There are two practical lessons here:

1. Upgrade your JDK for the best performance (as the article says, the slowdown is gone in JDK 26).

2. Don't try to help the GC by pooling objects. Mutating old objects can be expensive, while allocating new ones is cheap (at least for objects that don't do some exceptionally expensive initialisation).

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marginalia_nu 2 days ago | parent | next [-]

Object pooling still has its place, but like any optimization it needs to be based on benchmarks and shouldn't be done haphazardly. Blindly pooling objects will lead to regressions and resource contention more often than improvements.

There are also middle ground options, like pooling objects but giving the pool a lifecycle that is tied to a request.

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pron 2 days ago | parent [-]

The problem is that 1. it's not easy to beat the JDK's GCs at memory management (assuming you've picked the right GC for your workload) especially as they keep getting better and better, and 2. how a pool behaves relative to the GC depends greatly on the GC algorithm (e.g. the same pool could help a bit with, say, Parallel GC, and hurt significantly with G1 or ZGC), and the different GC algorithms also tend to change significantly from release to release, so it's hard to write a good pool that can remain good both across different GCs and across different runtime versions.

In particular, the JDK's GCs are heavily optimised for short-lived objects with high allocation rates. What you want to avoid is temporary data finding itself in the old gen. The newer GCs may dynamically size the young generation to match your program's natural meaning of "short lived", but the longer an object lives, the higher the chances it ends up in the old gen. You want only objects that stick around for a very long time (and have a low allocation rate) to end up in old gen. If you just write naive code, chances are things will work out well. Once you start being clever, you're taking a risk.

So if you're willing to profile your program, with a workload that's representative of production workload (a microbenchmark is useless) on every runtime version and potentially change your "manual optimisation" every six months, you can try. But if not, the advice for the best performance over time is to rely on the platform and let it do its thing. The reason is that the JVM is continuously being optimised for "normal programs". If you're doing anything too clever, you may find that in a future release, your code is making things worse because the optimisations that target normal code don't help your code (or could even treat it as unusual and have it hit slow paths).

I once spoke to a company that were very proud in getting something like a 10% improvement over naive code in Java 8, thanks to some hand optimisation they worked a lot on, only to discover that it caused a 15% regression compared to doing nothing special on JDK 11.

	▲	marginalia_nu 2 days ago \| parent [-]
		Where pooling does sometimes win is for stuff like intermediate buffers for compression or decompression, since a Java alloc will zero the memory, which for sufficiently large buffers is much costlier than the allocation itself, and in such a case you don't care if it's zeroed. Removing allocation pressure can also have effects on other parts of the system, but that is anything but trivial to measure or reason about.

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cogman10 2 days ago | parent | prev | next [-]

Honestly, I don't really understand why G1 is being pushed so hard.

The parallel collector is a perfectly fine collector, particularly for smaller heaps. Even the serial collector isn't bad for things like a containerized environment, yet G1 replaces it by default now [1].

It's not a bad algorithm, but especially when you start talking about sub 2G environments I've not seen a situation where the parallel and serial collectors won't handily beat G1 on pretty much every metric. Major collectors with modern CPUs just doesn't take much time for a lot of memory.

[1] https://openjdk.org/jeps/523

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pron 2 days ago | parent [-]

If anything, I think it's not unlikely that ZGC will become the default at some point, as it matures. It's hard to beat Parallel on batch workloads, although G1 is getting there. ZGC is unparalleled for low-latency (GC pauses are just gone). G1 is intended to offer a compromise that could be a reasonable default.

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cogman10 2 days ago | parent | next [-]

I have no qualms with ZGC being the default. The low latency that it offers at near G1 speeds is a very good trade off (IMO).

I just have a problem with G1 because in my experience, the best place for it is fairly large heaps. Get something sub 2 or even 10G, especially if you have a few cores to offer, and the parallel and often even the serial collector will give G1 latency even on major collections with superior throughput and overhead.

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nickyvdicarlo 2 days ago | parent | prev [-]

I would be very surprised if ZGC became the default, because it incurs a significant overhead penalty to eliminate those GC pauses. All else equal you're effectively just sacrificing throughput for latency, since it's doing a bunch of extra housekeeping in the background (foreshadowing...) That's a perfectly reasonable tradeoff to make if low latency is a priority (or perhaps more importantly if having very consisent/predictable latency is a priority) but in most Java projects I've been exposed to that's been a tertiary concern at best. Frankly, I question if most Java developers are even aware that they're allocating physical memory when they type 'new'...

In the modern enterprise Java world (that I've been exposed to) it's very common to have a mandate that all components deploy a minimum of N instances across X regions for resiliency. By design that almost always means you're deploying at least 2x more compute than you strictly need, so the top priority is generally minimizing per-instance overhead to minimize cloud spend.

For example, the default templates at my current company deploy something like 0.25-0.5 vCPU per instance, and therin lies the rub. ZGC performance is _catastrophically_ bad with <=1 cpus because when there's only one core, any "concurrent" GC events become full on stop the world events. We had someone pilot a change to the default JVM args for all components because they heard that ZGC would reduce latency, only to discover that basically all of our microservices immediately failed their perf tests. For the first one I spot checked, throughput was down ~90% and p95 went from ~40ms to >1s, because more time was being spent on "background" GC than actually servicing requests.

Hope that didn't come off adversarial. I just find GC fascinating, and ended up spending a bunch of time working with the team that owns those defaults to draft general recommendations. TLDR is that when in doubt don't specify/let the JVM pick for you, and don't be surprised if it picks serial :)

	▲	pron 15 hours ago \| parent [-]
		> I would be very surprised if ZGC became the default, because it incurs a significant overhead penalty to eliminate those GC pauses That throughput penalty is not very high with generational ZGC. It's not zero, but it's not very high, either. What ZGC mostly does is spread the memory management activity more evenly across the duration of the program (this does have a cost due to barriers being active more, but it's not huge). But we have some work planned to improve ZGC even further, which is why I didn't say I think it will become the default imminently, only eventually. > ZGC performance is _catastrophically_ bad with <=1 cpus That may well be true, but the JVM can automatically choose a different default algorithm for these circumstances. Indeed, until very recently, the default for low-CPU environments was different (Serial) than for bigger ones (G1).

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ejboy 2 days ago | parent | prev | next [-]

I am happy to see JDK versions actually becoming faster and lighter over time. Nice contrast with other platforms that seem to be moving in the opposite direction.

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exabrial 2 days ago | parent | prev [-]

2: Dont optimize. Dont optimize, yet. If you must optimize, use a profiler.