Async-std: an async port of the Rust standard library
async.rs
async.rs
What do I gain if I have code like this [0], which has a bunch of `.await?` in sequence?
I know .await != join_thread(), but doesn't execution of the current scope of code halt while it waits for the future we are `.await`-ing to complete?
I know this allows the executor to go poll other futures. But if we haven't explicitly spawned more futures concurrently, via something like task::spawn() or thread::spawn(), then there's nothing else the cpu can possible do in our process?
[0] https://github.com/async-rs/async-std/blob/master/examples/t...
For a more complex networked application, we have the tutorial here: https://github.com/async-rs/a-chat
I think the expectation with Rust async-await at the moment is likely that people are familiar with async syntax from other languages e.g. Python - it's not even in beta yet, you need to be running nightly to get the syntax.
If there was another future spawned then the await would cause the runtime to sit there until either of the futures completed. The code would attend to the first future that completes intil that hits an await.
Async is just a way to get cooperative threads compiled to a static state machine, trading lower concurrent utilization and throughput for less context switch overhead and lower latency.
Now imagine that you spawned a few hundred of them with JoinAll. Each would run, multiplexed within a single thread, with execution being passed at the await points.
* anyone know the correct nomenclature for this? Single-coroutine?
Same code flow just it allows you to launch the same thing multiple times without having to wait for the whole thing to finish sequentially or wait on the OS to handle your threads.
As soon as you do that, your code isn't async anymore. And if you're using a framework like Vert.X or node that only runs one thread per core you're in big trouble.
The most reasonable answer I've seen to all this is Java's Project Loom. An attempt to make fibers transparently act like threads, so you can use regular threaded libraries as async code.
Rust is going to have the same problem Java does with async. A lot of code was written way before async was available, and it not always obvious whether something blocks.
In my c# world, I use async methods for REST endpoints, which in turn use async calls for anything IO-bound (database, message bus, distributed key store, file system etc). I think more often than not, it's done correctly.
For example, socket.read() might return a future that represents a read on a file descriptor. I don't know the internals of Rust's async support at all, but presumably the future is queued up and exposes some kind of trait that Tokio et al can recognize as being an FD so it can be polled on using the best API such as epoll_wait() or whatever.
But let's say there's some kernel or hardware API or something that has a wait API that isn't based on file descriptors, and I implement my own async function get_next_event() that uses this API. Do I need to extend Tokio, or the Rust async runtime API, to make it understand how to integrate this into its queues? In a non-FD case, wouldn't it have to spawn a parallel thread to handle waiting for that one future, since it can't be included in epoll_wait()?
So, futures have basically two bits of their API: the first is that they're inert until the poll is called. The second is that they need to register a "waker" with the executor before they return pending. So it's not so much that the executor needs to know details about how to do the polling; but the person implementing socket.read() needs to implement the future correctly. It would construct the waker to do the right thing with epoll. Tokio started before this style of API existed, and so bundles a few concepts in the current stack (though honestly, an integrated solution is nicer in some ways, so I don't think it's a bad thing, just that it makes it slightly easier to conflate the pieces since they're all provided by the same package.)
Async/await, strictly speaking, is 100% agnostic of all of this, because it just produces stuff with the Futures interface; these bits are inside the implementation of leaf futures. And executors don't need to know these details, they just need to call poll at the right time, and in accordance with their wakers.
I can't wait until the async book is done, it's really hard remembering which bits worked which way at which time, to be honest.
Is this true? Essentially this is claiming that an executor does not need to use mio (epoll/kqueue/...) to be able to execute futures that do async network i/o.
So who uses mio? Would each type implementing the Future trait use mio internally as a private detail? That is, using two such future types, would they maintain multiple independent kqueues and the executor isn't able to put them both in one?
Tokio uses mio to implement its futures that do async IO, so if you use Tokio, you use mio. You don’t have to use Tokio, though it is the most popular and most battle tested.
Many futures don’t do IO directly; for example, all of the combinator futures. Libraries can be written to be agnostic to the underlying IO, only using the AsyncRead/AsyncWrite traits, for example.
If the executor is Tokio, it’s built on mio which will use one of kqueue, epoll or iocp depending on the platform: https://docs.rs/mio/0.6.19/mio/struct.Poll.html#implementati...
Nope, async really isn't trivial.
> I know .await != join_thread(), but doesn't execution of the current scope of code halt while it waits for the future we are `.await`-ing to complete?
It doesn't, that's the charm of it.
It's best to treat 'await' as syntactic sugar, and to dig in to the underlying concepts.
I realise we're not talking C#/.Net, but that's what I know: in .Net, your function might do slow IO (network activity, say) then process the result to produce an int. Your function will have a return-type of `Task<int>`. Your function will quickly return a non-completed Task object, which will enter a completed state only once the network activity has concluded and processing has occurred to give the final `int` value.
The caller of your function can use the `Task#ContinueWith` method, which enqueues work to occur if/when the Task completes, using the result value from the Task. (We'll ignore exceptions here.)
Internal to your function, the network activity itself will also have taken the form of a standard-library Task, and our function will have made use of its `ContinueWith` method. Things can compose nicely in this way; `Task#ContinueWith` returns another Task.
(We needn't think about the particulars of threads too much here, but some thread clearly eventually marks that Task object as completed, so clearly some thread will be in a good position to 'notice' that it's time to act on that `ContinueWith` now. The continuation generally isn't guaranteed to run on the same thread as where we started. That's generally fine, with some notable exceptions.)
You might think that chain-invoking `ContinueWith` would get tedious, as you'd have to write a new function for each step of the way if we make use of several async operations - each continuation means writing another function to pass to `ContinueWith`, after all. Perhaps it would be more natural to just write one big function and have compiler handle the `ContinueWith` calls.
You'd be right. That's why they invented the `await` keyword, which is essentially just syntactic sugar around .Net's `ContinueWith` method. It also correctly handles exceptions, which would otherwise be error-prone, so it's generally best to avoid writing continuations manually.
There's more machinery at play here of course, but that seems like a good starting point.
Assorted related topics:
* If you use `ContinueWith` on a Task which is already completed, it can just stay on the same thread 'here and now' to run your code
* It's possible to produce already-completed Task objects. Rarely useful, but permitted.
* There's plenty going on with thread-pools and .Net 'contexts'
* The often-overlooked possibility of deadlocking if you aren't careful [0]
* None of this would make sense if we had to keep lots of background threads around to fire our continuations, but we don't [1]
* Going async is not the same thing as parallelising, but Tasks are great for managing parallelism too
* This stuff doesn't improve 'straight-line' performance, but it can greatly improve our scalability by avoiding blocking threads to wait on IO. (That is to say, we can better handle a high rate of requests, but our speed at handling a lone request on a quiet day, will be no better.)
I found this overview to be fairly digestible [2]
[0] https://blog.stephencleary.com/2012/07/dont-block-on-async-c...
[1] https://blog.stephencleary.com/2013/11/there-is-no-thread.ht...
[2] https://stackoverflow.com/a/39796872/
See also:
https://docs.microsoft.com/en-us/dotnet/standard/parallel-pr...
https://docs.microsoft.com/en-us/dotnet/api/system.threading...
Slight word of warning: `async/await` is more than just sugar in Rust, it also enables borrowing over awaits, which was previously not possible.
https://doc.rust-lang.org/std/future/trait.Future.html#requi...
Here is synchronous code:
result = server.getStuff()
print(result)
Here is synchronous code, that tries to be asynchronous: server.getStuff(lambda result: print(result))
Once server.getStuff returns, the callback passed to it is called with the result.Here is the same code with async/await:
result = await server.getStuff()
print(result)
Internally, the compiler rewrites it to (roughly) the second form. That's called a continuation.That's pretty much it.
A more involved example.
Synchronous code:
result = server.getStuff()
second = server.getMoreStuff(result+1)
print(result)
Synchronous code that tries to be asynchronous: server.getStuff(
lambda result: server.getMoreStuff(
result+1,
lambda result2: print(result2)
))
A lot of JS code used to look like this hideous monstrosity.Async/await version:
result = await server.getStuff()
second = await server.getMoreStuff(result+1)
print(result)
Remember again, that it is basically transformed by the compiler into the second form. result = await server.getStuff()
second = await server.getMoreStuff(result+1)
print(result)
`await getStuff()` MUST terminate before `await getMoreStuff() ` begins. So this chunk alone is analagous to synchronous code, unless we're in the middle of a spawned task, and there are other spawned tasks in the executor that can be picked up.Async/await is really popular in the JavaScript community because in web apps, you usually only have a single thread of execution which you share with the browser UI code. So if your code made a network request synchronously, the user might not be able to scroll or click links or anything until it finished.
Frankly, in the case of sequential flow like the above, I would rather write
result = server.getStuff()
second = server.getMoreStuff(result+1)
print(result)
and have the runtime automatically perform work-stealing for me. No need for awaits. They just litter the code. This is what Go does.Gevent in Python does something similar [implicit switching] using a dirty monkeypatching. It is great while it works. Sooner or later the explicit cooperative concurrency such as provided by async/await syntax wins (e.g., asyncio, trio, curio Python libraries)
Indeed, since you mention continuations, I'm sure you realize that they're more or less callbacks.
server.getStuff(gotStuff)
server.getMoreStuff(gotMoreStuff)
Just using functions is more simple and also more powerful.
A function being async usually means stuff will happen, things can go wrong, and you might want to do different things depending on the response or whether it failed.Where await is useful though is in serial execution of async functions that really should be sync, but them being async is an optimization in order to not block the thread.
It is really unfortunately that so much extra crud had to be introduced to JS (corutines, async, promises) in order to be able to await. Reading complex Promise based code is very unplesent, with async functions pretending to be pure, without any error handling, full of side effects, and omitted returns.
With callbacks we had inexperienced programmers writing pyramids of callbacks and if logic. But it was not that bad, as the complexity was in your face, and not hidden under layers of leaky abstraction.
You are correct. In edge cases where there is only 1 await in the queue for 1 process with 1 thread you gain nothing.
But you're accurately describing an edge case where await has limited value.
Await's true power shows up when you anticipate having multiple in-flight operations that all will, at overlapping points, be waiting on something.
Rather than consume the current thread while waiting, you're telling the run-time, go ahead and resume another task that has reached the end of its await.
This was possible before using various asynchronous design patterns, but all of them were clunky, in that they required boilerplate code to do what the compiler should be able to figure out on its own:
"Hey, runtime. This is an asynchronous call. Go do something useful with this thread and get back to me."
Second, await is MUCH EASIER for future developers to process because it looks exactly like any other method call and makes it easy to reason about the logic flow of the code.
Rather than chasing down async callbacks and other boilerplate concepts to manually handle asynchronous requests, the code reads like its synchronous twin.
int a = await EasyToFollowAsyncIntent();
This makes the code much easier to reason about.
To me those are the 2 biggest gains from async.
1. Less boilerplate code for asynchronous calls.
2. Code remains linearly readable despite being highly asynchronous.
If you have an async method that can wait for input on both devices, you can await the results of both of them, and they won't block eachother.
Async can be useful when more control over the details of execution is needed.
I've seen a lot of people try to manage complex programs by working with threads directly. Whatever they come up with is very unlikely to be as correct and reliable as the abstractions provided by the language. Even when they get it right, programs written with those techniques are difficult to modify without introducing new bugs.
Manual management of threads is becoming like manual management of memory -- it is discouraged by newer language features and you should only do if you really need to.
1. Get used to callbacks in NodeJS, for example write some code using fs that reads the content of a file, then provide a callback to print that content.
2. Get used to promises in NodeJS, for example turn the code in #1 into a promise by creating a function with that calls the success/reject handler as appropriate on the callback from opening that file. Then use the promise to open the file and use .then(...) to handle the action.
3. Now do it in async. You have the promise, so you just need to await it and you can inline it.
By doing it in the 3 steps I find it is more clear what is really happening with async/await.
I thought Rust had other, better ways to create non-blocking code so I don't understand why to use async instead.
[0] https://journal.stuffwithstuff.com/2015/02/01/what-color-is-...
Isn't the alternative WCiYF is proposing to allow the caller to treat any function asynchronously, while having no way to discern whether doing so might be counterproductive?
It's sometimes called "cold futures".
https://news.ycombinator.com/item?id=20676641
It's trivial to turn async into sync in Rust. You can use ".poll", "executor::block_on", et cetera.
Turning sync into async is harder in any language. Even Go with it's easy threading. That's a good argument to make async the default in libraries in Rust, but since async isn't stable yet, that would have been hard to do 5 years ago.
well in most languages you can wrap sync into async. so it's not "hard". it's just harder to have NON blocking code. i.e. in c# there is a difference between:
`await Task.Run(() => Thread.Sleep(5000));`
and
`await Task.Delay(5000);`
both will wait for 5 seconds but one will waste cpu cycles while the other won't.
It is not easy to do in a cirrect and performant way. "async" doesn't mean "code that runs in another thread". You can have a single threaded runtime running async code (that's usually the case for javascript).
The "async-ness" is in those cases provided by the use of non-blocking primitives for IO, network etc. If a function is making a blocking call to the file system even if you make it async it will not help since the main thread will still be blocked on that system call.
The performance will also be quite different: waiting for data on 10000 sockets in a non-blocking way is quite different from having 10000 threads doing the same.
Elixir's Task module (in the stdlib):
future = Task.async(fn ->
do_something_here
end)
...do_other_things...
result = Task.await(future, timeout)
Mixing it with the Enum library makes concurrency dead-simple (got I a junior dev dispatching concurrent tasks in scripts with confidence), at the expense of an ugly nested double lambda. some_list_of_values
|> Enum.map(fn value ->
Task(fn -> do_something_with(value) end)
end)
|> Enum.map(&Task.await(&1, timeout))This is largely why Python async took so long to mature, because so much inbuilt functionality was making IO operations transparently using core sync impls that locked up any async executor.
Console IO operations are actually message call to a "global group leader" which performs the operation, so they are async (and atomic). This can sometimes be confusing if an operation (such as logging) has a bunch of middlemen with an IO operation as a side effect. It's worth the atomicity, though, so none of your IO calls are interrupted by another IO call. Also, if you run a command on a remote node which dispatches IO as part of its own process, the IO will be forwarded back to its group leader (which is on your local node), which is useful for introspecting into another VM.
Disk IO is also different; each open file descriptor effectively gets its own "thread" that you send IO messages to. There are ways to bind a file descriptor directly to your current "thread", but you "have to be more careful when you do that" - you do that if performance is more important (and I have done this, it's not terrible if you are careful).
Network IO is also different; the erlang VM kind of has its own network stack, if you will, but you can set up a socket to be its own "thread" or you can bind a socket into a thread so that network packets get turned into erlang messages.
Handling blocking is all done for you by the VM, which is preemptive and tries to give threads fair share of the VM time.
When people say that programming the erlang VM is like doing everything in its own os, they aren't kidding. Except unlike linux, where your communications are basically limited, you get to interact with your processes via structured data types with coherent language (and also IPC calls are way cheaper than OS processes).
> Does Elixer overload IO operations to be async in async contexts?
Maybe the right way to answer this is: When in Elixir, presume everything is async.
This makes it a hell of a lot easier to reason about.
Is it 0-cost abstraction? I mean, is `sync_read` will compile to the same code like `async_read.poll`? Because turning sync into async is kind of trivial as well: just spawn new thread for that sync block.
- Create an epoll descriptor.
- Add my socket to that descriptor.
- Poll the descriptor for a readiness notification.
- Read the descriptor.
Those first three system calls weren't required in the synchronous version, and unless the read is large enough to overshadow them, they represent some additional cost. But that cost is required by the OS itself, not by Rust's abstractions.
Someone with more experience writing Mio code might want to jump in and correct me here though.
No, they don't. Goroutines have stacks, while Rust async code does not. Go has to start stacks small and copy and grow them dynamically because it doesn't statically know how deep your call stack is going to get, while async/await compiles to a state machine, which allows for up-front allocation. Furthermore, Go's M:N scheduling imposes significant costs in other places, such as FFI.
Besides, for the vast majority of apps, OS threads are not significantly different from goroutines in terms of efficiency. Rust doesn't have a GIL and per-thread startup time and memory usage are very low. It only starts to matter once you have a lot of threads—as in, tens of thousands of clients per second—and in that case it's mostly stack size that is the limiting factor.
This is not true for a use case with a lot of connections, additionally context switch cost a lot more now with all side channel attack mitigations on.
M:N threading was slower than 1:1 in Rust.
Sync is a rudiment of our close past. We use it when we need to shave off development costs.
> What you don’t use, you don’t pay for. And further: What you do use, you couldn’t hand code any better.
In that mind-set, it is completely okay that `sync_read` and `async_read.await` can totally compile to something different, as they abstract different things.
Boats has some more thoughts on this here: https://boats.gitlab.io/blog/post/zero-cost-abstractions/
Rust had legitimate reasons for taking the approach that they did. One can agree that they made the correct decision without excusing and obscuring the consequential costs.
Arguing that the problem doesn't exist if you only stick to functions of a single color isn't a rebuttal, it's an admission! But the fact of the matter is async functions have real limitations and costs, which is why they're not the default in Rust, which in turn is why any Rust program will always have some mix of differently colored functions. But, yeah, the fewer of one color and the more of the other color, the better. That's the point.
Maybe new code will be exclusively async and existing code will switch over.
Some (but not all) of which might even benifit from async... although graphics code has it's own solutions to many of these problems, and it certainly wouldn't be the bread and butter of your core render loop.
1) For performance reasons, your GPU consumes command buffers after a decent delay from when your CPU requests it. This means async logic crops up for screenshot/recording readbacks, visibility queries, etc. assuming you don't want to simply stall everything and tank your framerate.
2) New lower level graphics APIs expose the asyncronous logic of command submission more than ever before, limiting safe CPU access to memory based on what the GPU is still accessing. This sometimes spills into higher level APIs - e.g. bgfx buffer uploads can either take a reference to memory (fast) - which you must keep valid and unmodified for a frame or two (asyncronous, and currently difficult to expose a sound+safe API for to Rust) - or it can make an extra deep copy (perf hit) to pretend it's behaving in a more syncronous fashion.
3) Resource loading is heavily asyncronous. You don't want to stall a game out on blocking disk I/O for a missing minimap icon if you can just fade it in a few seconds later. I might not have 10,000 GPUs to drive, but I've certainly had 10,000 assets to load, semi-independently, often with minimal warning.
So yes, Rust still has colors, but it doesn’t matter because a red function can call a blue one without a problem and vice versa. You’re right in saying that async functions have a cost and shouldn’t be used indiscriminately - so just use them when it makes sense. As opposed to JavaScript, Rust doesn’t make you commit to one or the other early and either face major refactors in the future or pay the price of async when it’s not required.
P.S. I think there are some caveats for library authors and also to blocking the thread on a single future, but maybe more qualified people can comment on those.
Held, in 2015 but doesn't any longer since js had async/await.
This blog post isn't really interesting anyways, and its popularity mainly comes from the zealotry of gophers.
There are hacks like “deasync”, but I personally wouldn’t use it.
https://github.com/abbr/deasync
Rust can block on an individual future so, say, a sync callback can still take advantage of async functions.
What cannot be done is to perform a blocking call on a Promise from a sync function. And that is by design because JavaScript has a single threaded runtime.
Five years ago Rust still had green threads. Literally every standard library I/O function was async, and the awaits were always written for you with no effort.
Its literally taken five years to get back to an alpha thats not as good, and we'll still have to wait for a new ecosystem to built on top of it. I know not everyone writes socket servers and so forcing the old model on everyone probably doesn't make sense long-term, but I still have to shake my head at comments like this.
D made a similar mistake by requiring GC/runtime from start and now even though they added ways to avoid it the ecosystem and the language design are "poisoned" by it an itmakeas it a very hard sell in some places where it could be sold as a C++ successor.
Because rust made the right choice in time it's now a contender in that space, if it chose to go down the runtime required/custom threading model route it would have much less practical appeal. If you can swallow runtime/threading abstraction overhead why not just bolt on a GC and use Go
C++11 introduced a GC API in the standard library, and one of the biggest C++ game engine does use GC in their engine objects, Unreal.
C++ on Windows makes heavy use of reference counting (which is a GC algorithm from CS point of view), via COM/UWP.
The biggest problem to overcome is religious, not technical.
Not sure if Ref counting is a good example here, as there is no runtime monitoring the object graph hierarchy and of course Rust it’s self uses ref counting in many situations.
Reference Counting is a garbage collection implementation algorithm from CS point of view.
RC has plenty of runtime costs as well, cache invalidation, lock contention on reference counters, stop the world in complex data structures, possible stack overflows if destructors are incorrectly written, memory fragmentation.
The new I/O system is better in several ways. First, as you acknowledged, not everyone writes servers that need high scalability. M:N has no benefit for those users, and it severely complicates FFI. Second, async is faster than M:N because it compiles to a state machine: you don't have a bunch of big stacks around.
I'm not saying it was the wrong decision five years ago, but it definitely was a choice and there could have been a different one. I was responding to someone who said async wasn't an option five years ago.
M:N is the parallelization level. I'm actually not sure if Rust is M:1 or M:N or both based on configuration.
M is the number of concurrent process in the language, basically the number of user thread. These user threads can be implemented to be stackful or stackless, up to the language. The N is the number of OS threads.
At least that's always been my understanding.
It also was constantly crashing and had weird semantic issues. I very much prefer the current state, even if I'm a bit sad that async/await has taken us so long.
[0]: https://ziglang.org
The idea is that you can set the global "io_mode" mode to blocking, mixed or evented and I/O functions will switch their implementation accordingly. The type of the function will then, if I got that right, propagate up the call stack and turn functions that touch it transparently into either normal or async/awaitable funtions.
Nice way to avoid a bifurcation of the ecosystem into red/green functions. Its a bit magical maybe, any other trade-offs?
I mean, don’t you know at compile-time whether you want something to be async or not? If so, it should be handled by the type system, not by mutating a variable at runtime.
No thanks.
Edit: I just remembered that in cooperative multitasking, it's probably possible for the OS to safely save the program stack pointer, meaning the program doesn't have to unwind its stack when yielding, unlike async programs. Never mind, that makes the two models quite different. However, in practice, programs written for cooperative multitasking really should be structured just like async programs in order to be responsive (so users can, for example, interact with the GUI while downloading files in the background.)
Which one? It’s “cooperative” ie not unpredictable. The points where one can block are predictable and documented explicitly, otherwise how would the programmer know they won’t block forever. The same should hopefully be the case for async/awaitable apis.
In fact where async/await will actually give up control are harder to tease out.
The differences are really not as big as they would seem.
I don’t see how this increases overhead to deal with either.
Basically, coop multitasking and async/await operate on the exact same execution framework, the latter just gives convenient syntactic support.
Perhaps you should see how typescript turns async await into js.
[1] If implemented with care, not doing syscalls in the middle of async primitives and using fast nearly-O(1) algorithms for timers, etc. it can be incredibly fast. And of course Rust also gives enough room to mess up all that nice determinism.
So the event handler gets called immediately? No that’s not right. What would be the point of that? The event handler or continuation obviously needs to be scheduled on something that is awaitable. Meanwhile, other concurrent tasks may be able to run.
> This is the essence of asynchronous programming. There are no tasks, no yielding, practically no overhead and everything is deterministic
This is just totally wrong. Especially re tasks: https://docs.python.org/3/library/asyncio-task.html#creating...
There is nothing inherent about async and await that prevents “yielding”... the issue of yielding and semaphores is a concurrency issue and since async and await are used in concurrent programming environments, the same issues apply.
While it is true async and await don’t require any kind of cooperative concurrent framework to work, that is kind of their whole point for existing. A single task async/await system isn’t terribly interesting.
It's kind of like this: async/await is syntactic sugar for higher-order abstractions around event loops. At the level of event loops and event hadnlers there is no awaiting anymore. And the whole point of event loops is to not run event handlers concurrently, that's why they are even called loops, they invoke handlers one by one in a loop deterministically without concurrent tasks and once there is nothing more to run they just block and wait for new events. Obviously you can run multiple event loops in parallel, but you shouldn't share memory between them, as it defeats the purpose, is always slower and is never really necessary, you can just use asynchronous message passing to communicate between event loops when you have to.
> A single task async/await system isn’t terribly interesting.
And yet this is the whole point of async/await, promises, futures and event loops. All of them exist to avoid mistakes and performance problems of shared memory concurrency. I mean, really, if you have semaphores or mutexes in event handlers, futures, promises or async functions - you are in a broken concurrency model zone.
As far as I understand, cooperative is far more efficient than preemptive, but unsuitable for poorly written or untrusted code.
I wish to learn and would really appreciate your assistance if you are willing to help.
Well..
await new Promise((res, rej) => { setImmediate(res); })
(In environments without `setImmediate` this is easily shimmed - https://github.com/YuzuJS/setImmediate)In fact, Rust does have a great solution for nonblocking code: just use threads! Threads work great, they are very fast on Linux, and solutions such as goroutines are just implementations of threads in userland anyway. (The "what color is your function?" post fails to acknowledge that goroutines are just threads, which is one of my major issues with it.) People tell me that Rust services scale up to thousands of requests per second on Linux by just using 1:1 threads.
Async is there for those who want better performance than what threads/goroutines/etc. can provide. If you don't want to deal with two "colors" of functions, you don't have to! Just use threads.
"""Three more languages that don’t have this problem: Go, Lua, and Ruby.
Any guess what they have in common?
Threads. Or, more precisely: multiple independent callstacks that can be switched between. It isn’t strictly necessary for them to be operating system threads. Goroutines in Go, coroutines in Lua, and fibers in Ruby are perfectly adequate."""
What more do you need?
Say you have 1000 threads. To handle a request each one needs to make 50ms of external or DB calls. In one second, each thread can handle 20 calls. So you can handle 20k requests/second with 1000 threads. But Rust is so fast it can serve 500k requests a second. So with regular threads, you need ~25,000 threads. The OS isn't going to like that.
With async you can run a single thread per core, with no concurrency limits. So you get your 500k requests without overhead. With fibers you just run 20k fibers which is a little bit of overhead but easy to do.
This is the core reason everyone is pushing async and fibers in fast languages. When you can push a ton of requests/second but each one has latency you can't control, regular threads will kneecap performance.
In "slow" languages like Python, Ruby, etc, async/fibers don't really matter because you can't handle enough requests to saturate a huge thread pool anyways.
But yes, eventually, for very heavy cases (more than what I would call "high") you will want async/await.
With 8k stack for each, you can easy have 10k-100k threads in a low-end system
And IMHO the added code complexity is not worth the trouble.
The thing is, this is just that - your opinion, generalized as The Truth. But engineering is about making the right trade-offs. Often threading will be fine, you'll win simplicity, and all is good. But sometimes you really need the performance, or your field is crowded and its a competitive advantage. Think large-scale infrastructure at AWS, central load-balancers, or high-freq-trading.
Heh? Where?
With a simulated load of ~20 users we were running over 1000 threads.
Several posts in the chain say that 20k+ threads is "fine". Not unless you have a ton of cores. The memory and context switching overhead is gigantic. Eventually your server is doing little besides switching between threads.
We had to rewrite our s3 code to use async, now we can do many thousands of concurrent uploads no problem.
Other places we've had to use async is a proxy that intercepts certain HTTP calls and user stats uploader that calls third party analytics service.
Just sayin it's not that unusual to need async code because threading overhead is too high
proc readLine(s: Socket | AsyncSocket): Future[string] {.multisync.} =
while true:
let c = await s.recv(1)
case c
of '\n':
return
else:
result.add(c)
This is equivalent to defining two `readLine` procedures, one performing synchronous IO and accepting a `Socket` and another performing asynchronous IO and accepting an `AsyncSocket`. It works very well in practice.The main challenges I see are around usability within the language design on how best to propagate and compose them.
[0] https://www.reddit.com/r/rust/comments/cjcwmu/is_there_inter...
'async' exists because Python has that GIL bullshit and so Python programmers had to invent that fifth wheel of 'async programming'.
Programmers in other languages then got jealous because they, too, wanted a complex, unnecessary framework that pollutes the whole runtime and serves to differentiate regular programmers from 'rockstar' programmers.
And so async got fashionable and barely-literate coders now think async is magic performance dust that will automatically make your program run 1000% faster.
TL;DR - it's just fashion, give it five years and we'll be reading posts about how async sucks and that it's stupid legacy tech invented by bonehead dinosaurs.
C# introduced it in 5.0, which came out in August 2012. The Python proposal (PEP 3156) for an async library was posted in 2012, the proposal (PEP 492) for async/await syntax in 2015, and implemented in Python 3.4 and 3.5 respectively, I believe. So C# predates Python by about 3 years.
From what I can gather, Python was influenced by C#. But C# doesn't have a global lock, and that's not why it has async/await.
Edit: Added PEP reference.
But it's odd that they do not cite Tokio. I know this isn't an academic paper, but come on have some professional curtesy and discuss the contributions made in prior art.
Carl Lerche and the rest of the Tokio contributors deserve a citation.
I am curious if the number of threads is unbounded, or if they have a bounded set but accept deadlocks, or if there is a third option other than those two that I am unaware of.
There is no true async I/O on most (if not all) current platforms - it's all threads, either in user space or in kernel space. Sometimes even deliberately, for example polling disk will give better latency compared to waiting for IRQ.
https://docs.microsoft.com/en-us/windows/win32/api/fileapi/n...
Is there any further documentation for it? I would have expected there doesn't need to be a real stack. Only state-machines for all the IO entities (like sockets) which get advanced whenever an outside event (e.g. interrupt) happens and which then signal the IO completion towards userspace. Didn't expect that it's necessary to keep stacks around.
If you mean io_submit, then yes, but in vast majority of cases, actual `io_submit` syscall will block, because of metadata updates, unaligned reads, etc ...
Yes, I mean io_submit, which is what MySQL uses.
I can definitely imagine blocking happening while waiting for a worker to be available, though. Did you mean simply blocking instead of deadlock?
The same scenarios would lead to resource exhaustion if the thread pool wasn't bounded.
https://github.com/async-rs/async-std/pulls?utf8=%E2%9C%93&q...
Also, anything from the tokio ecosystem like hyper would not work with async-std.
Edit: I originally had a first paragraph which was wrong. I mistakenly thought std::net::TcpListener is supposed to impl Read / Write.
It does implement AsyncRead and Write, because anything with `Read` and `Write` implements it: https://docs.rs/async-std/0.99.3/async_std/io/trait.Read.htm... (that's sadly a little backwards by rustdoc)
The problem is that tokio has their _own_ versions of the AsyncRead and Write traits.
Hyper can best be used with `async_std` through `surf`: https://github.com/rustasync/surf
>impl<T: AsyncRead + Unpin + ?Sized> Read for T {
That's saying that anything that impls futures::AsyncRead impls async_std::io::Read. async_std::net::TcpListener does not impl AsyncRead. (Compare with TcpStream and File which do.)
>Hyper can best be used with `async_std` through `surf`: https://github.com/rustasync/surf
Sure. You also don't need surf since you can directly use futures's compat executor wrapper around tokio's. The point is that you can't use stuff like hyper without the tokio executor being involved.
Features like Haskell—destructuring bind, useful type system.
Performance like C, including no GC.
Makes it a good option when reliability and performance matter (think web browser, database or anything at the OS level).
I beg to differ. If anything, Rust is often cited as being hard to read.
A lot of the fancier stuff is very different, but there's fairly close parallels to most of the basic syntax.
Not to mention one could hand pick examples which is what I'd expect from slides of a talk.
So we need Rust for younger generations.
Rust code is littered with things like |_|, (|&(&x, _), &mut, &'a and Result<(), Box<dyn std::error::Error + Send + Sync>>.
It's anything but easily readable.
This is bunk. Simply run this search[1] and behold the stream of Rust related submissions that get no play at all; zero comments and no more than one or two up votes. These instances of highly ranked rust stories are actually the exception; no more than one or two a week typically. The rest of the Rust stuff is seen by almost no one.
[1] https://hn.algolia.com/?query=rust&sort=byDate&prefix&page=1...
The thing I like in Go is that I don’t have to worry about that, it’s all automatic.
Go is such a joy to work with.
It's not Go, but we know what people like about Go. <3
It exports stdlib types (like io::Error) where appropriate so that libraries working with these can stay compatible, so `no_std` is not really an option.
The underlying library (async-task) is essentially core + liballoc, just no one made the effort to spell that out, yet.
Excellent, good to know!
I would love to see a lint for known-blocking constructs in async contexts, though: https://github.com/rust-lang/rust-clippy/issues/4377
Also, having explicit imports and types that name collide helps there for once.
I meant: is that a real thing? Is there a database binding out on crates.io that uses no_std ?
That gap might close, but it will stay with us for years.
It would be nice if you could provide your own sys crate so you could even use some of std on an embedded device. If you had say an RTC you could make time related calls work, maybe you'd wire networking to smoltcp etc. Currently you could do that - maybe - but you'd have to modify the Rust standard library.
But that plan is severely understaffed, we go so much else to do.