is it possible to use Arc without a lock? Because I really don't care the order of reading data. Here is my playground.
use std::{sync::Arc, thread};
fn main() {
println!("Hello, world!");
let x = Arc::new(0);
let y = Arc::clone(&x);
thread::spawn(move || {
for i in 0..10 {
println!("exe:{},{}", i, y);
}
});
while *x < 100000 {
// Is it ok to change the value of x here?
*x += 1;
}
}
No. Even if you don't care about anything at all, Rust still does not allow data races. And if you only don't care about the order, you can still get unexpected results because the operation isn't atomic at CPU-level or because of compiler optimizations.
However, you don't have to use mutexes or other similar locks. You can use atomics. And if you don't care about order you can use Ordering::Relaxed that is going to be almost free (free on loads on x86 and I think ARM too, adds will have some overhead but it is marginal probably):
use std::sync::atomic::{AtomicI32, Ordering};
fn main() {
println!("Hello, world!");
let x = Arc::new(AtomicI32::new(0));
let y = Arc::clone(&x);
thread::spawn(move || {
for i in 0..10 {
println!("exe:{},{}", i, y.load(Ordering::Relaxed));
}
});
while x.load(Ordering::Relaxed) < 100000 {
x.fetch_add(1, Ordering::Relaxed);
}
}
Arc protects the reference count itself, it doesn't protect the data it references. Per the Arc docs on Thread Safety:
Arc<T> makes it thread safe to have multiple ownership of the same data, but it doesn’t add thread safety to its data.
The general docs for Arc note:
Shared references in Rust disallow mutation by default, and Arc is no exception: you cannot generally obtain a mutable reference to something inside an Arc. If you need to mutate through an Arc, use Mutex, RwLock, or one of the Atomic types.
In short, Arc is not the appropriate type for what you're doing by itself. You could make it work just fine with an Arc<AtomicI32> or the like though, where the Arc maintains the lifetime, and the AtomicI32 protects access to the data itself.
Related
I'm trying to speed up a computationally-heavy Rust function by making it concurrent using only the built-in thread support. In particular, I want to alternate between quick single-threaded phases (where the main thread has mutable access to a big structure) and concurrent phases (where many worker threads run with read-only access to the structure). I don't want to make extra copies of the structure or force it to be 'static. Where I'm having trouble is convincing the borrow checker that the worker threads have finished.
Ignoring the borrow checker, an Arc reference seems like does all that is needed. The reference count in the Arc increases with the .clone() for each worker, then decreases as the workers conclude and I join all the worker threads. If (and only if) the Arc reference count is 1, it should be safe for the main thread to resume. The borrow checker, however, doesn't seem to know about Arc reference counts, and insists that my structure needs to be 'static.
Here's some sample code which works fine if I don't use threads, but won't compile if I switch the comments to enable the multi-threaded case.
struct BigStruct {
data: Vec<usize>
// Lots more
}
pub fn main() {
let ref_bigstruct = &mut BigStruct { data: Vec::new() };
for i in 0..3 {
ref_bigstruct.data.push(i); // Phase where main thread has write access
run_threads(ref_bigstruct); // Phase where worker threads have read-only access
}
}
fn run_threads(ref_bigstruct: &BigStruct) {
let arc_bigstruct = Arc::new(ref_bigstruct);
{
let arc_clone_for_worker = arc_bigstruct.clone();
// SINGLE-THREADED WORKS:
worker_thread(arc_clone_for_worker);
// MULTI-THREADED DOES NOT COMPILE:
// let handle = thread::spawn(move || { worker_thread(arc_clone_for_worker); } );
// handle.join();
}
assert!(Arc::strong_count(&arc_bigstruct) == 1);
println!("??? How can I tell the borrow checker that all borrows of ref_bigstruct are done?")
}
fn worker_thread(my_struct: Arc<&BigStruct>) {
println!(" worker says len()={}", my_struct.data.len());
}
I'm still learning about Rust lifetimes, but what I think (fear?) what I need is an operation that will take an ordinary (not 'static) reference to my structure and give me an Arc that I can clone into immutable references with a 'static lifetime for use by the workers. Once all the the worker Arc references are dropped, the borrow checker needs to allow my thread-spawning function to return. For safety, I assume this would panic if the the reference count is >1. While this seems like it would generally confirm with Rust's safety requirements, I don't see how to do it.
The underlying problem is not the borrowing checker not following Arc and the solution is not to use Arc. The problem is the borrow checker being unable to understand that the reason a thread must be 'static is because it may outlive the spawning thread, and thus if I immediately .join() it it is fine.
And the solution is to use scoped threads, that is, threads that allow you to use non-'static data because they always immediately .join(), and thus the spawned thread cannot outlive the spawning thread. Problem is, there are no worker threads on the standard library. Well, there are, however they're unstable.
So if you insist on not using crates, for some reason, you have no choice but to use unsafe code (don't, really). But if you can use external crates, then you can use the well-known crossbeam crate with its crossbeam::scope function, at least til std's scoped threads are stabilized.
In Rust Arc< T>, T is per definition immutable. Which means in order to use Arc, to make threads access data that is going to change, you also need it to wrap in some type that is interiorly mutable.
Rust provides a type that is especially suited for a single write or multiple read accesses in parallel, called RwLock.
So for your simple example, this would propably look something like this
use std::{sync::{Arc, RwLock}, thread};
struct BigStruct {
data: Vec<usize>
// Lots more
}
pub fn main() {
let arc_bigstruct = Arc::new(RwLock::new(BigStruct { data: Vec::new() }));
for i in 0..3 {
arc_bigstruct.write().unwrap().data.push(i); // Phase where main thread has write access
run_threads(&arc_bigstruct); // Phase where worker threads have read-only access
}
}
fn run_threads(ref_bigstruct: &Arc<RwLock<BigStruct>>) {
{
let arc_clone_for_worker = ref_bigstruct.clone();
//MULTI-THREADED
let handle = thread::spawn(move || { worker_thread(&arc_clone_for_worker); } );
handle.join().unwrap();
}
assert!(Arc::strong_count(&ref_bigstruct) == 1);
}
fn worker_thread(my_struct: &Arc<RwLock<BigStruct>>) {
println!(" worker says len()={}", my_struct.read().unwrap().data.len());
}
Which outputs
worker says len()=1
worker says len()=2
worker says len()=3
As for your question, the borrow checker does not know when an Arc is released, as far as I know. The references are counted at runtime.
I would like to have a shared struct between threads. The struct has many fields that are never modified and a HashMap, which is. I don't want to lock the whole HashMap for a single update/remove, so my HashMap looks something like HashMap<u8, Mutex<u8>>. This works, but it makes no sense since the thread will lock the whole map anyways.
Here's this working version, without threads; I don't think that's necessary for the example.
use std::collections::HashMap;
use std::sync::{Arc, Mutex};
fn main() {
let s = Arc::new(Mutex::new(S::new()));
let z = s.clone();
let _ = z.lock().unwrap();
}
struct S {
x: HashMap<u8, Mutex<u8>>, // other non-mutable fields
}
impl S {
pub fn new() -> S {
S {
x: HashMap::default(),
}
}
}
Playground
Is this possible in any way? Is there something obvious I missed in the documentation?
I've been trying to get this working, but I'm not sure how. Basically every example I see there's always a Mutex (or RwLock, or something like that) guarding the inner value.
I don't see how your request is possible, at least not without some exceedingly clever lock-free data structures; what should happen if multiple threads need to insert new values that hash to the same location?
In previous work, I've used a RwLock<HashMap<K, Mutex<V>>>. When inserting a value into the hash, you get an exclusive lock for a short period. The rest of the time, you can have multiple threads with reader locks to the HashMap and thus to a given element. If they need to mutate the data, they can get exclusive access to the Mutex.
Here's an example:
use std::{
collections::HashMap,
sync::{Arc, Mutex, RwLock},
thread,
time::Duration,
};
fn main() {
let data = Arc::new(RwLock::new(HashMap::new()));
let threads: Vec<_> = (0..10)
.map(|i| {
let data = Arc::clone(&data);
thread::spawn(move || worker_thread(i, data))
})
.collect();
for t in threads {
t.join().expect("Thread panicked");
}
println!("{:?}", data);
}
fn worker_thread(id: u8, data: Arc<RwLock<HashMap<u8, Mutex<i32>>>>) {
loop {
// Assume that the element already exists
let map = data.read().expect("RwLock poisoned");
if let Some(element) = map.get(&id) {
let mut element = element.lock().expect("Mutex poisoned");
// Perform our normal work updating a specific element.
// The entire HashMap only has a read lock, which
// means that other threads can access it.
*element += 1;
thread::sleep(Duration::from_secs(1));
return;
}
// If we got this far, the element doesn't exist
// Get rid of our read lock and switch to a write lock
// You want to minimize the time we hold the writer lock
drop(map);
let mut map = data.write().expect("RwLock poisoned");
// We use HashMap::entry to handle the case where another thread
// inserted the same key while where were unlocked.
thread::sleep(Duration::from_millis(50));
map.entry(id).or_insert_with(|| Mutex::new(0));
// Let the loop start us over to try again
}
}
This takes about 2.7 seconds to run on my machine, even though it starts 10 threads that each wait for 1 second while holding the exclusive lock to the element's data.
This solution isn't without issues, however. When there's a huge amount of contention for that one master lock, getting a write lock can take a while and completely kills parallelism.
In that case, you can switch to a RwLock<HashMap<K, Arc<Mutex<V>>>>. Once you have a read or write lock, you can then clone the Arc of the value, returning it and unlocking the hashmap.
The next step up would be to use a crate like arc-swap, which says:
Then one would lock, clone the [RwLock<Arc<T>>] and unlock. This suffers from CPU-level contention (on the lock and on the reference count of the Arc) which makes it relatively slow. Depending on the implementation, an update may be blocked for arbitrary long time by a steady inflow of readers.
The ArcSwap can be used instead, which solves the above problems and has better performance characteristics than the RwLock, both in contended and non-contended scenarios.
I often advocate for performing some kind of smarter algorithm. For example, you could spin up N threads each with their own HashMap. You then shard work among them. For the simple example above, you could use id % N_THREADS, for example. There are also complicated sharding schemes that depend on your data.
As Go has done a good job of evangelizing: do not communicate by sharing memory; instead, share memory by communicating.
Suppose the key of the data is map-able to a u8
You can have Arc<HashMap<u8,Mutex<HashMap<Key,Value>>>
When you initialize the data structure you populate all the first level map before putting it in Arc (it will be immutable after initialization)
When you want a value from the map you will need to do a double get, something like:
data.get(&map_to_u8(&key)).unwrap().lock().expect("poison").get(&key)
where the unwrap is safe because we initialized the first map with all the value.
to write in the map something like:
data.get(&map_to_u8(id)).unwrap().lock().expect("poison").entry(id).or_insert_with(|| value);
It's easy to see contention is reduced because we now have 256 Mutex and the probability of multiple threads asking the same Mutex is low.
#Shepmaster example with 100 threads takes about 10s on my machine, the following example takes a little more than 1 second.
use std::{
collections::HashMap,
sync::{Arc, Mutex, RwLock},
thread,
time::Duration,
};
fn main() {
let mut inner = HashMap::new( );
for i in 0..=u8::max_value() {
inner.insert(i, Mutex::new(HashMap::new()));
}
let data = Arc::new(inner);
let threads: Vec<_> = (0..100)
.map(|i| {
let data = Arc::clone(&data);
thread::spawn(move || worker_thread(i, data))
})
.collect();
for t in threads {
t.join().expect("Thread panicked");
}
println!("{:?}", data);
}
fn worker_thread(id: u8, data: Arc<HashMap<u8,Mutex<HashMap<u8,Mutex<i32>>>>> ) {
loop {
// first unwrap is safe to unwrap because we populated for every `u8`
if let Some(element) = data.get(&id).unwrap().lock().expect("poison").get(&id) {
let mut element = element.lock().expect("Mutex poisoned");
// Perform our normal work updating a specific element.
// The entire HashMap only has a read lock, which
// means that other threads can access it.
*element += 1;
thread::sleep(Duration::from_secs(1));
return;
}
// If we got this far, the element doesn't exist
// Get rid of our read lock and switch to a write lock
// You want to minimize the time we hold the writer lock
// We use HashMap::entry to handle the case where another thread
// inserted the same key while where were unlocked.
thread::sleep(Duration::from_millis(50));
data.get(&id).unwrap().lock().expect("poison").entry(id).or_insert_with(|| Mutex::new(0));
// Let the loop start us over to try again
}
}
Maybe you want to consider evmap:
A lock-free, eventually consistent, concurrent multi-value map.
The trade-off is eventual-consistency: Readers do not see changes until the writer refreshes the map. A refresh is atomic and the writer decides when to do it and expose new data to the readers.
I'm trying to write a program that spawns a background thread that continuously inserts data into some collection. At the same time, I want to keep getting input from stdin and check if that input is in the collection the thread is operating on.
Here is a boiled down example:
use std::collections::HashSet;
use std::thread;
fn main() {
let mut set: HashSet<String> = HashSet::new();
thread::spawn(move || {
loop {
set.insert("foo".to_string());
}
});
loop {
let input: String = get_input_from_stdin();
if set.contains(&input) {
// Do something...
}
}
}
fn get_input_from_stdin() -> String {
String::new()
}
However this doesn't work because of ownership stuff.
I'm still new to Rust but this seems like something that should be possible. I just can't find the right combination of Arcs, Rcs, Mutexes, etc. to wrap my data in.
First of all, please read Need holistic explanation about Rust's cell and reference counted types.
There are two problems to solve here:
Sharing ownership between threads,
Mutable aliasing.
To share ownership, the simplest solution is Arc. It requires its argument to be Sync (accessible safely from multiple threads) which can be achieved for any Send type by wrapping it inside a Mutex or RwLock.
To safely get aliasing in the presence of mutability, both Mutex and RwLock will work. If you had multiple readers, RwLock might have an extra performance edge. Since you have a single reader there's no point: let's use the simple Mutex.
And therefore, your type is: Arc<Mutex<HashSet<String>>>.
The next trick is passing the value to the closure to run in another thread. The value is moved, and therefore you need to first make a clone of the Arc and then pass the clone, otherwise you've moved your original and cannot access it any longer.
Finally, accessing the data requires going through the borrows and locks...
use std::sync::{Arc, Mutex};
fn main() {
let set = Arc::new(Mutex::new(HashSet::new()));
let clone = set.clone();
thread::spawn(move || {
loop {
clone.lock().unwrap().insert("foo".to_string());
}
});
loop {
let input: String = get_input_from_stdin();
if set.lock().unwrap().contains(&input) {
// Do something...
}
}
}
The call to unwrap is there because Mutex::lock returns a Result; it may be impossible to lock the Mutex if it is poisoned, which means a panic occurred while it was locked and therefore its content is possibly garbage.
I'm new to Rust and threading and I'm trying to print out a number while adding to it in another thread. How can I accomplish this?
use std::thread;
use std::time::Duration;
fn main() {
let mut num = 5;
thread::spawn(move || {
loop {
num += 1;
thread::sleep(Duration::from_secs(10));
}
});
output(num);
}
fn output(num: i32) {
loop {
println!("{:?}", num);
thread::sleep(Duration::from_secs(5));
}
}
The above code doesn't work: it always prints 5 as if the number is never incremented.
Please read the "Shared-State Concurrency" chapter of The Rust Book, it explains how to do this in detail.
In short:
Your program does not work because num is copied, so output() and the thread operate on different copies of the number. The Rust compiler will fail to compile with an error if num is not copyable.
Since you need to share the same variable between multiple threads, you need to wrap it in an Arc (atomic reference-counted variable)
Since you need to modify the variable inside the Arc, you need to put it in a Mutex or RwLock. You use the .lock() method to obtain a mutable reference out of a Mutex. The method will ensure exclusive access across the whole process during the lifetime of that mutable reference.
use std::sync::{Arc, Mutex};
use std::thread;
use std::time::Duration;
fn main() {
let num = Arc::new(Mutex::new(5));
// allow `num` to be shared across threads (Arc) and modified
// (Mutex) safely without a data race.
let num_clone = num.clone();
// create a cloned reference before moving `num` into the thread.
thread::spawn(move || {
loop {
*num.lock().unwrap() += 1;
// modify the number.
thread::sleep(Duration::from_secs(10));
}
});
output(num_clone);
}
fn output(num: Arc<Mutex<i32>>) {
loop {
println!("{:?}", *num.lock().unwrap());
// read the number.
// - lock(): obtains a mutable reference; may fail,
// thus return a Result
// - unwrap(): ignore the error and get the real
// reference / cause panic on error.
thread::sleep(Duration::from_secs(5));
}
}
You may also want to read:
Why does Rust have mutexes and other sychronization primitives, if sharing of mutable state between tasks is not allowed?
What happens when an Arc is cloned?
How do I share a mutable object between threads using Arc? (for why we need Arc<Mutex<i32>> instead of Arc<i32>)
When would you use a Mutex without an Arc? (for why we need Arc<Mutex<i32>> instead of Mutex<i32>)
The other answer solves the problem for any type, but as pnkfelix observes, atomic wrapper types are another solution that will work for the specific case of i32.
Since Rust 1.0, you can use AtomicBool, AtomicPtr<T>, AtomicIsize and AtomicUsize to synchronize multi-threaded access to bool, *mut T, isize and usize values. In Rust 1.34, several new Atomic types have been stabilized, including AtomicI32. (Check the std::sync::atomic documentation for the current list.)
Using an atomic type is most likely more efficient than locking a Mutex or RwLock, but requires more attention to the low-level details of memory ordering. If your threads share more data than can fit in one of the standard atomic types, you probably want a Mutex instead of multiple Atomics.
That said, here's a version of kennytm's answer using AtomicI32 instead of Mutex<i32>:
use std::sync::{
atomic::{AtomicI32, Ordering},
Arc,
};
use std::thread;
use std::time::Duration;
fn main() {
let num = Arc::new(AtomicI32::new(5));
let num_clone = num.clone();
thread::spawn(move || loop {
num.fetch_add(1, Ordering::SeqCst);
thread::sleep(Duration::from_secs(10));
});
output(num_clone);
}
fn output(num: Arc<AtomicI32>) {
loop {
println!("{:?}", num.load(Ordering::SeqCst));
thread::sleep(Duration::from_secs(5));
}
}
Arc is still required for shared ownership (but see How can I pass a reference to a stack variable to a thread?).
Choosing the right memory Ordering is far from trivial. SeqCst is the most conservative choice, but if there is only one memory address being shared, Relaxed should also work. See the links below for more information.
Links
std::sync::atomic module documentation
Atomics (chapter of The Rustonomicon)
LLVM Memory Model for Concurrent Operations and Atomic Instructions and Concurrency Guide
What is the right approach to share a common object between many threads when the object may sometimes be written to by one owner?
I tried to create one Configuration trait object with several methods to get and set config keys. I'd like to pass this to other threads where configuration items may be read. Bonus points would be if it can be written and read by everyone.
I found a Reddit thread which talks about Rc and RefCell; would that be the right way? I think these would not allow me to borrow the object immutably multiple times and still mutate it.
Rust has a built-in concurrency primitive exactly for this task called RwLock. Together with Arc, it can be used to implement what you want:
use std::sync::{Arc, RwLock};
use std::sync::mpsc;
use std::thread;
const N: usize = 12;
let shared_data = Arc::new(RwLock::new(Vec::new()));
let (finished_tx, finished_rx) = mpsc::channel();
for i in 0..N {
let shared_data = shared_data.clone();
let finished_tx = finished_tx.clone();
if i % 4 == 0 {
thread::spawn(move || {
let mut guard = shared_data.write().expect("Unable to lock");
guard.push(i);
finished_tx.send(()).expect("Unable to send");
});
} else {
thread::spawn(move || {
let guard = shared_data.read().expect("Unable to lock");
println!("From {}: {:?}", i, *guard);
finished_tx.send(()).expect("Unable to send");
});
}
}
// wait until everything's done
for _ in 0..N {
let _ = finished_rx.recv();
}
println!("Done");
This example is very silly but it demonstrates what RwLock is and how to use it.
Also note that Rc and RefCell/Cell are not appropriate in a multithreaded environment because they are not synchronized properly. Rust won't even allow you to use them at all with thread::spawn(). To share data between threads you must use an Arc, and to share mutable data you must additionally use one of the synchronization primitives like RWLock or Mutex.