Are people still dealing with GC issues?

I find that it basically just more or less works out of the box on modern JVMs.

kelseyfrog 3 days ago | parent | next [-]

It's selection bias. There's a huge number of GC language users, but those who experience problems tend to be the ones who comment.

You're right; the vast majority of people use GC just fine and go about their day. We should update little to none when we see evidence of GC hardship.

	▲	stmw 3 days ago \| parent \| next [-]
		It depends a lot on the scale of the system, which often means that those fewer users are actually doing things that are more complex and more valuable - either at the lower end or at the high end.
	▲	2001zhaozhao 3 days ago \| parent \| prev [-]
		I sometimes run into browser JavaScript GC issues for browser games specifically but on the JVM side i have not run into any pain points for a long time. (I run a first-person shooter Minecraft server, and for this and other fast-paced gaming in general pause times under a millisecond or so is generally good.)

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hylaride 3 days ago | parent | prev | next [-]

There are edge cases where GC issues can crop up, in particular specific "serverless" models (eg AWS lambdas) where the JVM can get "paused" between executions and GC doesn't cleanly run, causing memory to trend upwards until the next cold-start happens (especially if you're running it within a docker container yourself). Limited CPU situations that can exist in these kinds of runtime environments also limit GC in several ways, too.

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skullone 3 days ago | parent [-]

What's it like running JVM inside serverless? Python gets interesting enough when it pauses waiting for another call sometimes, the JVM seems like it'd introduce its own interesting things :o

	▲	hylaride 3 days ago \| parent [-]
		Other than some GC issues, meaning we had to give it more memory than we'd otherwise like thereby making them a bit more expensive, it's mostly been fine. The key to ephemeral java is keeping scope limited and not using it when cold starts matter (which can cause a bit of jitter in execution lag). Our use case was asynchronous, so it worked. We wanted to investigate using the native AWS java lambdas with snapstart and/or using parallel GC, but the place I used them at a year ago was under the tyranny of product having complete control of our backlog, so we didn't get to go that far with it or even more serious tech debt for that matter. More memory may or may not even be much of an issue depending on your workload. If you can handle the odd OOM error it would have been fine, but for our use case lambdas were so cheap that it didn't really matter, outside of us techies preferring to do it "right". Having the max execution time be less than 15m could also minimize the heap bloat at the cost of more cold starts.

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thangalin 3 days ago | parent | prev | next [-]

> Are people still dealing with GC issues?

Have you tried real-time audio processing for digital radio communications on a JVM that requires sub-millisecond latency on older, temperature-hardened CPUs?

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pron 3 days ago | parent [-]

Use ZGC.

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hedora 3 days ago | parent [-]

Does it provide hard latency bounds like Azul does (did?), and are they lower than disk/network latencies on modern hardware?

I moved to c++/rust years ago because those languages do, and tens of milliseconds matter for network services. At the time Java could pause for 10’s of seconds, which was 1000x worse than waiting for a spinning disk to seek.

These days, disks are 100s micros to single digit millis, so I guess if Java GC is finally working 30 years after they “fixed” its performance problems, then I’d want to be able to tune ZGC to not pause the app for more than ~ 500us, max.

This article is from last year, but suggests they’re still off by an order of magnitude:

https://www.morling.dev/blog/lower-java-tail-latencies-with-...

Also, that’s measuring a 30 second window.

If you hammer a 100GB-1TB heap in steady state with small allocations for, say, a month at 100% CPU, does it eventually do the typical Java thing, where a major compaction takes the process down for seconds or even minutes, or does it just slow down application requests so it can keep up with load?

	▲	mdavidn 3 days ago \| parent \| next [-]
		> If you hammer a 100GB-1TB heap in steady state with small allocations for, say, a month at 100% CPU, does it eventually do the typical Java thing, where a major compaction takes the process down for seconds or even minutes, or does it just slow down application requests so it can keep up with load? No. Every garbage collection in Java relocates objects. Compared to malloc, memory fragmentation in long-lived processes is less of a concern. Freelists track only large segments of available memory. The allocator reserves a segment per thread and simply advances a pointer. Small short-lived objects are never visited by the collector. Instead, live siblings are relocated elsewhere before the entire segment is reclaimed. The above holds true for all of the collectors. The difference is how they deal with concurrent changes to object pointers by the application. Generally, stopping the world uses less net CPU than the memory barriers required by G1GC and ZGC, but most applications are willing to provide more memory and CPU in exchange for shorter pauses.
	▲	pron 3 days ago \| parent \| prev [-]
		> Does it provide hard latency bounds like Azul does (did?), and are they lower than disk/network latencies on modern hardware? Yes and yes (although we need to be more precise when we talk about latencies; see next paragraph). > These days, disks are 100s micros to single digit millis, so I guess if Java GC is finally working 30 years after they “fixed” its performance problems, then I’d want to be able to tune ZGC to not pause the app for more than ~ 500us, max. 1. You don't need to tune it. The algorithm simply doesn't collect garbage in stop-the-world pauses. 2. Hiccups are sporadic. They should not be compared to the average latency of normal operation. The relevant question is, is ZGC introducing longer hiccups than those a non-realtime kernel would, and the answer is no. > This article is from last year, but suggests they’re still off by an order of magnitude The article doesn't measure GC pauses when it shows latencies (it says: "With ZGC on the other hand, the longest GC pause time observed is ~50 microseconds"). It measures the response latencies of some service. Note that allocation stalls also occur with malloc, it just isn't reported conveniently. Of course, one of the greatest advantages of moving collectors still applies: Under high allocation rates, moving collectors (but not malloc/free!) allow you to compensate for increased CPU spent on memory management by increasing the heap (i.e. if your allocation rate doubles, you can increase the heap and keep the CPU cost of memory management the same). In the past, this advantage translated to higher throughputs compared to malloc/free, but suffered from GC pauses. Those pauses are gone today. > If you hammer a 100GB-1TB heap in steady state with small allocations for, say, a month at 100% CPU, does it eventually do the typical Java thing, where a major compaction takes the process down for seconds or even minutes, or does it just slow down application requests so it can keep up with load? No, it does not. You could, of course, construct some pathological cases where you'd have a high allocation rate for long-lived objects which would result in high CPU utilisation by the GC, but it's easier to get into pathological malloc/free cases in C++ (or Rust) than with ZGC. Let me put it another way: no matter your memory management strategy, it's possible to overwhelm it, but the likelihood that a real, "naive" program would overwhelm a malloc/free allocator is higher than it would the JDK's GCs.

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geodel 3 days ago | parent | prev [-]

Perhaps. That's why actual JVM GC developers are talking about it.