FnOnce() + Send + 'static>;

    impl ThreadPool {
        // --snip--

        pub fn execute<F>(&self, f: F)
            where
                F: FnOnce() + Send + 'static
        {
            let job = Box::new(f);

            self.sender.send(job).unwrap();
        }
    }

    // --snip--
    }

Listing 20-19: Creating a `Job` type alias for a `Box` that holds each closure and then sending the job down the channel

After creating a new `Job` instance using the closure we get in `execute`, we send that job down the sending end of the channel. We’re calling `unwrap` on `send` for the case that sending fails. This might happen if, for example, we stop all our threads from executing, meaning the receiving end has stopped receiving new messages. At the moment, we can’t stop our threads from executing: our threads continue executing as long as the pool exists. The reason we use `unwrap` is that we know the failure case won’t happen, but the compiler doesn’t know that.

But we’re not quite done yet! In the worker, our closure being passed to `thread::spawn` still only references the receiving end of the channel. Instead, we need the closure to loop forever, asking the receiving end of the channel for a job and running the job when it gets one. Let’s make the change shown in Listing 20-20 to `Worker::new`.

Filename: src/lib.rs

    // --snip--

    impl Worker {
        fn new(id: usize, receiver: Arc<Mutex<mpsc::Receiver<Job>>>) -> Worker {
            let thread = thread::spawn(move || {
                loop {
                    let job = receiver.lock().unwrap().recv().unwrap();

                    println!("Worker {} got a job; executing.", id);

                    (*job)();
                }
            });

            Worker {
                id,
                thread,
            }
        }
    }

Listing 20-20: Receiving and executing the jobs in the worker’s thread

Here, we first call `lock` on the `receiver` to acquire the mutex, and then we call `unwrap` to panic on any errors. Acquiring a lock might fail if the mutex is in a poisoned state, which can happen if some other thread panicked while holding the lock rather than releasing the lock. In this situation, calling `unwrap` to have this thread panic is the correct action to take. Feel free to change this `unwrap` to an `expect` with an error message that is meaningful to you.

If we get the lock on the mutex, we call `recv` to receive a `Job` from the channel. A final `unwrap` moves past any errors here as well, which might occur if the thread holding the sending side of the channel has shut down, similar to how the `send` method returns `Err` if the receiving side shuts down.

The call to `recv` blocks, so if there is no job yet, the current thread will wait until a job becomes available. The `Mutex<T>` ensures that only one `Worker` thread at a time is trying to request a job.

Theoretically, this code should compile. Unfortunately, the Rust compiler isn’t perfect yet, and we get this error:

    error[E0161]: cannot move a value of type std::ops::FnOnce() +
    std::marker::Send: the size of std::ops::FnOnce() + std::marker::Send cannot be
    statically determined
      --> src/lib.rs:63:17
       |
    63 |                 (*job)();
       |                 ^^^^^^

This error is fairly cryptic because the problem is fairly cryptic. To call a `FnOnce` closure that is stored in a `Box<T>` (which is what our `Job` type alias is), the closure needs to move itself out of the `Box<T>` because the closure takes ownership of `self` when we call it. In general, Rust doesn’t allow us to move a value out of a `Box<T>` because Rust doesn’t know how big the value inside the `Box<T>` will be: recall in Chapter 15 that we used `Box<T>` precisely because we had something of an unknown size that we wanted to store in a `Box<T>` to get a value of a known size.

As you saw in Listing 17-15, we can write methods that use the syntax `self: Box<Self>`, which allows the method to take ownership of a `Self` value stored in a `Box<T>`. That’s exactly what we want to do here, but unfortunately Rust won’t let us: the part of Rust that implements behavior when a closure is called isn’t implemented using `self: Box<Self>`. So Rust doesn’t yet understand that it could use `self: Box<Self>` in this situation to take ownership of the closure and move the closure out of the `Box<T>`.

Rust is still a work in progress with places where the compiler could be improved, but in the future, the code in Listing 20-20 should work just fine. People just like you are working to fix this and other issues! After you’ve finished this book, we would love for you to join in.

But for now, let’s work around this problem using a handy trick. We can tell Rust explicitly that in this case we can take ownership of the value inside the `Box<T>` using `self: Box<Self>`; then, once we have ownership of the closure, we can call it. This involves defining a new trait `FnBox` with the method `call_box` that will use `self: Box<Self>` in its signature, defining `FnBox` for any type that implements `FnOnce()`, changing our type alias to use the new trait, and changing `Worker` to use the `call_box` method. These changes are shown in Listing 20-21.

Filename: src/lib.rs

    trait FnBox {
        fn call_box(self: Box<Self>);
    }

    impl<F: FnOnce()> FnBox for F {
        fn call_box(self: Box<F>) {
            (*self)()
        }
    }

    type Job = Box<dyn FnBox + Send + 'static>;

    // --snip--

    impl Worker {
        fn new(id: usize, receiver: Arc<Mutex<mpsc::Receiver<Job>>>) -> Worker {
            let thread = thread::spawn(move || {
                loop {
                    let job = receiver.lock().unwrap().recv().unwrap();

                    println!("Worker {} got a job; executing.", id);

                    job.call_box();
                }
            });

            Worker {
                id,
                thread,
            }
        }
    }

Listing 20-21: Adding a new trait `FnBox` to work around the current limitations of `Box<FnOnce()>`

First, we create a new trait named `FnBox`. This trait has the one method `call_box`, which is similar to the `call` methods on the other `Fn*` traits except that it takes `self: Box<Self>` to take ownership of `self` and move the value out of the `Box<T>`.

Next, we implement the `FnBox` trait for any type `F` that implements the `FnOnce()` trait. Effectively, this means that any `FnOnce()` closures can use our `call_box` method. The implementation of `call_box` uses `(*self)()` to move the closure out of the `Box<T>` and call the closure.

We now need our `Job` type alias to be a `Box` of anything that implements our new trait `FnBox`. This will allow us to use `call_box` in `Worker` when we get a `Job` value instead of invoking the closure directly. Implementing the `FnBox` trait for any `FnOnce()` closure means we don’t have to change anything about the actual values we’re sending down the channel. Now Rust is able to recognize that what we want to do is fine.

This trick is very sneaky and complicated. Don’t worry if it doesn’t make perfect sense; someday, it will be completely unnecessary.

With the implementation of this trick, our thread pool is in a working state! Give it a `cargo run` and make some requests:

    $ cargo run
       Compiling hello v0.1.0 (file:///projects/hello)
    warning: field is never used: `workers`
     --> src/lib.rs:7:5
      |
    7 |     workers: Vec<Worker>,
      |     ^^^^^^^^^^^^^^^^^^^^
      |
      = note: #[warn(dead_code)] on by default

    warning: field is never used: `id`
      --> src/lib.rs:61:5
       |
    61 |     id: usize,
       |     ^^^^^^^^^
       |
       = note: #[warn(dead_code)] on by default

    warning: field is never used: `thread`
      --> src/lib.rs:62:5
       |
    62 |     thread: thread::JoinHandle<()>,
       |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
       |
       = note: #[warn(dead_code)] on by default

        Finished dev [unoptimized + debuginfo] target(s) in 0.99 secs
         Running `target/debug/hello`
    Worker 0 got a job; executing.
    Worker 2 got a job; executing.
    Worker 1 got a job; executing.
    Worker 3 got a job; executing.
    Worker 0 got a job; executing.
    Worker 2 got a job; executing.
    Worker 1 got a job; executing.
    Worker 3 got a job; executing.
    Worker 0 got a job; executing.
    Worker 2 got a job; executing.

Success! We now have a thread pool that executes connections asynchronously. There are never more than four threads created, so our system won’t get overloaded if the server receives a lot of requests. If we make a request to /sleep, the server will be able to serve other requests by having another thread run them.

> Note: if you open /sleep in multiple browser windows simultaneously, they might load one at a time in 5 second intervals. Some web browsers execute multiple instances of the same request sequentially for caching reasons. This limitation is not caused by our web server.

After learning about the `while let` loop in Chapter 18, you might be wondering why we didn’t write the worker thread code as shown in Listing 20-22.

Filename: src/lib.rs

    // --snip--

    impl Worker {
        fn new(id: usize, receiver: Arc<Mutex<mpsc::Receiver<Job>>>) -> Worker {
            let thread = thread::spawn(move || {
                while let Ok(job) = receiver.lock().unwrap().recv() {
                    println!("Worker {} got a job; executing.", id);

                    job.call_box();
                }
            });

            Worker {
                id,
                thread,
            }
        }
    }

Listing 20-22: An alternative implementation of `Worker::new` using `while let`

This code compiles and runs but doesn’t result in the desired threading behavior: a slow request will still cause other requests to wait to be processed. The reason is somewhat subtle: the `Mutex` struct has no public `unlock` method because the ownership of the lock is based on the lifetime of the `MutexGuard<T>` within the `LockResult<MutexGuard<T>>` that the `lock` method returns. At compile time, the borrow checker can then enforce the rule that a resource guarded by a `Mutex` cannot be accessed unless we hold the lock. But this implementation can also result in the lock being held longer than intended if we don’t think carefully about the lifetime of the `MutexGuard<T>`. Because the values in the `while` expression remain in scope for the duration of the block, the lock remains held for the duration of the call to `job.call_box()`, meaning other workers cannot receive jobs.

By using `loop` instead and acquiring the lock and a job within the block rather than outside it, the `MutexGuard` returned from the `lock` method is dropped as soon as the `let job` statement ends. This ensures that the lock is held during the call to `recv`, but it is released before the call to `job.call_box()`, allowing multiple requests to be serviced concurrently.