Fearless Concurrency
作者：互联网
Handling concurrent programming safely and efficiently is another of Rust's major goals.
For simplicity's sake, we'll refer to many of the problems as concurrent rather than being more precise by saying concurrent and/or parallel. You may wonder about differences between concurrency and parallelism.
Concurrency is when two or more tasks can start, run and complete in overlapping time periods. It's can be achieved on a single-core machine. Just let the operating system arranges the CPU time reasonably. In a CPU time, there can be only task running.
Parallelism is when tasks literally run at the same time, even in a CPU time, there can be multiple tasks running in multiple cores, if your machine has a multi-core processor.
Using Threads to Run Code Simultaneously
This chapter won't cover detailed introduction and goodnesses to threads, so if you're not familiar with them, you should acquire these knowledges first. We'll just focus on the usage of threads in Rust and how to avoid data races.
Many programming languages provide their own special implementation of threads. Programming language-provided threads are known as green threads, and languages that use green threads will execute them in the context of a different number of operating system threads. For this reason, the green-threaded model is called the M:N model: there are M green threads per N operating system threads, where M and N are not necessarily the same number.
Creating a New Thread with spawn
We use the function thread::spawn function to create a new thread and pass it a closure containing the code we want to run in the new thread.
thread::spawn(|| {
println!("Hello world from the spawned thread.");
thread::sleep(Duaration::from_milli(1));
})
Note that with this function, the new thread will be stopped when the main thread ends.
Waiting for All Threads to Finish Using join Handles
The return type of the function thread::spawn is JoinHandle. A JoinHandle is an owned value that we can the join method on it. Once we call the method, the thread that calls the method have to wait until the thread that spawned from the function which returns the JoinHandle.
Using move Closures with Threads
The move closure is often used alongside thread::spawn because it allows you to use data from one thread in another thread.
We have mentioned that the move keyword allows you to take the ownership of values that the closure uses in its environment.
use std::thread;
fn main() {
let v = vec![1, 2, 3];
let handle = thread::spawn(move || {
println!("Here's a vector: {:?}", v);
});
handle.join().unwrap();
}
Using Message Passing to Transfer Data Between Threads
One increasingly popular approach to ensuring safe concurrency is message passing, where threads communicate by sending each other messages containing data.
One major tool Rust has for accomplishing message-sending concurrency is the channel. A channel has a transmitter and a receiver, one part of your code calls methods on the transmitter with the data you want to send, and another part checks the receiving end for arriving messages. A channel is said to be closed is either the transmitter or receiver half is dropped.
We create a new channel using the mpsc::channel function; mpsc stands for multiple producer, single consumer. The mpsc::channel function returns a tuple, the first element is the sending end and the second element is the receiving end.
let (tx, rx) = mpsc::channel();
Let's take an example to see how a channel works.
use std::sync::mpsc;
use std::thread;
fn main() {
let (tx, rx) = mpsc::channel();
thread::spawn(move || {
let val = String::from("Hi");
tx.send(val).unwrap();
});
}
The transmitting end has a send method that sends a value to the receiving end and return a Result<T,E> type, if the receiving end has already been dropped and there's no where to send a value, the operation will return an error. In this example, we're calling unwrap to panic in case of error. For a real application, we would handle the error more specifically, you can review the error handling chapter for strategies for proper error handling.
Let's see the receiving end:
use std::sync::mpsc;
use std::thread;
fn main() {
let (tx, rx) = mpsc::channel();
thread::spawn(move || {
let val = String::from("Hi");
tx.send(val).unwrap();
});
let received = rx.recv().unwrap();
println!("received: {}", received);
}
So we let the spawned thread in charge of sending and the main thread in charge of receiving. The receiving end has a recv method to receive values.
The recv method is a blocking method, a blocking method, means when you call it, the thread on which the method get called will be blocked until the method returns.
If you don't want to block the thread, you can use the method try_recv. The try_recv method immediately returns a Result<T, E>: an Ok value holding a message if one is available and an Err if there aren't any messages this time.
We can also treat rx as an iterator and use it in a for loop as such.
for received in rx {
println!("Got: {}", received);
}
The loop will also block the thread, and every time the receiving end receives a value, the code in the loop block will run.
Channels and Ownership Transference
Let's see how channels and ownership work together.
For the above code, when we use the send method to send a value to another thread will take the ownership of the value. Nor we can pass a reference as a parameter, cause we cannot sure how long is the value gonna live and the Rust compiler has to make sure that the value lives longer than the its any reference.
The send function takes ownership of its parameter, and when the value is moved, the receiver takes ownership of it. This stops us from accidentally using the value again after sending it; the ownership system checks that everything is okay.
Creating Multiple Producers by Cloning the Transmitter
We mentioned that mpsc was an acronym for multiple producer, single consumer. We know that the channel method can only produce one transmitting end and one receiving end. If we want to have multiple producer, we can clone the transmitting end.
use std::sync::mpsc;
use std::thread;
use std::time::Duration;
fn main() {
// --snip--
let (tx, rx) = mpsc::channel();
let tx1 = tx.clone();
thread::spawn(move || {
let vals = vec![
String::from("hi"),
String::from("from"),
String::from("the"),
String::from("thread"),
];
for val in vals {
tx1.send(val).unwrap();
thread::sleep(Duration::from_secs(1));
}
});
thread::spawn(move || {
let vals = vec![
String::from("more"),
String::from("messages"),
String::from("for"),
String::from("you"),
];
for val in vals {
tx.send(val).unwrap();
thread::sleep(Duration::from_secs(1));
}
});
for received in rx {
println!("Got: {}", received);
}
// --snip--
}
Shared-State Concurrency
Shared memory concurrency is like multiple ownership: multiple threads can access the same memory location at the same time. Usually, we use mutexes to manage multiple accessing to shared memory.
Using Mutexes to Allow Access to Data from One Thread at a Time
Mutex is an abbreviation for mutual exclusion, a mutex allows only one thread to access some data at any time.
When a thread want to access a shared data protected by mutex, it has to first attempt to require the mutex lock which cannot be required successfully if any thread is using the data. In this way, we can make sure that only thread accessing the data at any time.
The API for Mutex<T>
The Rust provides a Mutex<T> type for mutexes demand in the std::sync module.
According to the source code, a Mutex<T> is a struct which is able to contain a value. We can pass the value in as a parameter of the new method.
use std::sync::Mutex;
fn main() {
let m = Mutex::new(5);
{
let mut num = m.lock().unwrap();
*num = 6;
}
println!("m = {:?}", m);
}
When we want to access the data in the mutex, we need to call the lock method which will block the current thread and return a Result type.
After unwrapping, we get a MutexGuard type result. A MutexGuard is an RAII (Resource Acquisition Is Initialization, an Object-Oriented Programming concept to avoid memory leak) guard to allow scoped unlock of the lock. When the guard goes out of scope, the mutex will be unlocked. To access the value, we need to dereference the result.
The call to lock would fail if another thread holding the lock panicked. In that case, no one would ever be able to get the lock, so we've chosen to unwrap and have this thread panic if we're in that situation.
Sharing a Mutex<T> Between Multiple Threads
Since a mutex may get accessed by multiple threads, we need to make sure it is accessible in multiple threads.
However, if we just create a mutex variable in the main thread like:
let m = Mutex::new(0);
We're not allowed to use it in multiple threads, cause the thread using it will take the ownership of the value. So only types that implement the Copy trait is allowed to bring into multiple threads.
Multiple Ownership with Multiple Threads
The multiple owners for a single value mechanism may save us. We've mentioned that in the "Smart Pointer" chapter, a value can be owned by multiple threads and the value will not be dropped until all references go out of the scope.
However, if wrap a mutex with Rc, we still get errors:
let m = Rc::new(Mutex::new(0));
The error message says: "Rc<Mutex\<T>> cannot be sent between threads safely". This brings an issue that we haven't talked about yet: what types can be used in concurrent situations? The answer is all types that implement the Send trait, we will talk about this in more detail later.
So this method won't work out either.
Atomic Reference Counting with Arc<T>
Arc<T> is a type like Rc<T> that is safe to use in concurrent situations, Arc is an abbreviation for atomically reference counted. And the Arc<T> type has the same API.
Sum all this up, we get the code:
use std::sync::{Arc, Mutex};
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());
}
Extensible Concurrency with the Sync and Send Traits
Allowing Transference of Ownership Between Threads with Send
The Send marker trait indicates that ownership of the type implementing Send can be transfered between threads. Almost every Rust type implements Send except Rc<T>.
Allowing Access from Multiple Threads with Sync
The sync marker trait indicates that it is safe for the type implementing Sync to be referenced from multiple threads. Similar to Send, primitive types are Sync.
标签：use,thread,Fearless,value,let,Concurrency,threads,method 来源： https://www.cnblogs.com/lunar-ubuntu/p/14441026.html