The system property jdk.tracePinnedThreads triggers a stack trace when a thread blocks while pinned. Running with -Djdk.tracePinnedThreads=full prints a complete stack trace when a thread blocks while pinned, highlighting native frames and frames holding monitors. Running with -Djdk.tracePinnedThreads=short limits the output to just the problematic frames.https://github.com/jasync-sql/jasync-sql/wiki/API-Overview
From project WIKI (https://github.com/jasync-sql/jasync-sql/wiki)
The designers of Project Loom would say the exact opposite. The whole push behind Project Loom and similar models (Go's oft-praised "goroutines" runtimes being another one) is motivated by Threads being a much better fit for async behavior in a fundamentally procedural language like Java or Go than promise-based frameworks like async/await.
The whole motivation of Project Loom is to make the simple thing (spawning threads to handle blocking IO) the fast thing as well (by actually replacing the blocking IO with efficient async IO OS calls and managing the threads internally). Project Loom will be considered a full success if the next generation Java web server does something akin to "new Thread(() -> {executeHandlerFunc(conn); }.Start(); " for each incoming connection, just like the Go built-in web server.
My understanding is that that highest performance webserver is nginx. And it uses async internally.
IMO, virtual threads is a better general purpose language feature because it avoids function coloring and is generally easier to reason about, but it may not result in the highest performance Java webserver.
The purpose of project Loom is to abstract that away from Java application code. The runtime can use the most efficient IO for the given platform (ideally io_uring on Linux or IOCP on Windows, for example) even if the application code calls the old blocking File.Write(). The application can then use simple APIs and code patterns, but still get massive performance.
With Loom, you can easily have 20,000 virtual threads servicing 20,000 concurrent HTTP requests and each "blocked" in IO, while only using, say, 100 OS threads that are polling an IOCP. A normal Linux box can typically only handle around maybe 1000 threads across all running processes.
For example, this program:
var threads = new Thread[20000];
for (int i = 0; i < 20000; i++) {
threads[i] = Thread.ofVirtual().start(() -> {
try {
Files.copy(FileSystems.getDefault().getPath("abc.txt"), System.out);
} catch (IOException e) {
System.err.println("Error writing file");
e.printStackTrace();
}});
}
for (int i = 0; i < 20000; i++) {
threads[i].join();
}
Run as `java Test > ./cde.txt` takes about 4.5s to run on my WSL2 system with 2 cores, writing a 2 GB file (with abc.txt having 100KB); even this would be within the HTTP timeout, though users would certainly not be happy. Pretty sure a native Linux system on a machine beefy enough to be used as a web server would have no problem serving even larger files over a network like this.2. You did not compare against fewer threads to see if threads are actually the bottleneck rather than IO. Also, all your threads are competing for stdout.
Sure, but then again the designers of circa 2000-2010 J2EE also thought the verbosity and over-engineering was a good idea.
It mostly works fine and it's an impressive bit of engineering. But it has some really ugly failure modes in combination with hacky legacy code designed for real threads. So, you can't blindly assume things to just work. Hence the deadlocks.
Many Java servers already work the way you outline. It's just that they are a bit tedious to use with the traditional Java frameworks. Which is one reason I like using Spring's webflux with Kotlin instead. Just way nicer when it's all exposed via co-routines.
You could say the second choice, the specific API, was done, at least to some extent, for backwards compatibility reasons. I wouldn't agree, but I think there is at least some argument to be made. Here is one of the designer's explanation [0]:
> We also realized that implementing the existing thread API, so turning it into an abstraction with two different implementations won't add any runtime overhead. I also found that when talking about Java's new user mode threads back when this feature was in development, and back when we still called them fibers, every time I talked about them at conferences, I kept repeating myself and explaining that fibers are just like threads. After trying a few early access releases of the JDK with a fiber API, and then a thread API, we decided to go with the thread API.
However, the choice of adding a new concurrency primitive to Java in the form of green threads instead of others was very very clearly not done for backwards compatibility's sake. Ron Pressler (who is active here as 'pron') has several talks on the advantages of green threads over async/await that you can look at [0][1]. The designers of Go also had the same belief, and also chose to add green threads as the fundamental built-in concurrency primitive in Go, obviously not for backwards compatibility reasons in their case.
[0] https://www.infoq.com/presentations/virtual-threads-lightwei...
Virtual threads are nice for unblocking legacy code but they aren't without issues. There are better options for new code with less trade offs on the jvm as well. I've recently been experimenting with jasync-postgresql (there's a mysql variant as well) as an alternative to JDBC in Kotlin. It's a nice library. It does have some limitations and is a bit on the primitive side. But it appears to be somewhat widely used in various database frameworks for Scala, Java, and Kotlin.
Databases and database frameworks are an area on the JVM where there just is a huge amount of legacy code built on threads and blocking IO. It's probably one of the reasons Oracle worked on virtual threads as migrating away from these frameworks is unlikely to ever happen in a lot of code bases. So, waving a magic wand and making all that code non blocking is very attractive. But of course that magic has some hard limitations and synchronize blocks are one of those. I imagine they are working on improving that further.