State of Loom
cr.openjdk.java.net
cr.openjdk.java.net
This model of concurrency is so much better than the async/await model used by many other languages. No more colored functions [1], or worse Completable<Future>, promises et al. Nice stacktraces, debuggers that work plus no need for thread pools anymore. I can't wait for this to be ready for production.
Only drawback seems to be when calling native code. I guess it's the same problem that Golang has. Good thing is that the Java ecosystem is not that dependent on native stuff, so I think it's a fair tradeoff to make.
[1] https://journal.stuffwithstuff.com/2015/02/01/what-color-is-...
That's a property of the function, whether or not you want the type system to help you with it. I can call a function myRedFunction, but if it calls a blue function, it's blue.
> or worse Completable<Future> What is this? Future<Result> f = e.submit(() -> { ... return result; }); // spawns a new virtual thread
> This model of concurrency is so much better than the async/await mode
ThreadFactory tf = Thread.builder().virtual().factory();
ExecutorService e = Executors.newUnboundedExecutor(tf);
Future<Result> f = e.submit(() -> { ... return result; }); // spawns a new virtual thread
...
Result y = f.get(); // joins the virtual thread
Future<Result> f = async ( ... result; )
Result y = await (f);The problem is that in, say, C# or Kotlin, subroutines with the same semantics come in two different colours. The type system "helps" you distinguish between things that aren't meaningfully distinguishable.
> I don't get it. This just looks like async/await (submit/get) with extra steps.
You only need to submit if you want to do stuff in parallel and then join (also, there are no extra steps). The analogue to:
var a = await doA();
var b = await doB();
var a = doA();
var b = doB();(2) Can you give an example of an async and a non-async subroutine that have "the same semantics"?
2. sleep vs. delay in either C# or Kotlin.
How do you execute doA() and doB() concurrently? In C# you can do something like:
var t1 = doA();
var t2 = doB();
await Task.WhenAll(new[] {t1, t2});
var a = t1.Result;
var b = t2.Result;
Many of you are perhaps scratching your head and going "What? But of course I concurrently do multiple things all the time!" But this is one of those cases where you grossly overestimate the frequency of exceptions precisely because they are exceptions, and so they stick out in your mind [1]. If you go check your code, I guarantee that either A: you are working in a rare and very stereotypical case not common to most code or B: you have huge swathes of promise code that just chains a whole bunch of "then"s together, or you await virtually every promise immediately, or whatever the equivalent is in your particular environment. You most assuredly are not doing something fancy with promises more than one time per function on average.
This connects with academic work that has showed that in real code, there is typically much less "implicit parallelism" in our programs than people intuitively think. (Including me, even after reading such work.) Even if you write a system to automatically go into your code and systematically finds all the places you accidentally specified "doA" and "doB" as sequential when they could have been parallel, it turns out you don't actually get much.
[1]: I have found this is a common issue in a lot of programmer architecture astronaut work; optimizing not for the truly most common case, but for the case that sticks out most in your mind, which is often very much not the most common case at all, because the common case rapidly ceases to be memorable. I've done my fair share of pet projects like that.
The paper ParaSail: A Pointer-Free Pervasively-Parallel Language for Irregular Computations[1] contains the following excerpt.
"This LLVM-targeted compiler back end was written by a summer intern who had not programmed in a parallel programing language before. Nevertheless, as can be seen from the table, executing this ParaSail program using multiple threads, while it did incur CPU scheduling overhead, more than made up for this overhead thanks to the parallelism “naturally” available in the program, producing a two times speed-up when going from single-threaded single core to hyper-threaded dual core."
One anecdote proves nothing but I'm cautiously optimistic that newer languages will make it much easier to write parallel programs.
I want to emphasize that what was discovered by those papers is that if you take existing programs and squeeze all the parallelism from them you possibly can safely and automatically, it doesn't get you very much.
That doesn't mean that new languages and/or paradigms may not be able to get a lot more in the future.
But I do think just bodging promises on to the side of an existing language isn't it. In general that's just a slight tweak on what we already had and you don't get a lot out of it.
If you just need to wait for both to finish, something like this should do it:
var t1 = startA();
var t2 = startB();
var a = finishA(t1);
var b = finishB(t2);
The distinction is important though, because it affects the observable behaviour of other effects present in these functions. https://glyph.twistedmatrix.com/2014/02/unyielding.html
The only cases where you want the same function to come in two colour variants is when it's a higher-order function, and in that case what you really want is not to ignore colour but for the function to be polymorphic over colour. (i.e. higher-kinded types).
Only if the language is single-threaded to begin with, like JavaScript.[1] There is no real difference in C# and Kotlin between, say, sleep and delay. It's a syntactic distinction between semantically equivalent terms (for all practical purposes).
[1]: Even then there are better ways to reason about effects.
The difference in the native call case isn't semantic; it's, at worst, a difference in performance [1], and as far as I know, no one is making that distinction today, so there's nothing to erase. Moreover, as Java doesn't have async/await, there isn't even an artificial distinction to erase.
I don't know all the reasons Java abandoned green threads. One of them was that the classic VM that had green threads was simply replaced with HotSpot; it wasn't an evolution of a single VM. But more practically, and putting aside the fact that it was M:1, at the time there Java code relied on native FFI a great deal, whereas today it is very rare in general.
[1]: This is a little inaccurate. There could be a difference in liveness properties (deadlock) in that case, but neither async/await nor kernel threads, for that matter, make intrinsic liveness guarantees. You have to trust your scheduler in all cases.
You do have that control: the value of having explicitly async functions is that it becomes possible to have non-async functions (just as the value of having explicitly nullable values is that it becomes possible to have non-nullable values, and the value of having explicitly-exception-throwing functions is that it becomes possible to have non-exception-throwing functions). A non-async function is nothing more or less than a function that is guaranteed to execute on a single native thread, whereas an async function might be executed over multiple native threads; in particular after `val x = f()` execution will continue on the same native thread as before, whereas after `val x = await f()` execution might continue on a different native thread.
I hope it works out, but there just seems to be so much opportunity for unforeseen edge cases; something very fundamental and global that every (post-1.2) Java programmer is used to knowing will no longer be true.
That async/await allows this implementation detail to leak is not a feature, it's a bug. It forces a syntactic distinction without a semantic difference (well, it introduces a semantic difference as a bad side effect of a technical decision -- the semantic difference is that you can observe the current thread changing underneath you, which, in turn, makes the syntactic difference beneficial; in other words, it's a syntactic "solution" to a self-imposed, avoidable problem).
You're putting the cart before the horse. On the assumption that the programmer needs to be able to control native threading behaviour in at least some cases (if only a small minority), surfacing the details of the points at which evaluation may cross native thread boundaries is useful and important, and async/await is the minimally-intrusive way to achieve that. If it's really possible to abstract over the native threading completely seamlessly such that the programmer never needs to look behind the curtain, then async/await is pointless syntactic complexity - just as if it were possible to write error-free code then exceptions would be pointless syntactic complexity. But if there's still a need to control native threading behaviour then this is going to end up being done by some kind of magic scheduler hints that aren't directly visible in the code and will be easy to accidentally disrupt by refactoring, and in that case I'd rather have async/await (as long as I've got a way to be polymorphic over it).
The only place where this could be important is when dealing with Java code that cares about the identity of the native thread by querying it directly (because native code will see the native thread, but it's hidden from Java code). But, 1. such code is very rare, 2. almost all of it is in the JDK, which we control, and 3. even if some library somewhere does it, then that particular library will need to change to support virtual threads well, just as we require for most new big Java features.
Having said that, I don't claim async/await isn't a good solution for some platforms, and in some cases there's little choice. For example, Kotlin has no control of the JDK, which is necessary for lightweight threads, and languages with pointers into the stack as well as no GC and lots of FFI might find that a user-mode thread implementation is too costly. But I think that in cases where usermode threads can be implemented efficiently and in a way thar interacts well with the vast majority of code, they are clearly the preferable choice.
I'm thinking of when you need to "pin" to a particular native thread. In a native-threads + async/await language you have direct and visible control over where that happens. In a green-threads language it's going to involve magic.
> Having said that, I don't claim async/await isn't a good solution for some platforms, and in some cases there's little choice. For example, Kotlin has no control of the JDK, which is necessary for lightweight threads, and languages with pointers into the stack as well as no GC and lots of FFI might find that a user-mode thread implementation is too costly. But I think that in cases where usermode threads can be implemented efficiently and in a way thar interacts well with the vast majority of code, they are clearly the preferable choice.
A priori I agree. I expected green threads in Rust to work out too. I just can't get past having seen it fail to work out so many times. Maybe this time is different.
No magic, just a custom scheduler for that particular thread. For example:
Thread.builder().virtual(Executors.newFixedThreadPool(1)).factory();
> I expected green threads in Rust to work out too. I just can't get past having seen it fail to work out so many times. Maybe this time is different.
Implementing usermode threads in Java and in Rust is very different as their constraints are very different. Here are some differences: Rust has pointers into the stack, Java doesn't; allocating memory (on stack growth) in Rust is costly and needs to be tracked, while in Java it's a pointer bump and tracked by the GC; Rust runs on top of LLVM, while Java controls the backend; Rust code relies on FFI far more than Java. So both the constraints and implementation challenges are too different between them to be comparable.
Not to mention that they have different design goals: Rust, like all low-level languages, has low abstraction (implementation details are expressed in signatures) because, like all low-level languages, it values control more than abstraction. Java is a high-level language with a high level of abstraction -- there is one method call abstraction, and the JIT chooses the implementation; there is one allocation abstraction, and the GC and JIT choose the implementation -- and it values abstraction over control. So whereas, regardless of constraints, Rust happily lives with two distinct thread-like constructs, in Java that would be a failure to meet our goals (assuming, of course, meeting them is possible).
There are many things that work well in high-level languages and not in low-level ones and vice versa, and that's fine because the languages are aimed at different problem domains and environments. Java should be compared to other high-level languages, like Erlang and Go, where userspace threads have been working very well, to the great satisfaction of users.
Having said that, I suggest you take a look at coroutines in Zig, a language that, I think, brings a truly fresh perspective to low-level programming, and might finally be what we low-level programmers have been waiting for so many years.
But there's a spooky-action-at-a-distance between that scheduler and the code that's running on the thread. Code that's meant to be pinned (and may behave incorrectly if not pinned) looks no different from any other code.
> Not to mention that they have different design goals: Rust, like all low-level languages, has low abstraction (implementation details are expressed in signatures) because, like all low-level languages, it values control more than abstraction. Java is a high-level language with a high level of abstraction -- there is one method call abstraction, and the JIT chooses the implementation; there is one allocation abstraction, and the GC and JIT choose the implementation -- and it values abstraction over control. So whereas, regardless of constraints, Rust happily lives with two distinct thread-like constructs, in Java that would be a failure to meet our goals (assuming, of course, meeting them is possible).
Java isn't positioned as a high-level, high-abstraction language and that's not, IME, the user community it has. It's a language that offers high performance at the cost of being verbose and cumbersome - witness the existence of primitive types, the special treatment of arrays, the memory-miserly default numeric types, the very existence of null. I've heard much more about people using Java for low-latency mechanical-sympathy style code than people using it for high-abstraction use cases like scripting or workbooks. It's always been advertised as a safer alternative to C++ - rather like Rust.
(I'm all for trying to expand Java to be useful in other cases, but that's not grounds to sacrifice what it currently does well. For all the criticism Java attracts, it is undeniably extremely successful in its current niche)
Same goes for async/await. The decision to keep you running on the same native thread is up to the scheduler.
> Java isn't positioned as a high-level, high-abstraction language and that's not, IME, the user community it has.
I beg to differ. It aims to be a good compromise between productivity, observability and performance. Every choice, from JIT to GC, is about improving performance for the common case while helping productivity, not improving performance by adding fine-grained control. There are a few cases where this is not possible. Primitives is one of them, and, indeed, 25 years later, we're "expanding" primitives rather than find some automatic way for optimal memory layout.
> It's always been advertised as a safer alternative to C++ - rather like Rust.
I think you're mistaken, and in any event, this is certainly not our position. Java is designed for a good blend of productivity, observability and performance, and unless the circumstances are unusual, it opts for improving common-case performance with high abstractions rather than worst-case performance with low abstractions like C++/Rust. Roughly speaking, the stance on performance is how do we get to 95% with the least amount of programmer effort.
Anyway, regardless of what I said above, the constraints on the design of usermode threads other than philosophy are also very different for Java than for C++/Rust for reasons I mentioned. Still, Zig does it more like Java (despite still using the words async and await, but they mean something more like Loom's submit and join than what they mean in C#): https://youtu.be/zeLToGnjIUM
The scheduler decides what happens at each yield point, but code that doesn't yield is guaranteed to stay pinned to a single native thread. A non-async function is somewhat analogous to a critical section; the difference between async and not is a visible distinction between must-run-on-a-pinned-native-thread functions and may-be-shuffled-between-native-threads functions.
Are these semantically the same?
Runnable action1 = () -> System.out.println("foo");
Runnable action2 = () -> System.out.println("bar");
action1.run();
action2.run();
var action3 = runAsync(() -> System.out.println("foo"));
var action4 = runAsync(() -> System.out.println("bar"));
action3.join();
action4.join();
I'm not comparing parallel to sequential. My point was that we're already doing parallel programming:
CompletableFuture<Result> fx = CompletableFuture.supplyAsync(() -> result);
CompletableFuture<Result> fy = CompletableFuture.supplyAsync(() -> result);
Result x = fx.join();
Result y = fy.join();
// > plus no need for thread pools anymore.
ThreadFactory tf = Thread.builder().virtual().factory();
ExecutorService e = Executors.newUnboundedExecutor(tf);
// > No more [...] Completable<Future>, promises et al.
Future<Result> fx = e.submit(() -> { ... return result; });
Future<Result> fy = e.submit(() -> { ... return result; });
Result x = fx.get();
Result y = fy.get();
fx <- async (return 3)
fy <- async (return 3)
x <- wait fx
y <- wait fyNo, but that's not what I meant. These are semantically the same:
action1sync();
action2sync();
await action1async();
await action2async();
The excitement is about going from my second example to the first.
> Especially when other languages look like:
It doesn't matter what they look like in the code. They suffer from all the problems I mention in the article: exceptions lose context, debuggers and profilers lose their effectiveness, APIs are split into two disjoint worlds. Virtual threads gives you code that doesn't just look synchronous, but behaves like that in every observable way.
What the code looks like on the screen is a very small portion of the problem we're trying to solve.
Second, Java doesn't have async/await today. If Java was to introduce it, it wouldn't be compatible with the code written today. The big benefit of project loom is that code written today will get all the benefits of async/await without changing any code. In fact, because it's not important to pool threads, it actually gets easier.
The big problem with async/await in languages like C# or even coroutines in Kotlin is that it doesn't mix with the "old" api. The get the benefits you need to do a huge refactor of your code, and you need to make sure that any library you pull in is compatible.
Java's approach seems much better.
def sync_foo():
task = async_bar()
loop = asyncio.new_event_loop()
return loop.run_until_complete(task)
task.RunSynchronously()
There’s a split, because every step of an async process has to be async/await compatible or you lose all benefit. In a small code base, this might not be a big problem. Where I work it will never realisticly be done.
With project loom we won’t have to do anything or learn anything new. Just upgrade the java runtime and everything just works better :)
But yeah, the magic is: All code is now implicitly async (except native calls) - as if all code always had async in it's signature. Just - there is no need to now add this to the signature.
because altering the underlying thread pool can convert all existing code to fibers without syntax changes. This is the crux of "colored functions", two different signatures for async/non-async.
The implications for improving the performance of existing code are enormous. Most Java API's give you at least indirect control of the thread pool used. Which means they can be converted to fibers without updating the library.
In Java, executors are basically thread pools. If you can update the executor to use fibers the rest of the code is using fibers now. Your second example only converts a single call site to fibers. A thread pool could be used in hundreds of places.
In practice, this is a huge difference. I can update my Streams to use a fiber pool, and all across my app the hundreds/thousands of streams are using fibers now. Same story with REST and DB access. There's usually a single thread pool for each. A few lines of code to update the pools and my REST and DB calls are all using fibers.
It could have been so much better.
As for C#, some kind of fibers appear to have been considered but deemed too hard or not worth the trade-offs. See here: https://github.com/dotnet/runtime/issues/11084
The acceptable alternative was, apparently, forcing to programmers to litter their code with words such as async/await/task in-between the words and symbols that actually describe the purpose of their program, should they want to take advantage of non-blocking IO. All the way throughout the call-stack, nonetheless. And you also get crap like this: https://github.com/dotnet/corefx/pull/4868
This points at the bigger problem that every implementation of green threads has: it breaks interop unless everybody buys into it. Async/await is fundamentally callback-based, which can be represented nicely even in C ABI - so literally any language that can interop with C, can interop with an async/await model, with execution flow asynchronous throughout the entire chain. Runtimes that choose to roll their own green threads, like Go, and I guess now also Java, are effectively stating that their convenience is worth the inability to interface well with async code outside of their runtime.
> Runtimes that choose to roll their own green threads, like Go, and I guess now also Java, are effectively stating that their convenience is worth the inability to interface well with async code outside of their runtime.
You'd still be able to interop with async code outside of runtime, you can still model the API as callbacks for the interop purposes where needed.
But yes, interop has sam trade-offs. Which are, IMO, entirely correct trade-offs to make for Go, Java and .NET (and overwhelmingly so). But they are probably not for (as an example) Rust, according to it's goals.
Can you maybe recommend a good overview over all the current concurrent approaches and concepts, like async/await, and alternatives, and their advantages and problems? I would love to get a more recent overview on this.
I had the impression that most recent languages follow on the async/await concept. At least JS and Python. Maybe also Rust? Go? Erlang? And there are probably libraries for C++ to do the same, or maybe it is already integrated? I have to admit that I did not fully follow all this development.
When project loom is implemented in Java, all code which makes use of threads today automatically gains all the benefits of the async/await model, without any refactoring.
Go and Erlang doesn't do the async/await thing. They only have one notion of concurrency (goroutines in Go, processes in Erlang). They don't require you to use async and await constructs, but they work similarly to async/await under the hood.
The problem is that your split-up async function ceases to be a normal function. It doesn't use the stack in a similar way than normal functions. Furthermore, the executor / event loop is required for running those async functions.
So you can't call async functions from normal functions, because they aren't. You need to create an event loop and then hand the task over for it to process it. Your world splits up into sync and async functions.
Go and Erlang are going with the similar "lightweight thread" approach as Java's project Loom. On the other hand, JS, Python and C# have gone with async. I'm not sure if these languages actually need async, going with something similar as project Loom would have also fit, and would have been simpler from the user perspective, perhaps? But hindsight is 20/20.
Rust has also gone async, and I'd argue it's the only one of the pack who really have async/await as a necessity - this is because of two design requirements that differ from Java, C#, Python and JS: 1) must have native-level performance when calling foreign code that expects a C-like stack. Something like Loom doesn't provide that. 2) must not have an implicit default runtime.
Have you taken the CLR (a.k.a. .NET / C#) async await for a spin? Microsoft's done a great job of squaring away those details so the stack/thread discontinuity doesn't much matter.
Coming from Java to JavaScript, I really, really yearn for the equivalent of ThreadLocals. For example, most Java logging libraries let you set a "context" object that can be used for logging a request ID or user ID anywhere down the call stack. You can't do that in Node, so instead you have to explicitly pass that context object down in all your function calls, or make use of brittle, complicated, hacky, not-fully-supported features like "continuation local storage".
Debugging stack traces in an async/await world is a mess because you don't get a nice "from the start of the request down to this call" view of the stack.
Perhaps most importantly, with Node at least you need to worry about starving your main event loop because there is only a single top-level main thread (but understand that's not inherent to the async/await issue in general).
While I understand why you feel that way today, you may find yourself some point in the future deeply, deeply detesting ThreadLocal. Sure it seems all convenient but all hell breaks loose when you need to use a threadpool, a future, an actor model...
Similarly, for the stacks, it's largely a tooling issue - if the debugger understands async, and the framework retains enough information about the origin of the promise, it can re-create the original stack trace, and combine it with the current one - .NET debuggers in VS and VSCode do this, as well, and WinRT even does this for C++.
For example, in Python you have this http client library called `requests`. It's very easy to use, but it is synchronous and you can't use it in when doing async/await. Instead you have to use a similar library called aiohttp. And it's like that for every single library or function doing any sort of IO, you need two versions of everything. Same thing happens in Node.js. You have `spawn` which is asynchronous and `spawnSync` which is synchronous. And so on.
And it doesn't stop with functions, this division goes across the language it self. For example in Python you have a `for` loop and an `async for` loop. Same in JS, you have `for` and `for await`. C# also has it's own `await forech` construct. It's like splitting the world for no reason.
The great advantage of Loom is that you don't need a parallel language, you can use the same http clients, database clients, filesystem libraries that you were using in a synchronous world, but now you will be able to use concurrently in millions of virtual threads.
As the article mentions, the whole reason why async/await was invented, is because doing concurrency with kernel threads is very expensive. They are slow to create and they use a lot of memory. Using Promises and an event loop you can run multiple concurrent operations in a single OS thread. This gives you the chance to achieve much more concurrency than running one operation per OS thread. The problem is that this changes the way you program a lot. Your code is not sequential anymore, your error handling is different, even some conditional operations are different. Async/await is just some syntactic sugar created to make this looks like the regular programming model. It makes the function calls look sequentials (by adding an `await` prefix), it makes the errors look like exceptions, it makes the for loops look like regular for loops. But this is just appearance. It's something that looks similar, but it's different, and that's why you can mix it with regular code.
Loom model is closer to Go and Erlang.
Others have given actual explanations, but I'll chime in with a bit of a tongue-in-cheek one: it's better than async/await because it doesn't have async/await (yet has all the benefits provided by them).
As much as I want a more expressive language, all the explicit async/await, futures, callbacks, etc. junk needed just for your API handler to cooperate with concurrent requests (not even do its own parallel processing) keeps on sending me back to Go. I look forward to being able to write Java in the same style.
What I really like about this project is that we can keep Spring MVC applications in non-reactive form. Spring MVC came out with reactive framework for implementing APIs. But I'm not a fan of this style for a few reasons, plus there is millions of LOC doing it the non react implementation. By utilizing project Loom, we do not have to switch over to the Spring reactive way, and we can increase the performance of existing code.
EDIT: Here is the video: https://www.youtube.com/watch?v=Csc2JRs6470:
- he goes into Loom at 19:30.
- he goes into the demo at 24:00.
To explain: if you debug async code on Kotlin right now, you cannot single-step in a debugger, because the debugger attaches to a thread. But coroutines get scheduled on different threads all the time!
I wonder what this means for ThreadLocals and Locks? Will they work as before? If so, that is huge! Because locks don't work with async code either, for obvious reasons. The consequence is that the whole ecosystem is split in two parts! You cannot just use a Guava cache in Kotlin coroutine-based code.
If Loom manages to avoid all of this, this is fantastic news.
Yes. You can try that today: http://jdk.java.net/loom
Go was the first to solve colouring but they have it seems a less type safe solution
Not without a syntactic distinction, and not without losing the performance characteristics you want coroutines to begin with.
> By colorless we mean that you can use a suspend return type directly and not through the ugliness of a promise.
That's not colourless. Colourless means that there is no syntactic distinction between sleep and delay. Two subroutines that mean the same but have a different syntactic colour.
> kotlin could have had no suspend keyword and be officially colorless,
It could not. You'd need to control the JDK to do that, or depend on class reloading, or pay a very high price in performance. Not to mention that it still wouldn't help when calling Java code (directly or indirectly) nor would it change how, say, JFR observes your program.
The problem is that Kotlin has very little influence over the platforms it targets -- Java, Android, JS and LLVM (well, maybe it has some influence over Android) -- and so must do its best to implement its functionality on top.
> I believe the best of both worlds
We don't want two worlds. We don't need two worlds. We want one that behaves as it should.
The point is that functions themselves don’t come in sync or async flavors. Just like in Java.
You call the queues blocking, but they aren't really in the sense of "blocking" usually used when talking about async in Rust. The Go runtime can and will preempt your Go code in the middle of waiting for a channel to run some other task, and this preemption is what makes it different from a blocking Rust channel. An async Rust channel will also make the calling function wait for messages when you await the receive method.
Basically my point is that because any Go code can be preempted at any point, that makes all Go code async. The language not making you type await on everything doesn't make it sync.
This is partly why the Go library ecosystem insists on rewriting everything from scratch in Go, instead of wrapping native libraries.
Indeed, Java itself had green threads (only!) in the first couple of versions.
Because functional programming requires loops to be written as recursive function calls, you can't do too much without calling/leaving a function, so a process can't avoid premption.
Which it might continue to be. As Kotlin needs to support other backends than just the JVM.
As pointed out elsewhere this won't really help you in any way in this situation.
Is there something in particular about the JVM that makes it more difficult, or is it just that the work hasn't been done yet for some reason?
https://stackoverflow.com/questions/15410661/is-it-possible-...
I thought this was weird because IIRC Java 1.0 used green threads in Linux and it was a big deal when they moved to OS threads.
I’ve long believed that the IT world moves in cycles but this is a very clear example of exactly that. Java has gone from green threads to Posix threads and now back to green threads.
I do think it’s awesome (I love goroutines) and Threads in Java have become a but of a nightmare, made a little easier with executors and CompletableFutures. So this further improvement is great news.
But still... call me when the builder pattern is dead.
What Loom and Go do is to schedule green threads on a bunch of system threads and spawn more system threads when they get blocked doing synchronous system calls.
(And if you want to be pedantic, IIRC the green threads were originally mapped to the Java process, not a thread, because threads were either unavailable or immature in Linux when Java 1 came out; I can’t remember which)
The green threads on the JVM were not the same kind as green threads in Go (and Loom), they would block on IO. Can't speak for Loom, but Go automagically reschedules your green thread when it blocks which allows other threads to run while waiting.
The point is they weren't rescheduled when they would block in the JVM, every process has a main thread.
But I find the cycle - what I called the hype cycle - from internal scheduling to external scheduling and back again, interesting, and I wonder what, if anything, we as an industry can learn from this?
ISTM that Java 1.2 could have improved on green threads instead of moving to os threads. So, is there something we can learn from these two transitions that will help us all make better decisions in the future? The use of OS threads and all the complexity that this has caused has cost the industry hundreds of thousands of hours of developer time. If we can learn some lessons from this then isn’t that a good thing?
1. Threading got much faster and lightweight. This is what Java was initially trying to work around, until it didn't have to any more.
2. The problem moved to handling as many sockets concurrently as possible. Even lightweight system threads are too heavy for scaling linearly with the number of connections (too much context-switching overhead, too much space for stack, etc.)
Green-threading has become a good idea again because we now have a kernel API that is used to multiplex a lot (but not all) I/O systemcalls.
Today Go runtime uses epoll/kqueue to read from a big bunch of sockets, whenever something new happens to any of them. This takes one system thread only.
The API model of epoll/kqueue implies some way to handle concurrency in your user code: this can either be callbacks (or async/await syntactic sugar) or green threads and CSP (channels and so on.) This is why green threading is having a comeback.
(Sorry for implying you did not read the article!)
> Green-threading has become a good idea again because we now have a kernel API that is used to multiplex a lot (but not all) I/O systemcalls.
OK, that makes a lot of sense. I had to read up about how epoll is different from select/poll (that's how long it's been since I worked in C :). Clearly epoll was needed to make green threads efficient, but from what I can see, by the time epoll and friends were widespread, the pthread model was entrenched in Java.
No it’s not the same thing - Java was previously M:1, then became M:M, and now Loom is M:N and also preserves M:M at the same time.
It’s a comment on the hype cycle. As a long time (since 1.0!) java developer, I like that Java has adopted a more efficient threading model. But they are certainly returning to a state where the JVM manages the threads rather than the OS, which certainly is the same as the original release, at least on Linux.
So it's more circumstance and necessity than hype.
Today, green threads are faster. Have os threads become slower? Not that I know of. All that’s really changed is how green threads are implemented.
We went from “green threads bad os threads good” to “os threads bad green threads good”. Sure, the new green threads are better than the old ones, but in some alternate universe maybe we could have got here without os threads (and maybe saved hundreds of thousands of hours of developer time in the process).
To me, what’s interesting is that this appears to be a case of evolutionary “local maxima”. Java went from green threads to os threads because os threads gave better performance for the amount of effort expended. But now we’re moving back to green threads - at much greater effort, 20 years later. I’m sure I’m not the only person that wonders what lessons we can learn from this?
Green threads employed only one kernel thread so couldn't take advantage of multicore, and at the time Java relied on native code so much more than today.
> but in some alternate universe maybe we could have got here without os threads
Maybe :)
> But now we’re moving back to green threads - at much greater effort, 20 years later
These aren't green threads but M:N, and I don't think it's a much greater effort than the effort that would have been required to add it to HotSpot back then.
The first green threads implementation, which was of course Java 1.0, was certainly M:1 - my memory is that we didn't even have pthreads in linux at the time - but the term today doesn't specifically mean a M:1 mapping.
On the other hand, of course JVM1.0 invented "green threads" which was M:1. So yeah this is confusing and I made it more confusing. Sorry. :)
So the point I was trying to make is that Java originally scheduled threads in userspace, then delegated scheduling to the OS, and has now taken it back. In hindsight it seems that delegating this key function to the OS has caused a lot of pain, and I'm interested in the drivers for using OS threads instead of just making the original green thread implementation better.
To be even clearer, I see this a lot in software. We delegate some key function of a product (like database access) to some inefficient and complex machinery (like an ORM) and then spend years working around the problems that decision caused. I've done this myself. I'd like to understand how to stop doing it.
I don't know all the reasons behind abandoning green threads, but some are mentioned here: https://docs.oracle.com/cd/E19455-01/806-3461/6jck06gqe/inde... namely, no multi-core and bad FFI ("interoperate with existing MT applications"). Plus, a little later, the transition to HotSpot left little desire to reimplement userspace threading. There was no pressing need, there was other, higher-priority work needed, and FFI was still an impediment. In other words, making green threads better was neither an important requirement nor a reasonable possibility back then.
Why have we "gone back"? 1. the scale of concurrency required today is higher and resulted in the scaffolding I mention in the article, 2. FFI is no longer an impediment as Java code rarely relies on native code these days.
Nevertheless, Project Loom doesn't switch from kernel to userspace threads, but rather lets you choose which implementation you want for each thread.
We aren’t moving back! Back then it was M:1. We're now moving to M:N/M:M.
You’re making it sound like we’re reverting to the previous design or implementation. Neither is true.
(Also, IIRC Linux didn't even have native OS threads when Java 1.0 came out, so M:1 was literally and the only option available in Linux at the time. My memory is that we had to wait for pthreads before we could have hotspot on Linux, but it's a long time ago and quite tangental to my point).
This is where you're getting confused.
This wasn't an 'intervening decision' because we haven't removed it and with Loom the OS is still able to schedule your threads. The user-space threads are opt-in. That's why it's not a reversion. Because Java was never like this before.
A small caveat is that Erlang has a Refc binary type that is reference counted, when sending a message with a refc binary to another process on the same node the content isn't copied, just the reference value (like a pointer) and the reference count is incremented.
There is an area where copies could potentially be avoided, but I don't think they are. Recent versions of beam have an optional off-heap message queue feature; some software patterns have a proxy process that accepts messages and sends them as-is to another process; if the message is off-heap for the proxy process, and it would send to the next process off-heap, it could be possible to avoid copying it, but it might be a bit tricky. (I don't think this is done, but that's why I said AFAIK earlier)
https://news.ycombinator.com/item?id=17646169 from 2018
https://news.ycombinator.com/item?id=15599854 from 2017
https://news.ycombinator.com/item?id=23194215 - 3 comments from a few days ago
Moving this slow is why the implementation is much better than the same in C#, Kotlin, or JS.
I think I proposed this at a crazy idea talk at VEE a long ass time ago (10 years or more). It’s still a good idea but I guess not crazy anymore.
Does anyone have a reference to some up to date notes on the state of scalability of Linux and/or free-/dragonfly-bsd scalability at the process level?
I don't doubt processes are a bit heavy for scaling to a million active threads of execution - but it'd be nice to see what one could expect on a low end server (say 16 cores, 64gb ram) today?
Best reference I could easily find was this experiment that had 100k connections to mysql which has thread per connection model. Seems to handle it well
https://www.percona.com/blog/2019/02/25/mysql-challenge-100k...
There is an early access [1]
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As for having in in JDK17, Ron provides an answer in the reddit thread [2]
[2] https://old.reddit.com/r/programming/comments/gkgzld/state_o...
I often wish the language had adopted it instead of the C#-like await async, since it’s just more straightforward.
I would consider myself a pretty harsh critic of Python but even I appreciate the elegance of the gevent approach to concurrency.
...and eating it too
Thread.startVirtualThread(() -> {});
Task.Run(()=>{})
Optionally you can decide to opt into the await unboxing sugar by adding async to your method signature. There's arguably some double dipping with the async keyword on a method. It allows the await keyword to be used inside the method but also forces the caller into a different calling style. You can argue this shows API intent for cooperative threading. That said, you can still use async and sync interchangeably.
The syntax seems very similar to me.
Is there something else going on in Loom that I'm missing? Is it a matter of how the virtual threads are scheduled/preempted vs how other languages with async/await schedule their tasks?
Loom with "Thread.startVirtualThread" will run something on a userland / green thread (ie. not a kernel thread so no context switching and blocking it "costs" practically nothing). async-await is actually a subset of wat Loom does in the sense that Loom allows for far more then just async-await. Most of the "hate" for async-await is probably because it leads to the "what color is your function" [1] problem.
[1] https://journal.stuffwithstuff.com/2015/02/01/what-color-is-...