Why is the Rust compiler so slow?
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Do you really believe that nobody over the course of Rust's lifetime has ever taken a look at C compilers and thought about if techniques they use could apply to the Rust compiler?
Unity builds are useful for C programs because they tend to reduce header processing overhead, whereas Rust does not have the preprocessor or header files at all.
They also can help with reducing the number of object files (down to one from many), so that the linker has less work to do, this is already sort of done (though not to literally one) due to what I mentioned above.
In general, the conventional advice is to do the exact opposite: breaking large Rust projects into more, smaller compilation units can help do less "spurious" rebuilding, so smaller changes have less overall impact.
Basically, Rust's compile time issues lie elsewhere.
Go has sub-second build times even on massive code-bases. Why? because it doesn't do a lot at build time. It has a simple module system, (relatively) simple type system, and leaves a whole bunch of stuff be handled by the GC at runtime. It's great for its intended use case.
When you have things like macros, advanced type systems, and want robustness guarantees at build time.. then you have to pay for that.
I can believe that, but even so it's caused by the type system monomorphising everything. When it use qsort from libc, you are using per-compiled code from a library. When you use slice::sort(), you get custom assembler compiled to suit your application. Thus, there is a lot more code generation going on, and that is caused by the tradeoffs they've made with the type system.
Rusts approach give you all sorts of advantages, like fast code and strong compile time type checking. But it comes with warts too, like fat binaries, and a bug in slice::sort() can't be fixed by just shipping of the std dynamic library, because there is no such library. It's been recompiled, just for you.
FWIW, modern C++ (like boost) that places everything in templates in .h files suffers from the same problem. If Swift suffers from it too, I'd wager it's the same cause.
But not having to is a win, as the monomorphised sorts are just much faster at runtime than having to do an indirect call for each comparison.
Not all programmers of course - if you look at std there are many places that split types into generic and non-generic parts so the compiler will reuse as much code as possible, but it does come at the cost of additional complexity. Worse if you aren't already aware of why they are doing it, the language does a marvellous job of hiding the reason that complexity is there. I'd wager a novice Rust programmer is as befuddled by it as a JavaScript programmer coming across his first free() call in C.
I have this dream of a language like Rust that makes the trade-off plain, so the programmer is always aware of "this is a zero cost abstraction - you're just making it plain via the type system your doing the right thing" and "I'm going to have to generate a lot of code for this". Then go a step further and put the types and source you want to export to other libraries in a special elf section in the .so so you don't need the source to link against it, then go another step further and make the programmer using the .so explicitly instantiate any stuff that does require a lot of code generated so he is aware of what is happening.
That said, I don't think it would help the compile time problem in most cases. C++ already does something close by forcing you to put exported stuff in .h files, and they ended up with huge .h files and slow compiles anyway.
Nevertheless doing that would make for a Rust like language, that, unlike Rust, supported an eco-system of precompiled libraries just like C does. Rust is so wedded to transparent monomorphisation it looks near impossible now.
I was all excited to conduct the "cargo check; mrustc; cc" is 100x faster experiment, but I think at best, the multiple is going to be pretty small.
There are multiple caveats on providing this to users (we can't assume that macro invocations are idempotent, so the new behavior would have to be opt in, and this only benefits incremental compilation), but it's in our radar.
Unfortunately that doesn't seem to ever be a scenario cargo will support out of the box.
I belong to the school of thought that C style macros in C++ should be nuked.
Exception being source code I don't own.
A big reason that amalgamation builds of C and C++ can absolutely fly is because they aren't reparsing headers and generating exactly one object file so the linker has no work to do.
Once you add static linking to the toolchain (in all of its forms) things get really fucking slow.
Codegen is also a problem. Rust tends to generate a lot more code than C or C++, so while the compiler is done doing most of its typechecking work, the backend and assembler has a lot of things to chuck through.
for i in 0..10 {}
let mut iter = Range { start: 0, end: 10 }.into_iter();
while let Some(i) = iter.next() {}This has tradeoffs: increased ABI stability at the cost of longer compile times.
I’d like to see tooling for this to pinpoint bottlenecks - it’s not always obvious what’s making builds slow.
I second this enthusiastically.
If it improves compile time, that sounds like a bug in the compiler or the design of the language itself.
Even this can lead to unworkable compile times, to the point that code is rewritten.
Nah. Slow type checking in Swift is primarily caused by the fact that functions and operators can be overloaded on type.
Separately-compiled generics don't introduce any algorithmic complexity and are actually good for compile time, because you don't have to re-type check every template expansion more than once.
Wouldn't you say a lot of that comes from the macros and (by way of monomorphisation) the type system?
I suspect this leaks into both compile-time and run-time costs.
Could you expand on that, please? Every time you run dynmically linked program, it is linked at runtime. (unless it explicitly avoids linking unneccessary stuff by dlopening things lazily; which pretty much never happens). If it is fine to link on every program launch, linking at build time should not be a problem at all.
If you want to have link time optimization, that's another story. But you absolutely don't have to do that if you care about build speed.
I think lazily linking is the default even if you don't use dlopen, i.e. every symbol gets linked upon first use. Of course that has the drawback, that the program can crash due to missing/incompatible libraries in the middle of work.
Anyway, while what you said is theoretically half-true, a fairly large number of libraries are not designed/encapsulated well. This means almost all of their symbols are exported dynamically, so, the idea that there are only "few public exported symbols" is unfortunately false.
However, something almost no one ever mentions is that ELF was actually designed to allow dynamic libraries to be fairly performant. It isn't something I would recommend, as it breaks many assumptions on Unices, (while you don't get the benefits of LTO) you can achieve code generation almost equivalent to static linking by using something like "-fno-semantic-interposition -Wl,-Bsymbolic,-z,now". MaskRay has a good explanation on it: https://maskray.me/blog/2021-05-16-elf-interposition-and-bsy...
Go got famous compile times, because for a decade a new generation educated in scripting languages and used to badly configured C and C++ projects, took for innovation, what was actually a return to old values in compiler development.
DLLs got their start when early windowing systems didn't quite fit on the workstations of the era in the late 80s / early 90s.
In about 4 minutes both Microsoft and GNU were like, "let me get this straight, it will never work on another system and I can silently change it whenever I want?" Debian went along because it gives distro maintainers degrees of freedom they like and don't bear the costs of.
Fast forward 30 years and Docker is too profitable a problem to fix by the simple expedient of calling a stable kernel ABI on anything, and don't even get me started on how penetrated everything but libressl and libsodium are. Protip: TLS is popular with the establishment because even Wireshark requires special settings and privileges for a user to see their own traffic, security patches my ass. eBPF is easier.
Dynamic linking moves control from users to vendors and governments at ruinous cost in performance, props up bloated industries like the cloud compute and Docker industrial complex, and should die in a fire.
Don't take my word for it, swing by cat-v.org sometimes and see what the authors of Unix have to say about it.
I'll save the rant about how rustc somehow manages to be slower than clang++ and clang-tidy combined for another day.
…
Dynamic linking moves control from users to vendors and governments at ruinous cost in performance, props up bloated industries...
This is ridiculous. Not everything is a conspiracy!
If fact, if there was anything remotely controversial about a bunch of extremely specific, extremely falsifiable claims I made, one imagines your rebuttal would have mentioned at least one.
I said inflmatory things (Docker is both arsonist and fireman at ruinous cost), but they're fucking true. That Alpine in the Docker jank? Links musl!
But people should make an informed choice, and there isn't any noble or high minded or well-meaning reason to try to shout that information down.
Don't confidently assert falsehoods unless you're prepared to have them refuted. You're entitled to peddle memes and I'm entitled to reply with corrections.
The compiler is optimized for compilation speed, not runtime performance. Generally speaking, it does well enough. Especially because it's usecase is often applications where "good enough" is good enough (IE, IO heavy applications).
You can see that with "gccgo". Slower to compile, faster to run.
For pure computational workloads, it'll be faster. However, anything with heavy allocation will suffer as apparently the gccgo GC and GC related optimizations aren't as good as cgo's.
Since fast compilation was a goal, every part of the design was looked at through a rough "can this be a horrible bottleneck?", and discarded if so. For example, the import (package) system was designed to avoid the horrible, inefficient mess of C++. It's obvious that you never want to compile the same package more than once and that you need to support parallel package compilation. These may be blindingly obvious, but if you don't think about compilation speed at design time, you'll get this wrong and will never be able to fix it.
As far as optimizations vs compile speed goes, it's just a simple case of diminishing returns. Since Rust has maximum possible perfomance as a goal, it's forced to go well into the diminishing returns territory, sacrificing a ton of compile speed for minor performance improvements. Go has far more modest performance goals, so it can get 80% of the possible performance for only 20% of the compile cost. Rust can't afford to relax its stance because it's competing with languages like C++, and to some extent C, that are willing to go to any length to squeeze out an extra 1% of perfomance.
Unless you use sqlite, in which case your build takes a million years.
Compilation speed depends on what you do with a language. "Fast" is not an absolute, and for most people it depends heavily on community habits. Rust habits tend to favor extreme optimizability and/or extreme compile-time guarantees, and that's obviously going to be slower than simpler code.
Go and Dlang compilers were designed by those that are really good at compiler design and that's why they're freaking fast. They designed the language around the compiler constraints and at the same managed to make the language intuitive to use. For examples, Dlang has no macro and no unnecessary symbols look-up for the ambiguous >>.
Because of these design decisions both Go and Dlang are anomaly for fast compilation. Dlang in particular is notably more powerful and expressive compared to C++ and Rust even with its unique hybrid GC and non-GC compilation.
In automotive industry it's considered a breakthrough and game changing achievement if you have a fast transmission for seamless auto and manual transmission such as found in the latest Koenigsegg hypercar [1]. In programming industry however, nobody seems to care. Walter Bright the designer of Dlang has background in mechanical engineering and it shows.
[1] Engage Shift System: Koenigsegg new hybrid manual and automatic gearbox in CC850:
https://www.topgear.com/car-news/supercars/heres-how-koenigs...
The overall principle is sound though: it's true that doing some work is more than doing no work. But the borrow checker and other safety checks are not the root of compile time performance in Rust.
Stuff like inserting bounds checking puts more work on the optimization passes and codegen backend as it simply has to deal with more instructions. And that then puts more symbols and larger sections in the input to the linker, slowing that down. Even if the frontend "proves" it's unnecessary that calculation isn't free. Many of those features are related to "safety" due to the goals of the language. I doubt the syntax itself really makes much of a difference as the parser isn't normally high on the profiled times either.
Generally it provides stricter checks that are normally punted to a linter tool in the c/c++ world - and nobody has accused clang-tidy of being fast :P
But it _is_ about the sheer volume of stuff passed to LLVM, as you say, which comes from a couple of places, mostly related to monomorphization (generics), but also many calls to tiny inlined functions. Incidentally, this is also what makes many "modern" C++ projects slow to compile.
In my experience, similarly sized Rust and C++ projects seem to see similar compilation times. Sometimes C++ wins due to better parallelization (translation units in Rust are crates, not source files).
As an example, say your function takes anything that can be turned into a String. You'd write a generic wrapper that does the ToString step, then change the existing function to just take a String. That way when your function is called, only the thin outer function is monomorphised, and the bulk of the work is a single implementation.
It's not _that_ commonly known, as it only becomes a problem for a library that becomes popular.
fn foo<S: Into<String>>(s: S) {
fn inner(s: String) { ... }
inner(s.into())
}* Make no nested types - these slow compiler time a lot
* Include no crates, or ones that emphasize compiler speed
C is still v. fast though. That's why I love it (and Rust).
I wouldn't like it that much
One of the primary features of Rust is the extensive compile-time checking. Monomorphization is also a complex operation, which is not exclusive to Rust.
C compile times should be very fast because it's a relatively low-level language.
On the grand scale of programming languages and their compile-time complexity, C code is closer to assembly language than modern languages like Rust or Swift.
There's some other dependencies in there that are only used when building for test/benchmarking like serde, zstd, and criterion. You would need to be certain you're building only the library and not the test harness to be sure those aren't being built too.
The rust compiler is actually pretty fast for all the work it's doing. It's just an absolutely insane amount of additional work. You shouldn't expect it to compile as fast as C.
1. Use pointers and do not include header file for class, if you need pointer to that class. I think that's a pretty established pattern in C++. So if you want to declare pointer to a class in your header, you just write `class SomeClass;` instead of `#include "SomeClass.hpp"`.
2. Do not use STL or IOstreams. That project used only libc and POSIX API. I know that author really hated STL and considered it a huge mistake to be included to the standard language.
3. Avoid generic templates unless absolutely necessary. Templates force you to write your code in header file, so it'll be parsed multiple times for every include, compiled to multiple copies, etc. And even when you use templates, try to split the class to generic and non-generic part, so some code could be moved from header to source. Generally prefer run-time polymorphism to generic compile-time polymorphism.
Same applies to point 3, when used alongside external templates.
That's my 2000s development experience. Fortunately I've spent a good chunk of the 2010s and most of the 2020s using other languages.
The classic XKCD compilation comic exists for a reason.
Most likely treating C and C++ as scripting languages with header only libraries, only to complain about build times afterwards.
Maybe it's a MSVC thing - it does seem to have some multi-threading stuff. In any case raddbg non-clean builds take longer than any of my rust projects.
If you want to see the difference download unreal engine and compile the editor with and without unity builds enabled.
My experience has been the polar opposite of yours - similar size rust projects are an order of magnitude slower than C++ ones. Could you share an example of a project to compare with?
EDIT: i signed up to get access to unreal so take a look at how they do unity builds and turns out they have their own build tool (not CMake) that orchestrates the build. so does anyone know (can someone comment) whether unity builds for them (unreal) means literally one file for literally all project sources files or if it's "higher-granularity" like UNITY_BUILD in CMake (i.e., single file per object).
UE doesn't use a full unity build, it groups some files together into small "modules". I can see how this approach may have some benefits; you're trading off a faster clean build for a slower incremental build.
I tested compiling UnrealFrontend, and a default setup with the hybrid unity build took 148s. I noticed it was only using half my cores due to memory constraints. I disabled unity and upped the parallelism and got 182s, so 22% slower while still using less memory. A similarly configured unity build was 108s, so best case is ~2x.
On the other hand only changing the file TraceTools/SFilterPreset.cpp resulted in 10s compilation time under a unity build, and only 2s without unit.
I can see how this approach has its benefits (and drawbacks). But to be clear this isn't what projects like raddbg and sqlite3 are doing. They're doing a single translation unit for the entire project. No parallelism, no incremental builds, just a single compiler invocation. This is usually what I've seen people mean by a unity build.
> My experience has been the polar opposite of yours - similar size rust projects are an order of magnitude slower than C++ ones. Could you share an example of a project to compare with?
I just did a release build of egui in 35s, about the same as raddbg's release build. This includes compiling dependencies like wgpu, serde and about 290 other dependencies which add up to well over a million lines of code.
Note I do have mold configured as my linker, which speeds things up significantly.
I’m the tech director for a game studio using unreal and we spec the dev machines with enough memory to avoid that pressure - we require 2.5GB/Core, rounded up. Right now we’re using i9 14900k’s with 128GB RAM. We were on 5950x with 64GB before this.
I tried egui last night but failed to build it due to missing dependencies, but I’ll see if I can get it running on Monday. I’d also love to see what raddbg would be like if we split it into even 4 compilation units
Most certainly an unfair comparison; I did not know that "unity build" also referred to a hybrid setup. I've only seen people advocate for a single translation unit approach, and that's always just plain slow.
Personally I'll almost always prefer faster incremental compilation; thankfully my work's clean builds only take 30 seconds.
> I’d also love to see what raddbg would be like if we split it into even 4 compilation units
Should be a minimum of 32x faster just building in parallel with our hardware ;)
Unfortunately raddbg suffers from unity-build-syndrome: It has headers but they're missing definitions, and .c files are missing includes.
> Unfortunately raddbg suffers from unity-build-syndrome: It has headers but they're missing definitions, and .c files are missing includes.
We run a CI build once a week with unity disabled to catch these issues.
> Should be a minimum of 32x faster just building in parallel with our hardware ;)
My experience here is that parallelism is less than linear and avoiding repeated work is super-linear - there’s a happy medium. If you had 128 files and 32 cores it’s probably fast to compile in parallel, but likely even faster if you can just dispatch 32 “blobs” and link them at the end.
https://codeload.github.com/EpicGamesExt/raddebugger/tar.gz/...
It's not that it can't be done but that it usually is not worth the hassle and our goal should be for compilation to be fast despite not everything being in one file.
Turbo Pascal is a prime example for a compiler that won the market not least because of its - for the time - outstanding compilation speed.
In the same vein, a language can be designed for fast compilation. Pascal in general was designed for single-pass compilation which made it naturally fast. All the necessary forward declarations were a pain though and the victory of languages that are not designed for single-pass compilation proofs that while doable it was not worth it in the end.
I'm not sure what Rust or docker have to do with this basic issue, it just feels like young blood attempting 2020 solutions before exploring 1970 solutions.
The simple truth is a C compiler doesn’t need to do very much!
Have you tried troubleshooting a compiler error in a unity build?
Yeah.
Rust is generally faster to compile on a per-sourceline basis than c++. But rust projects compile all their dependencies as well.
For the kind of work I do — writing servers, networking, and glue code — fast compilation is absolutely paramount. At the same time, I want some type safety, but not the overly obnoxious kind that won’t let me sloppily prototype. Also, the GC helps. So I’ll gladly pay the price. Not having to deal with sigil soup is another plus point.
I guess Google’s years of experience led to the conclusion that, for software development to scale, a simple type system, GC, and wicked fast compilation speed are more important than raw runtime throughput and semantic correctness. Given the amount of networking and large - scale infrastructure software written in Go, I think they absolutely nailed it.
But of course there are places where GC can’t be tolerated or correctness matters more than development speed. But I don’t work in that arena and am quite happy with the tradeoffs that Go made.
Nowadays the culture seems to have evolved a bit. I now go into high alert mode if I see a channel cross a function boundary or a goroutine that wasn't created via errgroup or similar.
People also seem to have chilled out about the "share by communicating" thing. It's usually better to just use a mutex and I think people recognise that now.
It's just a project from a few very talented people who happen to draw their salary from Google's coffers.
I need none of that guarantee and all of the compilation speed along with a language where juniors in my team can contribute quickly. Different problem space.
> Types either represent the data or not
This definitely required, but is only really the first step. Where types get really useful is when you need to change them later on. The key aspects here are how easily you can change them, and how much the language tooling can help.
No. two types can represent the same payload, but one might be a simple structure, the other one could be three or twenty nested type template abstractions deep, and created by a proc macro so you can't chase down how it was made so easily.
As you go further towards formal verification you get:
* More accurate / tighter types. For example instead of `u8` you might have `range(0, 7)` or even a type representing all odd numbers.
* Better compile time detection of bugs. (Ultimately you are formally verifying the program.)
* Worse type errors. Eventually you're getting errors that are pretty much "couldn't prove the types are correct; try again".
* More difficulty satisfying the type checker. There's a reason formal verification of software isn't very popular.
So it's definitely true that "more obnoxious types" exist, but Go is very far from the obnoxious region. Even something like Rust is basically fine. I think you can even go a little into dependent types before they really start getting obnoxious.
TL;DR, he's just lazy and doesn't really care about bugs.
Well, that point in the design space was already occupied by Java which also has extremely fast builds. Go exists primarily because the designers wanted to make a new programming language, as far as I can tell. It has some nice implementation aspects but it picked up its users mostly from the Python/Ruby/JS world rather than C/C++/Java, which was the original target market they had in mind (i.e. Google servers). Scripting language users were in the market for a language that had a type system but not one that was too advanced, and which kept the scripting "feel" of very fast turnaround times. But not Java because that was old and unhip, and all the interesting intellectual space like writing libs/conf talks was camped on already.
And you left out classloader/classpath/JAR dependency hell, which was horrid circa late 90s/early 2000s...and I'm guessing was still a struggle when Go really started development. Especially at Google's scale.
Don't get me wrong, Java has come a long way and is a fine language and the JVM is fantastic. But the java of 2025 is not the same as mid-to-late 2000s.
But Go wasn't designed for CLI apps. It was designed for writing highly multi-threaded servers at Google, according to the designers, hence the focus on features like goroutines. And in that context startup time just doesn't matter. Startup time of servers at Google was (in that era) dominated by cluster scheduling, connecting to backends, loading reference data and so on. Nothing that a change in programming language would have fixed.
Google didn't use classloader based frameworks so that also wasn't relevant.
For example initial JIT caching experiments on OpenJDK came from J/Rockit.
Java programs rely on the JVM, of which there are many variants. Run time options are often split into multiple XML files -- one file for logging, another to control the number of threads and so on. Checking for the running process using `ps | grep` yields some long line that wraps the terminal window, or doesn't fit neatly into columns shown in `htop` or `btop`.
These complaints are mostly about conventions and idioms, not the languages themselves. I appreciate that the Java ecosystem is extremely powerful and flexible. It is possible to compile Java programs into standalone binaries, though I rarely see these in practice. Containers can mitigate the messiness, and that helps, up until the point when you need to debug some weird runtime issue.
I wouldn't argue that people should stop programming in Java, as there are places where it really is the best choice. For example deep legacy codebases, or where you need the power of the JVM for dynamic runtime performance optimizations.
There are a lot of places where Go is the best choice (eg. simple network services, CLI utilities), and in those cases, please, please deploy simple Go programs. Most of the time, developers will reach for whatever language they're most comfortable with.
What I like most about Go is how convenient it is, by default. This makes a big difference.
And with the increasing performance of Bun, it seems that Go is about to get a whooping by JS.
(Which isn't really true, as most of the Bun perf comes from Zig, but they are targeting JS Devs.)
None of these runtimes make JS anywhere even close to single-threaded Go perf, let alone multithreaded (goroutine) perf.
npm was also maybe the first default package manager that "just works," unlike Python or browser JS.
I'm also not fond of any of the Golang syntax, especially not having exceptions. Or if you want explicit errors, fine, at least provide nice unwrap syntax like Rust does.
I had to, to make sense of whatever was going on.
If this is systems programming, yeah you're reasoning about channels, but that's mostly the same in any language. Golang has slightly nicer support for that if anything.
I'm a fan of Go, but I don't think it's the product of some awesome collective Google wisdom and experience. Had it been, I think they'd have come to the conclusion that statically eliminating null pointer exceptions was a worthwhile endeavor, just to mention one thing. Instead, I think it's just the product of some people at Google making a language they way they wanted to.
For example, Ken Thompson has said his job at Google was just to find things he could make better.
Go has a very low barrier to entry, but also a relatively low ceiling. The proliferation of codegen tools for Go is a testament of its limited expressive power.
It doesn't mean that Go didn't hit a sweet spot. For certain tasks, it very much did.
Go is the product of like 3 Googlers' tastes. It isn't some perfect answer born out of the experience of thousands of geniuses.
I think they got a lot right - fantastic tooling, avoiding glibc, auto-formatting, tabs, even the "no functional programming so you have to write simple code" thing is definitely a valid position. But I don't think anyone can seriously argue that Go's handling of null is anything but a huge mistake.
I'd be interested in this project if you do decide to pursue it.
Something to look into in retirement.
At the same time, I have worked at places where people had to rewrite major parts of their backend in other languages because Python/Node was no longer sufficient.
First, dependencies don't translate easily to the perceived size. In C++ dependencies on large projects are often vendored (or even not used at all). And so it is easy to look at your ~400000 line codebase and go "it's slow, but there's a lot of code here after all".
Second (and a much worse problem) are macros. They actually hit the same issue. A macro that expands to 10s or 100s of lines can very quickly take your 10000 line project and turn it into a million line behemoth.
Third are generics. They also suffer the same problem. Every generic instantiation is eating your CPU.
But I do want to offer a bit of an excuse for rust. Because these are great features. They turn what would have taken 100000 lines of C or 25000 lines of C++ to a few 1000s lines of Rust.
However, there is definitely an overuse here making the ecosystem seem slow. For instance, at work we use async-graphql. The library itself is great, but it's an absolute proc-macro hog. There's issues in the repository open for years about the performance. You can literally feel the compiler getting slower for each type you add.
YSK: The compiler performance is IIRC exponential in the "depth" of types. And oh boy does GraphQL love their nested types.
Recently, support as added to help people analyze this
See https://nnethercote.github.io/2025/06/26/how-much-code-does-...
How do they do with smaller programs that would have taken far less than 100,000 lines of C.
For whatever reasons, many authors choose to rewrite small C utilties, or create similar ones, using Rust.^1 Perhaps there are countless examples of 100,000 line C programs rewritten in Rust but the ones I see continually submitted to HN, Github and elsewhere are much smaller.
How does Rust compilation time compare with C for smaller programs.
NB. I am not asking about program size. I am asking about compilation speed.
(Also curious about resource usage, e.g. storage, memory. For example, last time I measured, Rust compiler toolchain is about 2x as large as the GCC toolchain I am using.)
1. Some of these programs due to their size seem unlikely to have undetected memory-safety issues in any language. Their size makes them relatively easy to audit. Unlike a 100,000 line C program.
A truly robust C program will generally be much larger than the equivalent Rust program.
I had a quick look and found this article that compares a partial port of a C++ codebase (at around 17kloc). https://quick-lint-js.com/blog/cpp-vs-rust-build-times/
The resulting rust code apparently ended up slightly larger. This isn't entirely unsurprising to me despite the 25:1 figure from above. Certain things are much more macro-able than others (like de/serialization). Note that C++ is actually well positioned to level the field here with C++26 reflection.
Despite the slightly larger size, the compile times seem roughly equal. With rust scaling worse as the size increases. As a side-note, I did find this part relevant to some of my thoughts from above:
> For example, proc macros would let me replace three different code generators
Now, I know that C isn't C++. But, I think that when restricting yourself to a mostly C-like subset (no proc-macros, mostly no generics outside Option/Result) the result would likely mirror the one above. Depending on the domain and work needed, either language could be much shorter or longer. For example, anything involving text would likely be much shorter in rust as the stdlib has UTF-8 handling built-in. On the other hand, writing custom data structures would likely favor C.
I am interested to see if TRACTOR could help here. Being able to port C code to Rust and then observe the compile times would be pretty interesting. https://www.darpa.mil/research/programs/translating-all-c-to...
> So instead, I'd like to switch to deploying my website with containers (be it Docker, Kubernetes, or otherwise), matching the vast majority of software deployed any time in the last decade.
Containers offer many benefits. To name some: process isolation, increased security, standardized logging and mature horizontal scalability.
First stage compiles the code. This is good for isolation and reproducibility.
Second stage is a lightweight container to run the compiled binary.
Why is the author being attacked (by multiple comments) for not making things simpler when that was not claimed that as the goal. They are modernizing it.
Containers are good practice for CI/CD anyway.
Don't do what you don't need to do.
They are already long past the point of "complicate things unnecessarily".
A simple Dockerfile pales in comparison.
Docker is a (the, in some areas) modern way to do it, but far from the only way.
no, that's sandboxing.
"Unfortunately, this will rebuild everything from scratch whenever there's any change."
In this situation, with only one person as the builder, with no need for CI or CD or whatever, there's nothing wrong with building locally with all the local conveniences and just slurping the result into a docker container. Double-check any settings that may accidentally add paths if the paths have anything that would bother you. (In my case it would merely reveal that, yes, someone with my username built it and they have a "src" directory... you can tell how worried I am about both those tidbits by the fact I just posted them publicly.)
It's good for CI/CD in a professional setting to ensure that you can build a project from a hard drive, a magnetic needle, and a monkey trained to scratch a minimal kernel on to it, and boot strap from there, but personal projects don't need that.
Even at work, I have a few projects where we had to build a Java uber jar (all the dependencies bundled into one big far) and when we need it containerized we just copy the jar in.
I honestly don't see much reason to do builds in the container unless there is some limitation in my CICD pipeline where I don't have access to necessary build tools.
In my own time I usually write C or Zig.
If you now copy your binary to the container and it implicitly expects there to be a shared library in /usr/lib or wherever, it could blow up at runtime because of a library version mismatch.
When developing locally, use `cargo test` in your cli. When deploying to the server, build the Docker image on CI. If it takes 5 minutes to build it, so be it.
My 2c on this is nearly ditching rust for game development due to the compile times, in digging it turned out that LLVM is very slow regardless of opt level. Indeed it's what the Jai devs have been saying.
So Cranelift might be relevant for OP, I will shill it endlessly, took my game from 16 seconds to 4 seconds. Incredible work Cranelift team.
But it’s also probable that 16 seconds was fairly early in development and it would get much worse from there.
Performance matters.
https://github.com/TheBevyFlock/bevy_simple_subsecond_system
In C/C++ I don't even have to worry about it.
Out of interest what were they?
The one that immediately comes to mind is cvc5... not super recently though.
I suspect that "tried to" is doing a bit of work here. The fact that it was failing and swapping out probably meant that the more memory heavy g++ processes were going slower than the memory light ones, resulting in more of them running simultaneously than would likely have happened in a normal successful build. Still, this was on a system with 32GB of ram, so it was using roughly that before swapping would slow down more memory intensive processes.
Oops, changed one template in one header. And that impacts.... 98% of my code.
I don't know enough Rust, but I find these aspects are seriously lacking in C++ on Linux, and it is one of the few things I think Windows has it better for developers. Is Rust better?
For me, the ideal debugger is one you never leave. That is you are in a debugging session, maybe with your code running, or stopped on a breakpoint, and you write your code without leaving the session. You can see the values of your variables as you type them, the branches that will be taken, etc... When an error condition happen, you break on it, and still without leaving the session, you can fix the code, roll back before the error happened and see if it passes. IntelliJ is close to that, and it seems like some tools from the video game industry are even better.
Debugging should be natural, it shouldn't be something you pull out as a last resort. If it is not natural, it is a bad debugger, or a bad development environment, period. Maybe there are reasons for why it is bad, maybe the language designers have other priorities, which is acceptable, but it doesn't change the fact that it is bad. Same goes for slow compile times by the way.
Relevant: Subsecond: A runtime hotpatching engine for Rust hot-reloading - https://news.ycombinator.com/item?id=44369642 - June, 2024 (36 comments)
> Full IDE?
https://www.jetbrains.com/rust/ (newly free for non-commercial use)
> find these aspects are seriously lacking in C++ on Linux
https://www.jetbrains.com/clion/ (same, non-commercial)
I've only ever really used a debugger on embedded, we used gdb there. I know VS: Code has a debugger that works, I'm sure other IDEs do too.
> edit and continue
Hard to do in a pre-compiled language with no runtime, if you're asking about what I think you're asking about.
> Hot reload
Other folks gave you good links, but this stuff is pretty new, so I wouldn't claim that this is great and often good and such.
> Full IDE
I'm not aware of Rust-specific IDEs, but many IDEs have good support for Rust. VS: Code is the most popular amongst users according to the annual survey. The Rust Project distributes an official LSP server, so you can use that with any editor that supports it.
And I mentioned it as a downside of C++ on Linux, and I would expect a language that has "the best" tooling to have that.
C++ tooling isn't that great, but it has one thing going for it: it is popular in the video game industry, and the video industry has some of the best tools.
And sure enough, if by tooling you mean "package management", I'd say everything is better than C++, and on the other side, it seems that cargo is pretty good. I don't know how they tackle the "left-pad" problem that plagues npm though. By that I mean supply-chain attacks.
Btw, left-pad fallout wasn't all that bad. It's not like the author put something malicious into the code. For less than a day, people couldn't download that dep from npm. If someone really needed to fix a build, they could copy in a backup. Pretty sure a typical C++ or Python project build gets broken on its own more often than that.
Idk either, but code audits are definitely a solution. Take Debian packages for instance. Debian has package maintainers, and while they may no do full audits, they will at least test it before publishing. In addition, it doesn't get in the "stable" release before an extensive testing phase. Security patches are usually backported.
Or do like with the Apple App Store, where you don't get to publish anything unreviewed.
These are not perfect solution, there is no such thing as a perfect solution. For instance, Debian is famously lagging behind in versions, and the App Store will sometimes reject your app for no good reason, while being expensive. In every case there is some barrier to entry, a slow process, and it costs time and money, but that mitigates some of the issues.
Npm seems to have very little safeguards, has a culture of always taking the latest version, and as a result is often victim to supply-chain attacks. I don't think it is just popularity. Debian is really popular too, but AFAIK, it doesn't have this problem, in fact, one of the best known supply-chain attack is the xz library, and Debian didn't fall to it.
A.k.a. "Remember the Vasa!" https://news.ycombinator.com/item?id=17172057
New features: yes
Talking to users and fixing actual problems: lolno, I CBF
Thanks to pre-compiled headers, incremental compiler, incremental linker, and using binary libraries for all dependencies. Nowadays modules as well.
Rust compiles from scratch, some crates might get compiled multiple times due to conflicting configurations on the dependency graph, binary libraries require additional setup for something like scache.
Works great with docker: upon new compiler version or major website update, rebuild the layer with the incremental cache; otherwise just run from the snapshot and build newest website update version/state, and upload/deploy the resulting static binary. Just set so that mere code changes won't force rebuilding the layer that caches/materializes the fresh clean build's incremental compilation cache.
andy@bark ~/d/andrewkelley.me (master)> zig build --watch -fincremental
Build Summary: 3/3 steps succeeded
install success
└─ run exe compile success 57ms MaxRSS:3M
└─ compile exe compile Debug native success 331ms
Build Summary: 3/3 steps succeeded
install success
└─ run exe compile success 56ms MaxRSS:3M
└─ compile exe compile Debug native success 17ms
watching 75 directories, 1 processesRust is a large and robust language meant for serious systems programming. The scope of problems Rust addresses is large, and Rust seeks to be deployed to very large scale software problems.
These two are not the same and do not merit an apples to apples comparison.
edit: I made some changes to my phrasing. I described Zig as a "toy" language, which wasn't the right wording.
These languages are at different stages of maturity, have different levels of complexity, and have different customers. They shouldn't be measured against each other so superficially.
(EDIT: The parent has since edited this comment to contain more than just "zig bad rust good", but I still think the combative-ness and insulting tone at the time I made this comment isn't cool.)
Respectfully, the parent only offers up a Zig compile time metric. That's it. That's the entire comment.
This HN post about Rust is now being dominated by a cheap shot Zig one liner humblebrag from the lead author of Zig.
I think this thread needs a little more nuance.
Being frustrated by perceived bad behavior doesn't mean responding with more bad behavior is a good way to improve the discourse, if that's your goal here.
That's correct, but slinging cheap shots at each other is not how discussions on this site are supposed to be.
> I think this thread needs a little more nuance.
Yes, but your comment offers none.
That's not what I said. I said it's unlikely that fast compilation cannot be achieved while using LLVM which, I would argue, is proven by the existence of a fast compiler that uses LLVM.
this is a terrible look for your whole community
All Zig code is built in a single compilation unit and everything is compiled from scratch every time you change something, including all dependencies and all the parts of the stdlib that you use in your project.
So you've been comparing Zig rebuilds that do all the work every time with Rust rebuilds that cache all dependencies.
Once incremental is fully released you will see instant rebuilds.
https://bitemyapp.com/blog/rebuilding-rust-leptos-quickly/
https://old.reddit.com/r/rust/comments/1i2pr2e/improve_rust_...
https://old.reddit.com/r/rust/comments/ua09tc/experimental_f...
https://old.reddit.com/r/rust/comments/1k9ihhn/does_breaking...
https://old.reddit.com/r/rust/comments/x9z4cm/speeding_up_in...
https://old.reddit.com/r/rust/comments/rlszeq/the_best_cpu_f...
https://old.reddit.com/r/rust/comments/1hpuy01/why_you_need_...
https://old.reddit.com/r/rust/comments/1h9bdbr/rust_llvm_by_...
https://old.reddit.com/r/rust/comments/1j1rvy1/help_me_under...
Anyhoodle, I'm looking forward to testing the compile times again when Zig says the build times are fast now.
But if we're talking about incrementality, I look forward to testing that too when it's ready. I've got a Bazel build for work that pulls together Rust along with a custom (very slow) compiler and the cached successful pipelines take 2-3 minutes (mostly the benchmark run) and the ones that churned the non-rust take 15-18 minutes, of which about 10-11 minutes is just compiling the non-rust.
One major difference is the way each project considers compiler performance:
The Rust team has always cared to some degree about this. But, from my recollection of many RFCs, "how does this impact compiler performance" wasn't a first-class concern. And that also doesn't really speak to a lot of the features that were basically implemented before the RFC system existed. So while it's important, it's secondary to other things. And so while a bunch of hard-working people have put in a ton of work to improve performance, they also run up against these more fundamental limitations at the limit.
Andrew has pretty clearly made compiler performance a first-class concern, and that's affected language design decisions. Naturally this leads to a very performant compiler.
Do you have a list off the top of your head/do you know of a decent list? I've now read many "compiler slow" thoughtpieces by many people and I have yet to see someone point at a specific feature and say "this is just intrinsically harder".
I believe that it likely exists, but would be good to know what feature to get mad at! Half joking of course
You can't have a language with 100% of the possible runtime perf, 100% of the possible compile speed and 100% of the possible programmer ease-of-use.
At best you can abuse the law of diminishing returns aka the 80-20 rule, but that's not easy to balance and you run the risk of creating a language that's okay at everything, but without any strong selling points, like the stellar runtime performance Rust is known for.
So a better way to think about it is: Given Rust's numerous benefits, is having subpar compilation time really that big of a deal?
As someone who uses Rust as a daily driver at work at zed.dev (about 600K LoC of Rust), and Zig outside of work on roc-lang.org (which was about 300K LoC of Rust before we decided to rewrite it in Zig, in significant part because of Rust's compilation speed), yes - it is an absolutely huge deal.
I like a lot of things about Rust, but its build times are my biggest pain point.
It leads to blithe things about how there's no such things as zero-cost abstractions. But at one point the cost is so low and amortized that you're looking at something that's basically free.
What is the compilation cost of the `?` syntax shorthand? Probably quite low!
What about the compilation cost of underscores in number literals? Again, quite low?
To this point a bit, I think a lot of people talk about the borrow checker, but my understanding is it's fairly low cost, and I don't worry about it.
Monomorphisation costs though? That feels like something that could generate a lot of work.
Let's dig into this bit of that, to give you some more color:
> Split compiler/package manager — although it is normal for languages to have a package manager separate from the compiler, in Rust at least this results in both cargo and rustc having imperfect and redundant information about the overall compilation pipeline. As more parts of the pipeline are short-circuited for efficiency, more metadata needs to be transferred between instances of the compiler, mostly through the filesystem, which has overhead.
> Per-compilation-unit code-generation — rustc generates machine code each time it compiles a crate, but it doesn’t need to — with most Rust projects being statically linked, the machine code isn’t needed until the final link step. There may be efficiencies to be achieved by completely separating analysis and code generation.
Rust decided to go with the classic separate compilation model that languages like C use. Let's talk about that compared to Zig, since it was already brought up in this thread.
So imagine we have a project, A, and it depends on B. B is a huge library, 200,000 lines of code, but we only use one function from it in A, and that function is ten lines. Yes, this is probably a bad project management decision, but we're using extremes here to make a point.
Cargo will compile B first, and then A, and then link things together. That's the classic model. And it works. But it's slow: rust had to compile all 200,000 lines of code in B, even though we only are gonna need ten lines. We do all of this work, and then we throw it away at the end. A ton of wasted time and effort. This is often mitigated by the fact that you compile B once, and then compile A a lot, but this still puts a lot of pressure on the linker, and generics also makes this more complex, but I'm getting a bit astray of the main point here, so I'll leave that alone for now.
Zig, on the other hand, does not do this. It requires that you compile your whole program all at once. This means that they can drive the compilation process beginning from main, in other words, only compile the code that's actually reachable in your program. This means that in the equivalent situation, Zig only compiles those ten lines from B, and never bothers with the rest. That's just always going to be faster.
Of course, there are pros and cons to both of these decisions, Rust made the choice it did here for good reasons. But it does mean it's just going to be slower.
I suppose a lot of the coherence checking still "needs" to happen, but how I would love a "--i-dont-care-about-coherence-in-dependent-traits" flag or something. I know I'm missing a lot
There is ino operator overloading like C, so A + B can only mean one thing.
You can't redeclare a variable, so foo can only map to one thing.
The list goes on.
Basically it was designed to compile faster, and that means many issues on Github have been getting rejected in order to keep it that way. It's full of compromises.
What I'm more interested to know is what the runtime performance tradeoff is like now; one really has to assume that it's slower than LLVM-generated code, otherwise that monumental achievement seems to have somehow been eclipsed in very short time, with much shorter compile times to boot.
> Fil-C achieves this using a combination of concurrent garbage collection and invisible capabilities (each pointer in memory has a corresponding capability, not visible to the C address space)
With significant performance and memory overhead. That just isn't the same ballpark that Rust is playing in although hugely important if you want to bring forward performance insensitive C code into a more secure execution environment.
> Fil-C is currently 1.5x slower than normal C in good cases, and about 4x slower in the worst cases.
with room for optimization still. Compatibility has improved massively too, due to big changes to how it works. The early versions were kind of toys, but if Filip's claims about the current version hold up then this is starting to look like a very useful bit of kit. And he has the kind of background that means we should take this seriously. There's a LOT of use cases for taking stuff written in C and eliminating memory safety issues for only a 50% slowdown.
Your first claim is unverifiable and the second one is just so, so wrong. Even big projects with very talented, well-paid C or C++ devs eventually end up with CVEs, ~80% of them memory-related. Humans are just not capable of 0% error rate in their code.
If Zig somehow got more popular than C/C++, we would still be stuck in the same CVE bog because of memory unsafety. No thank you.
Zig does a lot of things to prevent or detect memory safety related bugs. I personally haven't encountered a single one so far, while learning the language.
> ~80% of them memory-related.
I assume you're referencing the 70% that MS has published? I think they categorized null pointer exceptions as memory safety bugs as well among other things. Zig is strict about those, has error unions, and is strict and explicit around casting. It can also detect memory leaks and use after free among other things. It's a language that's very explicit about a lot of things, such as control flow, allocation strategies etc. And there's comptime, which is a very potent tool to guarantee all sorts of things that go well beyond memory safety.
I almost want to say that your comment presents a false dichotomy in terms of the safety concern, but I'm not an expert in either Rust or Zig. I think however it's a bit broad and unfair.
Until you guys write an actual formal specification, the compiler is the language.
The project is adopting Ferrocene for the spec.
Yes, the soundness hole itself is low impact and doesn't need to be prioritized but it undermines the binary "Zig is definitively not memory-safe, while safe Rust, is, by definition, memory-safe" argument that was made in response to me. Now you're dealing with qualitative / quantitative questions of practical impact, in which my original statement holds: "Zig is less memory safe than Rust, but more than C/C++. Neither Zig nor Rust is fundamentally memory safe."
You can of course declare that Safe Rust is by definition memory safe, but that doesn't make it any more true than declaring that Rust solves the halting problem or that it proves P=NP. RustBelt is proven sound. Rust by contrast, as being documented by Ferrocene, is currently fundamentally unsound (though you won't hit the soundness issues in practice).
- If a safe Rust program exhibits a memory safety problem, it is a bug in the Rust compiler that is to be fixed - If a Zig program exhibits a memory safety problem, it is a bug in the Zig program that needs to be fixed, not in the compiler
Wouldn't you agree?
> Ferrocene is intended to document the behavior of the current version of the rustc compiler, so it's just an effort to formalize "the compiler is the language".
I must admit I haven't read the specification, but I doubt they attempt to be "bug for bug" compatible in the sense that the spec enumerates memory safety bugs present in the Rust compiler. But am I then mistaken?
As to the Ferrocene specification, it explicitly states "Any difference between the FLS and the behavior of the Rust compiler is considered an error on our part and the FLS will be updated accordingly."
Proposals to fix the soundness hole in Rust either change the variance rules themselves, or require where clauses in certain places. Either of these changes would require corresponding changes to chapter 4 of the Ferrocene specification.
I really don’t see how you can claim with a straight face that the two approaches are the same.
Look, I'm not saying the Zig and Rust approaches are the same. I explicitly stated that Rust is more memory safe than Zig (which is in turn more memory safe than C/C++).
This is because Rust has clearly delineated a "safe" subset of Rust which you have to explicitly opt out of that is mostly sound (and has a goal of eventually being entirely sound), has a culture of encouraging the use of the safe subset, and has taken a good approach to the interfacing of safe and unsafe code (i.e. if unsafe code is properly written and satisfies the exposed contract - despite the compiler being unable to verify this - then safe code can safely be linked with it).
All of this results in extremely low risk of memory corruption for Rust programs in practice (far lower than any other commonly used non-GC language with the sole exception of SPARK).
What you can't do though is reject the notion of memory safety being a sliding scale and draw a binary distinction between languages that are 100% perfectly memory safe and languages that are memory unsafe. Well you can, but Rust will fall on the side of memory unsafe for many years to come. Java (ignoring vendor-specific extensions) falls on the safe side though - the language semantics as specified are sound and it doesn't even have an unsafe subset.
Look, Zig has neat ideas. No disputing that. But on the sliding scale there’s a threshold where people are comfortable classifying something as being memory safe to avoid perfect being the enemy of good. And by that classification criteria, Zig falls well below the bar and Rust clears it easily.
Right, this is from before it's adopted as the actual spec, because it was from outside the project, and so could not be.
Also, these goalposts are moving: it was "Rust doesn't have a spec" and now it's "I don't like the spec."
Fixing this soundness hole does not require a breaking change to the language. It is an implementation bug, not a problem with the language as specified. But even if it were, Rust's policies around soundness do allow for this, and the project has done it in the past.
If there is a proposed fix to the soundness hole that wouldn't reject some existing sound Rust code, please link to it; none of the proposed fixes I've seen do so. And yes, Rust's policies do allow for breaking changes in pursuit of soundness - likely some day many years from now safe Rust will indeed be sound and guaranteed to be memory safe.
That is the absolute best description of memory safety I’ve heard expressed.
[1] The cult of the orange man would call this a plurality, which may be what has tripped you up, but the civilized world calls it a majority.
But by implementation and spec definitely not.
Edit: apparently I am replying to the main Zig author? Language evangelism is by far the worst part of Rust and has likely stirred up more anti Rust sentiment than “converting” people to Rust. If you truly care for your language you should use whatever leverage you have to steer your community away from evangelism, not embrace it.
This comment would be a lot better if it engaged with the posted article, or really had any sort of insight beyond a single compile time metric. What do you want me to take away from your comment? Zig good and Rust bad?
> A brief note: 50 seconds is fine, actually!
50 seconds should actually not be considered fine.
Now we get all of this off-topic discussion about Zig. Which I guess is good for you Zig folk... But it's pretty off-putting for me.
whoisyc's comment is extremely on point. As the VP of community, I would really encourage thinking about what they said.
Having concrete proof that something can be done more efficiently is extremely important and, no, I haven't "demonstrated" anything, since my earlier comment would have had way less substance to it without the previous context.
The comment from Andrew is not just random compiler stats, but a datapoint showing a comparable example having dramatically different performance characteristics.
You can find in this very HN submission various comments that assume that Rust's compiler performance is impossible to improve because of reasons that actually are mostly (if not entirely) irrelevant. Case in point, see people talking about how Rust compilation must take longer because of the borrow checker (and other safety checks) and Steve pointing out that, no, actually that part of the compilation pipeline is very small.
> Now we get all of this off-topic discussion about Zig.
So no, I would argue the opposite: this discussion is very much on topic.
And it can be considerably faster if you use something like subsecond[0] (which does incremental linking and hotpatches the running binary). It's not quite as fast as Zig, but it's close.
However, if that 331ms build above is a clean (uncached) build then that's a lot faster than a clean build of my website which takes ~12s.
```
> cargo clean && time cargo build
cargo build 713.80s user 91.57s system 706% cpu 1:53.97 total
> cargo clean && time cargo build --release
cargo build --release 1619.53s user 142.65s system 354% cpu 8:17.05 total
```
this is without incremental compilation. And it's not like you have to babysit a release build if you have a CI/CD system
https://corrode.dev/blog/tips-for-faster-rust-compile-times/...
FWIW - last stage where the binary is produced takes the longest and is single threaded and that's the largest difference between release and debug.
At a quick glance, most benchmarks show only 50% to 60% single threaded improvement between M1 and M4.
That wouldn't explain compilation times going from 6 minutes to 2 minutes.
I think this post (accidentally?) conflates two different sources of slowness:
1) Building in docker 2) The compiler being "slow"
They mention they could use bind mounts, yet wanting a clean build environment - personally, I think that may be misguided. Rust with incremental builds is actually pretty fast and the time you lose fighting dockers caching would likely be made up in build times - since you'd generally build and deploy way more often than you'd fight the cache (which, you'd delete the cache and build from scratch in that case anyway)
So - for developers who build rust containers, I highly recommend either using cache mounts or building outside the container and adding just the binary to the image.
2) The compiler being slow - having experienced ocaml, go and scala for comparisons the rust compiler is slower than go and ocaml, sure, but for non interactive (ie, REPL like) workflows, this tends not to matter in my experience - realistically, using incremental builds in dev mode takes seconds, then once the code is working, you push to CI at which point you can often accept the (worst case?) scenario that it takes 20 minutes to build your container since you're free to go do other things.
So while I appreciate the deep research and great explanations, I don't think the rust compiler is actually slow, just slower than what people might be use to coming from typescript or go for example.
The slowness is because everyone has to write code with generics and macros in Java Enterprise style in order to show they are smart with rust.
This is really sad to see but most libraries abuse codegen features really hard.
You have to write a lot of things manually if you want fast compilation in rust.
Compilation speed of code just doesn’t seem to be a priority in general with the community.
Refactoring seems to take about the same time too so no loss on that front. After all is said and done I'm just left with various logic bugs to fix which is par for the course (at least for me) and a sense of wondering if I actually did everything properly.
I suppose maybe two years from now we'll have people that suggest avoiding generics and tempering macro usage. These days most people have heard the advice about not stressing over cloning and unwraping (though expect is much better imo) on the first pass more or less.
Something something shiny tool syndrome?
they have only one priority, memory safety (from a certain class of memory bugs)
> To get your Rust program in a container, the typical approach you might find would be something like:
If you have `cargo build --target x86_64-unknown-linux-musl` in your build process you do not need to do this anywhere in your Dockerfile. You should compile and copy into /sbin or something.
If you really want to build in a docker image I would suggest using `cargo --target-dir=/target ...` and then run with `docker run --mount type-bind,...` and then copy out of the bind mount into /bin or wherever.
you can enable word wrapping as a workaround ( `:set wrap`). Lifehack: it can be hard to navigate in such file with just `h, j, k, l`, but you can use `gh, gj, etc`. With `g` vim will work with visual lines, while without it with just lines splitted with LF/CRLF
"Make k/j up/down work more naturally by going to the next displayed line vs
"going to the next logical line (for when word-wrapping is on):
noremap k gk
noremap j gj
noremap <up> gk
noremap <down> gj
"Same as above, but for arrow keys in insert mode:
inoremap <up> <Esc>gka
inoremap <down> <Esc>gjaDamn, this makes such a great ad.
>Build a new statically linked binary (with --target=x86_64-unknown-linux-musl) >Copy it to my server >Restart the website
Isn't it a basic C compiler feature that you can compile a file as an Object, and then link the objects into a single executable? Then you only recompile the file you changed.
Not sure what I'm missing.
The problem has been created by Docker which destroys all of the state. If this was C, you'd also end up losing all of the object files and rebuilding them every time.
I wrote up a lot of my ideas in a blog post mostly to avoid having to repeat my thoughts on this every time it comes up: https://saghm.com/cargo-features-rust-compile-times/
What? That's absolutely ideal! It's incredibly simple. I wish deployment processes were always that simple! Docker is not going to make your deployment process simpler than that.
I did enjoy the deep dive into figuring out what was taking a long time when compiling.
If anyone out there is already fully committed to using only Alpine Linux, I'd recommend trying creating native packages at least once.
Personally I don't care anymore, since I do hotpatching:
https://lib.rs/crates/subsecond
Zig is faster, but then again, Zig isn't memory save, so personally I don't care. It's an impressive language, I love the syntax, the simplicity. But I don't trust myself to keep all the memory relevant invariants in my head anymore as I used to do many years ago. So Zig isn't for me. Simply not the target audience.
https://news.ycombinator.com/item?id=44234080
(Rust compiler performance; 287 points, 261 comments)
The local builds are fast, why would you rebuild docker for small changes?
Also why is a personal page so much rust and so many dependencies. For a larger project with more complex stuff you’d have a test suite that takes time too. Run both in parallel in your CI and call it a day.
Here's a somewhat dated but still good overview of various approaches to generics in different languages including C++, Rust, Swift, and Zig and their tradeoffs: https://thume.ca/2019/07/14/a-tour-of-metaprogramming-models...
Really there are much larger issues that I have to deal with that build time does not affect.
DFA in the front end means slow.
Also, the article goes into great depth as to what is happening there, and the borrow checker never comes up.
Doing this on the whole program eats a lot of memory.
However, in my understanding, it takes that IR, does build a borrow graph, computes liveliness, and then does inference. There's been a number of details in how this has changed over the years, but it's vaguely datalog shaped.
xkcd is always relevant: https://xkcd.com/303/
When I had to deal with this I would just open the newspaper and read an article in front of my boss.
Cargo is the standard build system for Rust projects, though some users use other ones. (And some build those on top of Cargo too.)
Sadly, the compile time is just as bad, but I think in this case the allocator is the biggest culprit, since disabling optimization will degrade run-time performance. The Rust team should maybe look into shipping their own bundled allocator, "native" allocators are highly unpredictable.
[^1]: https://www.fermyon.com
> * Borrowing — Rust’s defining feature. Its sophisticated pointer analysis spends compile-time to make run-time safe.
> * Monomorphization — Rust translates each generic instantiation into its own machine code, creating code bloat and increasing compile time.
> * Stack unwinding — stack unwinding after unrecoverable exceptions traverses the callstack backwards and runs cleanup code. It requires lots of compile-time book-keeping and code generation.
> * Build scripts — build scripts allow arbitrary code to be run at compile-time, and pull in their own dependencies that need to be compiled. Their unknown side-effects and unknown inputs and outputs limit assumptions tools can make about them, which e.g. limits caching opportunities.
> * Macros — macros require multiple passes to expand, expand to often surprising amounts of hidden code, and impose limitations on partial parsing. Procedural macros have negative impacts similar to build scripts.
> * LLVM backend — LLVM produces good machine code, but runs relatively slowly. Relying too much on the LLVM optimizer — Rust is well-known for generating a large quantity of LLVM IR and letting LLVM optimize it away. This is exacerbated by duplication from monomorphization.
> * Split compiler/package manager — although it is normal for languages to have a package manager separate from the compiler, in Rust at least this results in both cargo and rustc having imperfect and redundant information about the overall compilation pipeline. As more parts of the pipeline are short-circuited for efficiency, more metadata needs to be transferred between instances of the compiler, mostly through the filesystem, which has overhead.
> * Per-compilation-unit code-generation — rustc generates machine code each time it compiles a crate, but it doesn’t need to — with most Rust projects being statically linked, the machine code isn’t needed until the final link step. There may be efficiencies to be achieved by completely separating analysis and code generation.
> * Single-threaded compiler — ideally, all CPUs are occupied for the entire compilation. This is not close to true with Rust today. And with the original compiler being single-threaded, the language is not as friendly to parallel compilation as it might be. There are efforts going into parallelizing the compiler, but it may never use all your cores.
> * Trait coherence — Rust’s traits have a property called “coherence”, which makes it impossible to define implementations that conflict with each other. Trait coherence imposes restrictions on where code is allowed to live. As such, it is difficult to decompose Rust abstractions into, small, easily-parallelizable compilation units.
> * Tests next to code — Rust encourages tests to reside in the same codebase as the code they are testing. With Rust’s compilation model, this requires compiling and linking that code twice, which is expensive, particularly for large crates.
[1]: https://www.pingcap.com/blog/rust-compilation-model-calamity...
For all the C++ laughing in this thread, there's really only one thing that makes C++ slow - non-`extern` templates - and C++ gives you a lot more space to speed them up than Rust does.
As for templates, I can't think of anything about them that would speed up things substantially wrt Rust aside from extern template and manually managing your instantiations in separate .cpp files. Since otherwise it's fundamentally the same problem - recompiling the same code over and over again because it's parametrized with different types every time.
Indeed, out of the box I would actually expect C++ to do worse because a C++ header template has potentially different environment in every translation unit in which that header is included, so without precompiled headers the compiler pretty much has to assume the worst...
It doesn't.