Shared State Concurrency
While message passing is a fine way of dealing with concurrency, it’s not the only one. Consider this slogan again:
Do not communicate by sharing memory; instead, share memory by communicating.
What would “communicate by sharing memory” look like? And moreover, why would message passing enthusiasts dislike it, and dislike it enough to invert it entirely?
Remember how channels are sort of like single ownership? Shared memory concurrency is sort of like multiple ownership: multiple threads can access the same memory location at the same time. As we saw with multiple ownership made possible by smart pointers in Chapter 15, multiple ownership can add additional complexity, since we need to manage these different owners somehow.
Rust’s type system and ownership can help a lot here in getting this management correct, though. For an example, let’s look at one of the more common concurrency primitives for shared memory: mutexes.
Mutexes Allow Access to Data from One Thread at a Time
A mutex is a concurrency primitive for sharing memory. It’s short for “mutual exclusion”, that is, it only allows one thread to access some data at any given time. Mutexes have a reputation for being hard to use, since there’s a lot you have to remember:
- You have to remember to attempt to acquire the lock before using the data.
- Once you’re done with the data that’s being guarded by the mutex, you have to remember to unlock the data so that other threads can acquire the lock.
For a real-world example of a mutex, imagine a panel discussion at a conference where there is only one microphone. Before a panelist may speak, they have to ask or signal that they would like to use the microphone. Once they get the microphone, they may talk for as long as they would like, then hand the microphone to the next panelist who would like to speak. It would be rude for a panelist to start shouting without having the microphone or to steal the microphone before another panelist was finished. No one else would be able to speak if a panelist forgot to hand the microphone to the next person when they finished using it. If the management of the shared microphone went wrong in any of these ways, the panel would not work as planned!
Management of mutexes can be incredibly tricky to get right, and that’s why so many people are enthusiastic about channels. However, in Rust, we can’t get locking and unlocking wrong, thanks to the type system and ownership.
The API of Mutex<T>
Let’s look at an example of using a mutex in Listing 16-12, without involving multiple threads for the moment:
Filename: src/main.rs
use std::sync::Mutex;
fn main() {
let m = Mutex::new(5);
{
let mut num = m.lock().unwrap();
*num = 6;
}
println!("m = {:?}", m);
}
Listing 16-12: Exploring the API of Mutex<T> in a
single threaded context for simplicity
Like many types, we create a Mutex<T> through an associated function named
new. To access the data inside the mutex, we use the lock method to acquire
the lock. This call will block until it’s our turn to have the lock. This call
can fail if another thread was holding the lock and then that thread panicked.
In a similar way as we did in Listing 16-6 in the last section, we’re using
unwrap() for now, rather than better error handling. See Chapter 9 for better
tools.
Once we have acquired the lock, we can treat the return value, named num in
this case, as a mutable reference to the data inside. The type system is how
Rust ensures that we acquire a lock before using this value: Mutex<i32> is
not an i32, so we must acquire the lock in order to be able to use the
i32 value. We can’t forget; the type system won’t let us do otherwise.
As you may have suspected, Mutex<T> is a smart pointer. Well, more
accurately, the call to lock returns a smart pointer called MutexGuard.
This smart pointer implements Deref to point at our inner data, similar to
the other smart pointers we saw in Chapter 15. In addition, MutexGuard has a
Drop implementation that releases the lock. This way, we can’t forget to
release the lock. It happens for us automatically when the MutexGuard goes
out of scope, which it does at the end of the inner scope in Listing 16-12. We
can print out the mutex value and see that we were able to change the inner
i32 to 6.
Sharing a Mutex<T> Between Multiple Threads
Let’s now try to share a value between multiple threads using Mutex<T>. We’ll
spin up ten threads, and have them each increment a counter value by 1 so that
the counter goes from 0 to 10. Note that the next few examples will have
compiler errors, and we’re going to use those errors to learn more about using
Mutex<T> and how Rust helps us use it correctly. Listing 16-13 has our
starting example:
Filename: src/main.rs
use std::sync::Mutex;
use std::thread;
fn main() {
let counter = Mutex::new(0);
let mut handles = vec![];
for _ in 0..10 {
let handle = thread::spawn(|| {
let mut num = counter.lock().unwrap();
*num += 1;
});
handles.push(handle);
}
for handle in handles {
handle.join().unwrap();
}
println!("Result: {}", *counter.lock().unwrap());
}
Listing 16-13: The start of a program having 10 threads
each increment a counter guarded by a Mutex<T>
We’re creating a counter variable to hold an i32 inside a Mutex<T>, like
we did in Listing 16-12. Next, we’re creating 10 threads by mapping over a
range of numbers. We use thread::spawn and give all the threads the same
closure: they’re each going to acquire a lock on the Mutex<T> by calling the
lock method and then add 1 to the value in the mutex. When a thread finishes
running its closure, num will go out of scope and release the lock so that
another thread can acquire it.
In the main thread, we’re collecting all the join handles like we did in
Listing 16-2, and then calling join on each of them to make sure all the
threads finish. At that point, the main thread will acquire the lock and print
out the result of this program.
We hinted that this example won’t compile, let’s find out why!
error[E0373]: closure may outlive the current function, but it borrows
`counter`, which is owned by the current function
-->
|
9 | let handle = thread::spawn(|| {
| ^^ may outlive borrowed value `counter`
10 | let mut num = counter.lock().unwrap();
| ------- `counter` is borrowed here
|
help: to force the closure to take ownership of `counter` (and any other
referenced variables), use the `move` keyword, as shown:
| let handle = thread::spawn(move || {
This is similar to the problem we solved in Listing 16-5. Given that we spin up
multiple threads, Rust can’t know how long the threads will run and whether
counter will still be valid when each thread tries to borrow it. The help
message has a reminder for how to solve this: we can use move to give
ownership to each thread. Let’s try it by making this change to the closure:
thread::spawn(move || {
And trying to compile again. We’ll get different errors this time!
error[E0382]: capture of moved value: `counter`
-->
|
9 | let handle = thread::spawn(move || {
| ------- value moved (into closure) here
10 | let mut num = counter.lock().unwrap();
| ^^^^^^^ value captured here after move
|
= note: move occurs because `counter` has type `std::sync::Mutex<i32>`,
which does not implement the `Copy` trait
error[E0382]: use of moved value: `counter`
-->
|
9 | let handle = thread::spawn(move || {
| ------- value moved (into closure) here
...
21 | println!("Result: {}", *counter.lock().unwrap());
| ^^^^^^^ value used here after move
|
= note: move occurs because `counter` has type `std::sync::Mutex<i32>`,
which does not implement the `Copy` trait
error: aborting due to 2 previous errors
move didn’t fix this program like it fixed Listing 16-5. Why not? This error
message is a little confusing to read, because it’s saying that the counter
value is moved into the closure, then is captured when we call lock. That
sounds like what we wanted, but it’s not allowed.
Let’s reason this out. Instead of making 10 threads in a for loop, let’s just
make two threads without a loop and see what happens then. Replace the first
for loop in Listing 16-13 with this code instead:
let handle = thread::spawn(move || {
let mut num = counter.lock().unwrap();
*num += 1;
});
handles.push(handle);
let handle2 = thread::spawn(move || {
let mut num2 = counter.lock().unwrap();
*num2 += 1;
});
handles.push(handle2);
Here we’re making 2 threads, and we changed the variable names used with the
second thread to handle2 and num2. We’re simplifying our example for the
moment to see if we can understand the error message we’re getting. This time,
compiling gives us:
error[E0382]: capture of moved value: `counter`
-->
|
8 | let handle = thread::spawn(move || {
| ------- value moved (into closure) here
...
16 | let mut num2 = counter.lock().unwrap();
| ^^^^^^^ value captured here after move
|
= note: move occurs because `counter` has type `std::sync::Mutex<i32>`,
which does not implement the `Copy` trait
error[E0382]: use of moved value: `counter`
-->
|
8 | let handle = thread::spawn(move || {
| ------- value moved (into closure) here
...
26 | println!("Result: {}", *counter.lock().unwrap());
| ^^^^^^^ value used here after move
|
= note: move occurs because `counter` has type `std::sync::Mutex<i32>`,
which does not implement the `Copy` trait
error: aborting due to 2 previous errors
Aha! In the first error message, Rust is showing us that counter is moved
into the closure for the thread that goes with handle. That move is
preventing us from capturing counter when we try to call lock on it and
store the result in num2, which is in the second thread! So Rust is telling
us that we can’t move ownership of counter into multiple threads. This was
hard to see before since we were creating multiple threads in a loop, and Rust
can’t point to different threads in different iterations of the loop.
Multiple Ownership with Multiple Threads
In Chapter 15, we were able to have multiple ownership of a value by using the
smart pointer Rc<T> to create a reference-counted value. We mentioned in
Chapter 15 that Rc<T> was only for single-threaded contexts, but let’s try
using Rc<T> in this case anyway and see what happens. We’ll wrap the
Mutex<T> in Rc<T> in Listing 16-14, and clone the Rc<T> before moving
ownership to the thread. We’ll switch back to the for loop for creating the
threads, and keep the move keyword with the closure:
Filename: src/main.rs
use std::rc::Rc;
use std::sync::Mutex;
use std::thread;
fn main() {
let counter = Rc::new(Mutex::new(0));
let mut handles = vec![];
for _ in 0..10 {
let counter = Rc::clone(&counter);
let handle = thread::spawn(move || {
let mut num = counter.lock().unwrap();
*num += 1;
});
handles.push(handle);
}
for handle in handles {
handle.join().unwrap();
}
println!("Result: {}", *counter.lock().unwrap());
}
Listing 16-14: Attempting to use Rc<T> to allow
multiple threads to own the Mutex<T>
Once again, we compile and get... different errors! The compiler is teaching us a lot!
error[E0277]: the trait bound `std::rc::Rc<std::sync::Mutex<i32>>:
std::marker::Send` is not satisfied
-->
|
11 | let handle = thread::spawn(move || {
| ^^^^^^^^^^^^^ the trait `std::marker::Send` is not
implemented for `std::rc::Rc<std::sync::Mutex<i32>>`
|
= note: `std::rc::Rc<std::sync::Mutex<i32>>` cannot be sent between threads
safely
= note: required because it appears within the type
`[closure@src/main.rs:11:36: 15:10
counter:std::rc::Rc<std::sync::Mutex<i32>>]`
= note: required by `std::thread::spawn`
Wow, that’s quite wordy! Some important parts to pick out: the first note says
Rc<Mutex<i32>> cannot be sent between threads safely. The reason for this is
in the error message, which, once distilled, says the trait bound Send is not
satisfied. We’re going to talk about Send in the next section; it’s one of
the traits that ensures the types we use with threads are meant for use in
concurrent situations.
Unfortunately, Rc<T> is not safe to share across threads. When Rc<T>
manages the reference count, it has to add to the count for each call to
clone and subtract from the count when each clone is dropped. Rc<T> doesn’t
use any concurrency primitives to make sure that changes to the count happen in
an operation that couldn’t be interrupted by another thread. This could lead to
subtle bugs where the counts are wrong, which could lead to memory leaks or
dropping a value before we’re done with it. So what if we had a type that was
exactly like Rc<T>, but made changes to the reference count in a thread-safe
way?
Atomic Reference Counting with Arc<T>
If you thought that question sounded like a leading one, you’d be right. There
is a type like Rc<T> that’s safe to use in concurrent situations: Arc<T>.
The ‘a’ stands for atomic, so it’s an atomically reference counted type.
Atomics are an additional kind of concurrency primitive that we won’t cover
here; see the standard library documentation for std::sync::atomic for more
details. The gist of it is this: atomics work like primitive types, but are
safe to share across threads.
Why aren’t all primitive types atomic, and why aren’t all standard library
types implemented to use Arc<T> by default? Thread safety comes with a
performance penalty that we only want to pay when we need it. If we’re only
doing operations on values within a single thread, our code can run faster
since it doesn’t need the guarantees that atomics give us.
Back to our example: Arc<T> and Rc<T> are identical except for the atomic
internals of Arc<T>. Their API is the same, so we can change the use line
and the call to new. The code in Listing 16-15 will finally compile and run:
Filename: src/main.rs
use std::sync::{Mutex, Arc};
use std::thread;
fn main() {
let counter = Arc::new(Mutex::new(0));
let mut handles = vec![];
for _ in 0..10 {
let counter = Arc::clone(&counter);
let handle = thread::spawn(move || {
let mut num = counter.lock().unwrap();
*num += 1;
});
handles.push(handle);
}
for handle in handles {
handle.join().unwrap();
}
println!("Result: {}", *counter.lock().unwrap());
}
Listing 16-15: Using an Arc<T> to wrap the Mutex<T>
to be able to share ownership across multiple threads
This will print:
Result: 10
We did it! We counted from 0 to 10, which may not seem very impressive, but we
learned a lot about Mutex<T> and thread safety along the way! The structure
that we’ve built in this example could be used to do more complicated
operations than just incrementing a counter. Calculations that can be divided
up into independent parts could be split across threads in this way, and we can
use a Mutex<T> to allow each thread to update the final result with its part.
You may have noticed that, since counter is immutable but we could get a
mutable reference to the value inside it, this means Mutex<T> provides
interior mutability, like the Cell family does. In the same way that we used
RefCell<T> in Chapter 15 to be able to mutate contents inside an Rc<T>, we
use Mutex<T> to be able to mutate contents inside of an Arc<T>.
Recall that Rc<T> did not prevent every possible problem: we also talked
about the possibility of creating reference cycles where two Rc<T> values
refer to each other, which would cause a memory leak. We have a similar problem
with Mutex<T> that Rust also doesn’t prevent: deadlocks. A deadlock is a
situation in which an operation needs to lock two resources, and two threads
have each acquired one of the locks and will now wait for each other forever.
If you’re interested in this topic, try creating a Rust program that has a
deadlock, then research deadlock mitigation strategies that apply to the use of
mutexes in any language and try implementing them in Rust. The standard library
API documentation for Mutex<T> and MutexGuard will have useful information.
Rust’s type system and ownership has made sure that our threads have exclusive access to the shared value when they’re updating it, so the threads won’t overwrite each other’s answers in unpredictable ways. It took us a while to work with the compiler to get everything right, but we’ve saved future time that might be spent trying to reproduce subtly incorrect scenarios that only happen when the threads run in a particular order.
Let’s round out this chapter by talking about the Send and Sync traits and
how we could use them with custom types.