[slipperydippery]

Whatever efficiency may hypothetically be possible with Java, you can in-fact spot a real world Java program in the wild by looking for the thing taking up 10x the memory it seems like it should need… when idle.

Yes yes I’m sure there are exceptions somewhere but I’ve been reading Java fans using benchmarks to try to convince me that I can’t tell which programs on my computer are Java just by looking for the weirdly slow ones, when I in fact very much could, for 25ish years.

Java programs have a feel and it’s “stuttery resource hog”. Whatever may be possible with the platform, that’s the real-world experience.

[mldbk]

I held the same view as you when I was 22, more than 15 years ago.

With over 15 years of professional experience since then, my perspective has shifted: Java demonstrates its strength when stability, performance, and scalability are required (e.g. bloody enterprise)

A common misconception comes from superficial benchmarking. Many focus solely on memory consumption, which often provides a distorted picture of actual system efficiency.

I can point to EU-scale platforms that have reliably served over 100 million users for more than a decade without significant issues. The bottleneck is rarely the language itself, it is the depth of the team’s experience.

[alt227]

> Many focus solely on memory consumption, which often provides a distorted picture of actual system efficiency.

When other languages can do the same thing with an order of magnitude less RAM, any other efficencies in the system tend to be overshadowed by that and be the sticking point in peoples memories.

You may argue that holding on to this extra memory makes subsequent calls and reads quicker etc, but in my experience generally people are willing to sacrifice milliseconds to gain gigabytes of memory.

[edem]

node is a notable exception. Compared to java node is a hellhole. the standard library is non-existent, most libraries are a buggy mess, the build system is horrible...in fact there is no reliable build system that solves all your typical problems in 1 app. The list goes on.

[MathMonkeyMan]

The JVM eats a chunk of memory in order to make its garbage collector more efficient. Think of it like Linux's page cache.

I haven't worked with too much Java, but I suspect that the distaste many have for it is due to its wide adoption by large organizations and the obfuscating "dressed up" tendency of the coding idioms used in large organizations.

The runtime isn't inherently slow, but maybe it's easier to write slow programs in Java.

[bdangubic]

you know why you don’t see many non-Java programs on your computer taking up 10x memory? because no one uses them to write anything :)

jokes aside, we got a shift in the industry where many java programs were replaced by electron-like programs which now take 20x memory

[vlovich123]

Technically kind of true but at the same time Android apps are predominantly Java/Kotlin. It speaks more to Java just having a bad desktop story. But it’s also why Android devices need 2x the ram

[vips7L]

That has nothing to do with Java. The Android runtime is NOT Java/OpenJdk.

[vlovich123]

No but it does speak to the memory overhead of tracing GC vs ref counting as garbage collection strategies.

[gf000]

Which is very important in... embedded settings.

While for typical backend situations, reference counting has a crazy high throughput overhead, doing atomic inc/decs left and right, that instantly trashes any kind of cache, and does it in the mutator thread that would do the actual work, for the negligible benefit of using less memory. Meanwhile a tracing GC can do (almost) all its work in another thread, not slowing down the actually important business task, and with generational GCs cleaning up is basically a no-op (of just saying that this region can now be reused).

It's a tradeoff as everything in IT.

Also, iPhone CPUs are always a generation ahead, than any android CPU, if not more. So it's not really Apples to oranges.

[vlovich123]

That would be a compelling counter if and only if languages like Java actually beat other languages in throughput. In practice that doesn’t seem to be the case and the reasons for that seem to be:

* languages like c++ and Rust simply don’t allocate as much as Java, instead using value types. Even C# is better here with value types being better integrated.

* languages like c++ and Rust do not force atomic reference counting. Rust even offers non atomic ref counting in the standard library. You also only need to atomic increment / decrement when ownership is being transferred to a thread - that isn’t quite as common depending on the structure of your code. Even swift doesn’t do too badly here because of the combination of compiler being able to prove the permission of eliding the need for reference counting altogether and offering escape hatches of data types that don’t need it.

* c++, Rust, and Swift can access lower level capabilities (eg SIMD and atomics) that let them get significantly higher throughput.

* Java’s memory model implies and requires the JVM to insert atomic accesses all over the place you wouldn’t expect (eg reading an integer field of a class is an atomic read and writing it is an atomic write). This is going to absolutely swamp any advantage of the GC. Additionally, a lot of Java code declares methods synchronized which requires taking a “global” lock on the object which is expensive and pessimistic for performance as compared with the fine-grained access other languages offer.

* there’s lots of research into ways of offering atomic reference counts more cheaply (called biased RC) which can safely avoid needing to do an atomic operation in places completely transparently and safely provided the conditions are met .

I’ve yet to see a Java program that actually gets higher throughput than Rust so the theoretical performance advantage you claim doesn’t appear to manifest in practice.

[zozbot234]

It depends how you implement reference counting. In Rust the atomic inc-dec operations can be kept at a minimum (i.e. only for true changes in lifecycle ownership) because most accesses are validated at compile time by the borrow checker.

[jghn]

> taking up 10x the memory it seems like it should need… when idle.

The JVM tends to hold onto memory in order to make things faster when it does wind up needing that memory for actual stuff. However, how much it holds on to, how the GC is setup, etc are all tunable parameters. Further, if it's holding onto memory that's not being used, these are prime candidates to be stored in virtual memory which is effectively free.

[edem]

Note that the memory problem you mentioned is not really a problem in fact. It is just how managed memory works in Java. Just run .gc() and you'll see what I'm talking about. It reserves memory which you can see on the charts but it is not necessarily used memory.

[gf000]

Well, you might want to read up on how OSs handle memory under the hood, and that virtual memory != physical, and that task manager and stuff like that can't show the real memory usage.

Nonetheless, tracing GCs do have some memory overhead in exchange for better throughput. This is basically the same concept as using a buffer.

-----

And can you tell which of these websites use Java from "the feel"? AWS cloud infra, a significant chunk of Google, Apple's backends, Alibaba, Netflix?

[jayd16]

"Java is bloated because I only look at the bloated examples."

Is C++ bloated because of the memory Chrome uses?

[slipperydippery]

When all your examples in actual use are bloated…

I’ve never seen another basic tech used to develop other programs that’s so consistently obvious from its high resource use and slowness, aside from the modern web platform (Chrome, as you put it). It was even more obvious back when we had slower machines, of course, but Java still stands out. It may be able to calculate digits of Pi in a tight loop about as fast as C, but real programs are bloated and slow.

[gf000]

Sounds like a classic case of confirmation bias.

Especially that like half of the web runs on Java, you just have absolutely no idea when it silently does its job perfectly.

[alt227]

> Especially that like half of the web runs on Java

Source?

W3 seems to think its more like ~5%

https://w3techs.com/technologies/comparison/pl-java

[gf000]

5% of "whose server-side programming language we know"

From the website.

And 76% of these websites is PHP, which seems to mean.. they can determine PHP more easily for a website (nonetheless, there are indeed a lot of WordPress sites, but not this amount).

[alt227]

Right, so Im assuming that as you are saying 'Half the web runs on java', maybe you know more about what websites are using in their backend? Care to share where you are getting this information from?

[slipperydippery]

K.