Interior mutability in Rust, part 2: thread safety

Key takeaways We can have thread-safe interior mutability through Mutex , RwLock and the various Atomic* types in std::sync

, and the various types in Mutex allows only one thread at a time, has no direct thread-unsafe counterpart, but can be thought of as only giving &mut T references

allows only one thread at a time, has no direct thread-unsafe counterpart, but can be thought of as only giving references RwLock is equivalent to RefCell , and also allows multiple readers or one writer

is equivalent to , and also allows multiple readers or one writer The Atomic types are equivalent to Cell

types are equivalent to std::sync::Arc is the thread-safe version of std::rc::Rc , necessary to share references among threads

is the thread-safe version of , necessary to share references among threads These thread-safe types have additional run-time cost compared to their unsynchronized counterparts

In Rust, we lock/protect data, not code

This article is part of a series about interior mutability in Rust. You can read part 1 here and part 3 here.

Introduction

In the previous article, we looked into Cell and RefCell as a way to achieve interior mutability—the ability to mutate particular fields in a structure regardless of its exterior (explicit or declared) mutability.

However, neither Cell nor RefCell are appropriate to share data among threads. Since Cell has no borrow checking mechanisms and its operations aren’t atomic, it’s possible to have race conditions where we read outdated values and lose updates. RefCell , on the other hand, has run-time borrow checking, but will panic when there are conflicting borrows, such as borrowing a mutably borrowed value. Additionally, RefCell uses a Cell to keep track of the borrow state. This means that even if you were careful and checked it before borrowing, you would risk mutably borrowing the value in multiple threads simultaneously, because its run-time borrow checks aren’t atomic either.

Because of those issues, both Cell and RefCell are marked !Sync , which means they’re unsafe to be used in more than one thread.

Additionally, we need to share references to the cell among threads, but the reference counter type we explored previously, Rc , is also not appropriate to be used in this scenario. The reference counter fields inside Rc are wrapped by Cell , so they would get erroneous values in a threaded program sooner or later. The presence of !Sync fields is “infectious”. Since Rc contains two Cell fields, their !Sync markers propagate to the entire Rc structure. Rc is also marked !Send — unsafe to send (move) to other threads. Likewise, !Send is just as “infectious” as !Sync .

We could implement both traits ourselves in our types, but since those traits are rather important, they’re marked as unsafe. So, we need to tell the Rust compiler we know what we’re doing by prefixing their impl declarations with the unsafe keyword. For instance, if we wanted to make the nodes in the example of the previous article Send and Sync :

unsafe impl < T > Send for Node < T > {} unsafe impl < T > Sync for Node < T > {}

This does make the compiler shut up and allows us to get on with it, but what does it mean?

Send and Sync are automatically derived by the compiler for most types. If a type contains a !Send or !Sync field, the “taint” always spreads to the parent types. By explicitly implementing those traits, we’re implicitly telling the user of our API that our types are thread-safe ( Sync ) and that they can be moved between threads safely ( Send ).

When we say our types are Send and Sync without actually introducing synchronization mechanisms, we’re disrespecting the “contracts” associated with those traits and misleading the user. They’d get run-time panics or bad results due to race conditions. Not a happy situation, at all.

Thread-safe interior mutability

Fortunately, Rust gives us good tools to achieve interior mutability in a thread-safe way without much effort. More than that, it does so in such a way that the borrow checker will have our backs most of the time, so we can’t shoot ourselves in the feet.

One of the really nice aspects about Rust is that once you get the hang of the borrow system, you can use the same reasoning with interior mutability in a single thread ( Cell and RefCell ) and in concurrent programs.

For Copy values

For Copy values (eg., integers), instead of Cell , we have Atomic types ( std::sync::atomic::* ) that rely on assembly instructions to prevent data races:

AtomicBool , a boolean type,

, a boolean type, AtomicIsize , a signed integer type,

, a signed integer type, AtomicUsize , an unsigned integer type, and

, an unsigned integer type, and AtomicPtr , a raw pointer type.

Even though there are only four types, you can can build on AtomicPtr to implement additional ones. Alternatively, you can use crates, such as the atom crate, to do so with a simple API. Quick disclaimer: I haven’t tried atom but the example in its README looks nice, and a quick glance at the source code looks exactly like what I would expect.

Using an atomic type is a bit more involved than doing the same with a Cell . Taking again the naive reference counter example of the previous article, using an AtomicUsize we’d have:

use std :: sync :: atomic ::{ AtomicUsize , Ordering }; struct NaiveRc < T > { reference_count : AtomicUsize , inner_value : T , } impl < T > Clone for NaiveRc < T > { fn clone ( & self ) -> Self { self .reference_count .fetch_add ( 1 , Ordering :: Relaxed ); // ... } }

As you can see, instead of simply assigning a new value to reference_count , we called fetch_add to atomically increment it. The first parameter is the increment size, while the second is new. An Ordering tells the compiler (and the CPU) how much freedom it has to reorder instructions. I won’t delve into that, as the official documentation explains it in sufficient detail.

For non-Copy values

For non-copy values, std::sync::RwLock is the counterpart to RefCell . Like RefCell , RwLock has semantics very similar to our old friend the borrow system, and allows either several “readers” or one “writer”, but not both at the same time, nor several “writers”.

Unlike RefCell , however, RwLock doesn’t panic when there are incompatible borrows: if a thread needs a mutable reference, it will just have to wait until the other threads release the lock (i.e., stop using the borrowed values).

We can get shared, read-only references with read (equivalent to borrow in RefCell ), or exclusive, mutable references with write ( borrow_mut , respectively).

Converting the graph example in the previous article to use RwLock instead of RefCell is straightforward: replace RefCell declarations with RwLock , change borrow to read and borrow_mut to write . We also need to replace Rc with Arc to be able to move references to other threads, but I’ll describe that later.

use std :: thread ; use std :: sync ::{ Arc , RwLock }; // Represents a reference to a node. // This makes the code less repetitive to write and easier to read. type NodeRef < T > = Arc < RwLock < _Node < T >>> ; // The private representation of a node. struct _Node < T > { inner_value : T , adjacent : Vec < NodeRef < T >> , } // The public representation of a node, with some syntactic sugar. struct Node < T > ( NodeRef < T > ); impl < T > Node < T > { // Creates a new node with no edges. fn new ( inner : T ) -> Node < T > { let node = _Node { inner_value : inner , adjacent : vec! [] }; Node ( Arc :: new ( RwLock :: new ( node ))) } // Adds a directed edge from this node to other node. fn add_adjacent ( & self , other : & Node < T > ) { self . 0 .write () .expect ( "Failed to acquire a write lock on node" ) .adjacent .push ( other . 0 .clone ()); } } struct Graph < T > { nodes : Vec < Node < T >> , } impl < T > Graph < T > { fn with_nodes ( nodes : Vec < Node < T >> ) -> Self { Graph { nodes : nodes } } } fn main () { // Create some nodes let node_1 = Node :: new ( 1 ); let node_2 = Node :: new ( 2 ); let node_3 = Node :: new ( 3 ); // Connect some of the nodes (with directed edges) node_1 .add_adjacent ( & node_2 ); node_1 .add_adjacent ( & node_3 ); node_2 .add_adjacent ( & node_1 ); node_3 .add_adjacent ( & node_1 ); // Add nodes to graph let graph = Arc :: new ( Graph :: with_nodes ( vec! [ node_1 , node_2 , node_3 ])); // Spawn a new thread that will print information about every node in the // graph. // The new scope makes this block more obviously different from the code // surrounding it and lets us group variables that will be moved into the // new thread, such as "graph". let guard = { let graph = graph .clone (); let message = "Failed to acquire a read lock" ; thread :: spawn ( move || { for _ in 0 .. 10 { // Show every node in the graph and list their neighbors for node in & graph .nodes { let node = node . 0 .read () .expect ( & message ); let value = node .inner_value ; let neighbours = node .adjacent .iter () .map (| n | n .read () .expect ( & message ) .inner_value ) .collect :: < Vec < _ >> (); println! ( "node ({}) is connected to: {:?}" , value , neighbours ); } println! ( "-------------" ); // Give the main thread a chance to run thread :: yield_now (); } }) }; for _ in 0 .. 10 { // Update the value of every node in the graph for node in & graph .nodes { let mut node = node . 0 .write () .expect ( "Failed to acquire a write lock" ); node .inner_value += 10 ; } // Give the other thread a chance to run thread :: yield_now (); } // Wait for the other thread to end guard .join () .expect ( "Error joining thread" ); }

You can view the differences between the single- and multi-threaded versions in this gist.

Apart from creating a new thread that prints the graph’s information and a new loop in the main thread that updates the node’s values, the only important differences are:

Arc<RwLock<_>> instead of Rc<RefCell<_>>

instead of Every call to borrow and borrow_mut was replaced with read and write , respectively.

I encourage you to make these changes yourself starting from the previous article’s code. Making small, incremental changes and compiling the intermediate versions usually helps me get an intuitive feel for how the API works.

Note that, unlike borrow and borrow_mut , read and write return a LockResult , which is a type alias for Result<Guard, PoisonError<Guard>> , and requires us to match , unwrap or expect it. The Guard is automatically coerced into a reference, so we can pretty much ignore it.

In my experience, you rarely need to deal with the error case for either read or write , as it only happens if another thread with a mutable reference (i.e., a successful write ) panics. In that case, you have a more serious bug elsewhere that you need to take care of.

Both read and write will block the thread until it gets the requested lock. Since you may not want to wait indefinitely, you can also call try_read and try_write instead, which won’t block and return an error if they couldn’t get a lock.

Besides RwLock , there is also std::sync::Mutex , whose name comes from “mutual exclusion”, because it guarantees mutually exclusive access to the wrapped value, i.e., only one thread can access it at a time. Because of this, it’s always safe to mutate the value once you get access to it.

We can look at Mutex as if it were an RwLock without read , only able to give the caller mutable references. In this sense, it’s more constraining than the regular borrow system or an RwLock , which allow either multiple simultaneous readers (with immutable references) or only one writer (a mutable reference) at a time. Even if we want an innocent immutable reference, we must get full permission to the inner value.

As there is only one kind of borrow for Mutex values, read and write are replaced by a single lock method, which will block the thread until the current lock owner releases it (i.e., the other borrow ends). Like with RwLock , if you don’t want to block the thread when the value isn’t available, you can call try_lock instead, which will either give you the lock/mutable reference or an error ( Err ).

Reference counting

As I mentioned earlier, std::rc::Rc lacks synchronization control, which makes it unsafe to be used by multiple threads. Its thread-safe counterpart is Arc , which lives in std::sync , along with RwLock and Mutex .

Arc is very similar to Rc but relies on AtomicUsize for the reference counter, which makes it safe to be updated by more than one thread, unlike Rc , which uses Cell<usize> .

pub struct Rc < T : ? Sized > { ptr : Shared < RcBox < T >> , } struct RcBox < T : ? Sized > { strong : Cell < usize > , weak : Cell < usize > , value : T , } pub struct Arc < T : ? Sized > { ptr : Shared < ArcInner < T >> , } struct ArcInner < T : ? Sized > { strong : atomic :: AtomicUsize , weak : atomic :: AtomicUsize , data : T , }

Arc ’s API is identical to Rc ’s, which makes replacing one with the other a simple matter of searching and replacing the name and correcting the import.

Closing thoughts

In the previous article, we learned that interior mutability in Rust can be achieved through Cell and RefCell in single-threaded programs, supported by Rc where necessary. In this article, we saw the same can be done in a safe way in concurrent programs with Atomic types and RwLock , with the help of Arc .

Single thread Multiple threads Copy value Cell Atomic* Non-Copy value RefCell RwLock , Mutex Reference counter Rc Arc

The table above summarizes the types to be used in single- and multi-threaded scenarios.

Type of access Borrow checker RefCell RwLock Mutex shared / read-only &T borrow read - exclusive / writable &mut T borrow_mut write lock

This second table highlights the similarities between the borrow checker, RefCell , RwLock and, to a lesser degree, Mutex .

You could ask, “Why bother opting for RefCell and Rc if RwLock and Arc have identical semantics and very similar APIs?”

Unfortunately, the types we explored in this article ( Atomic types, RwLock , Mutex and Arc ) depend on synchronization primitives with higher run-time overhead than their naive counterparts, and we’ll want to avoid them whenever possible.

We can have a regular Rc and RefCell combination for variables that aren’t shared with other threads, and their synchronized versions for the bits you want to parallelize. Because the API and semantics are similar in both cases, we will have little cognitive overhead using both.

Another important point we must also pay attention to, is the semantics of the wrapping. For instance, Arc<Vec<RwLock<T>>> is different from Arc<RwLock<Vec<T>>> . With the first, we can’t concurrently mutate the vector itself, but we can mutate its stored values. This is a consequence of Arc implementing Deref but not DerefMut , meaning we can only get immutable references to the vector (which contains lockable elements). With the second form, we get an immutable reference to RwLock , but since it can give us both kinds of references through read and write , we can mutate the vector, adding or removing elements. However, we lose the ability to concurrently mutate the values: once a thread gets a mutable reference to the vector, the others will have to wait, while the first form allows us to have one thread mutating each element in parallel.

In short, Arc<Vec<RwLock<T>>> allows us to mutate all elements of the vector in parallel if we wish to do so, while Arc<RwLock<Vec<T>>> allows only one thread to modify the vector (and its values), leaving other threads waiting for the lock.

If T is itself wrapped by Arc , we would be unable to mutate the stored values at all (because Arc coerces only to immutable references). We would need a monstrosity like Arc<RwLock<Vec<Arc<RwLock<T>>>>> to be able to concurrently mutate both the vector and its elements, but we should take this a hint to rethink how you want to parallelize your code.

Exploring interior mutability in a concurrent environment made me realize that Rust is different from other languages regarding locks. Whereas in other languages we use locks to protect code fragments, in Rust we use them to protect access to data.

In addition, locks are so similar in use to Rust’s borrow mechanisms that they feel like a thread-safe generalization of those mechanisms. Personally, I find this way much easier to reason about than the classic, C way.

Finally, I know it’s tempting, but don’t throw interior mutability everywhere just to make the borrow checker shut up. Consider carefully whether the situation really calls for interior mutability or a refactor of your data structures. This goes doubly so for concurrent programs, not only because RwLock , Mutex and Arc incur additional run-time costs, but also because synchronization is easy to mess up and leave you with race conditions. Fortunately, Rust’s borrow checker gives us precious guidance and makes them much less likely. Race conditions are nasty to debug, be especially careful about dropping your locks as soon as possible.

That’s it. Now you know enough to effectively employ interior mutability in your programs, whether they are single- or multi-threaded. Well done! 🎉

My thanks to /u/Manishearth, /u/Steel_Neuron, and /u/diwic for their feedback.

I hope you found this article useful and/or interesting. As always, if you found a mistake or have any questions, please ping me on Twitter (@meqif) or send me an email (words@ricardomartins.cc). You can also join the discussion on reddit.