I tried your challenge, and the first data point I uncovered contradicts this. Here is the source code of both programs: https://gist.github.com/anonymous/f01fc324ba8cccd690551caa43... --- The Rust program doesn't use unsafe, doesn't explicitly use C code, is shorter than the Go program, faster in terms of CPU time and uses less memory. I ran the following:
$ /usr/bin/time -v ./lossolo-go /tmp/OpenSubtitles2016.raw.sample.en the
$ /usr/bin/time -v ./target/release/lossolo-rust /tmp/OpenSubtitles2016.raw.sample.en the
The Go program takes ~6.5 seconds and has a maximum heap usage of 7.7 MB. The Rust program takes ~4.2 seconds and has a maximum heap usage of 6 MB. (As measured by GNU time using `time -v`.)
IMO, both programs reflect "naive" solutions. The point of me doing this exercise is to show just how silly this is, because now we're going to optimize these programs, but we'll limit ourselves to smallish perturbations in order to put a reasonable bound on the task.
If I run the Go program through `perf record`, the top hotspot is runtime.mallocgc. Now, I happen to know from experience that Scanner.Text is going to allocate a new string while Scanner.Bytes will not. I also happen to know that the Go standard library `bytes` package recently got a nice optimization that makes bytes.Contains as fast as strings.Contains: https://github.com/golang/go/commit/44f1854c9dc82d8dba415ef1... --- Since reading into a Go `string` doesn't actually do any UTF-8 validation, we don't lose anything by switching to using raw bytes.
Knowing this, we can tweak the Go program to great effect: https://gist.github.com/anonymous/c98dc8f6be6d414ae3e7aa6931... --- Running the same command as above, we now get a time of ~2.3 seconds and a maximum heap usage of 1.6 MB. That's impressive.
Now let's see if we can tweak Rust, which is now twice as slow as the Go program. Running perf, it looks like there's an even split between allocation, searching and UTF-8 validation, with a bit more towards searching. Like the Go program, let's attack allocation. In this case, I happen to know that the `lines` method returns an iterator that yields `String` values, which implies that it's allocating a fresh `String` for every line, just like our Go program was. Can we get rid of that? The BufReader API provides a `read_line` method, which permits the caller to control the `String` allocation. If we use that, our Rust program is tweaked to this: https://gist.github.com/anonymous/a6cf1aa51bf8e26e9dda4c50b0... --- It's not quite as symmetrical as a change as we made to the Go program, but it's pretty straight-forward IMO. Running the same command as above, we now get a time of ~3.3 seconds and a maximum heap usage of 6 MB.
OK, so we're still slower than the Go program. Looking at the profile again, the time now seems split completely between searching and UTF-8 validation. The allocation doesn't show up at all any more.
Is this where you got stuck? The next step from here isn't straight-forward because getting rid of the UTF-8 validation isn't possible to do safely while still using the String/&str search APIs. Notably, Rust's standard library doesn't provide a way to search an `&[u8]` directly using optimized substring search routines. Even if you knew your input was valid UTF-8 before hand, there's no obvious place to insert an unsafe `from_utf8_unchecked` because the BufReader itself is in control of producing the string contents. (You could do this by switching to using `BufReader.read_until` and then transmuting the result into an &str, but that would require unsafe.)
Let's take a leap. Rust's regex library has a little known feature that it can actually search the contents of an &[u8]. Rust's regex library isn't part of the standard library, but it is maintained as an official crate by the Rust project. If you know all of this, then it's possible to tweak the Rust program just a bit more to regain the speed lost by UTF-8 checking: https://gist.github.com/anonymous/bfa42d4f86e03695f3c880aace... --- Running the same command as above once again, we now get a time of ~2.1 seconds and a maximum heap usage of 6.5 MB.
In sum, we've beaten Go in CPU time, but lost the Battle for Memory and the battle for obviousness. Beating Go required noticing the `read_until` API of BufReader and knowing that 1) Rust's regexes are fast and 2) they can search &[u8] directly. It's not entirely unreasonable, but to be fair, I've done this without explicitly using any unsafe or any C code.
None of this process was rocket science. Both the Go and Rust programs were initially significantly sub-optimal because of allocation, but after some light profiling, it was possible to speed up both programs quite a bit.
Compared to the naive solution, some of our search tools can be a lot faster. Performing the same query on the same corpus:
ripgrep 1.13 seconds, 7.7 MB
ripgrep 1.35 seconds, mmap
GNU grep 1.73 seconds, 2.3 MB
ag 1.80 seconds, mmap
pt 6.41 seconds, mmap
sift 50.21 seconds, 16.6 MB
From here, the next step would be stop parsing lines and start searching the entire buffer directly. (I hope to make even this task very easy by moving some of the searching code inside of ripgrep to an easy to use library.)
In sum, your litmus test essentially comes down to these trade offs:
- Rust provides a rich API for its String/&str types, which are guaranteed to be valid UTF-8.
- Rust lacks a rich substring search API in the standard library for Vec<u8>/&[u8] types. Because of this, efficient substring search using only the standard library has an unavoidable UTF-8 validation cost in safe code.
- Go doesn't do any kind of UTF-8 checking and provides mirrored substring search APIs between its `bytes` and `strings` packages.
- The actual performance of searching in both programs probably boils down to optimized SIMD algorithms. Therefore, once you get past the ability to search each line of a file with minimal allocation, you've basically hit a wall that's probably the same in most mainstream languages.
In my opinion, these trade offs strike me as something terribly specific, and it's probably not something that is usefully generalizable. More than that, in the naive case, Rust is doing you a good service by checking that your input is valid UTF-8, which is something that Go doesn't do. I think this could go either way, but I think it's uncontroversial that guaranteeing valid UTF-8 up front like this probably eliminates a few possibly subtle bugs. (I will say that my experience with text encoding in Go has been stellar though.)
Most importantly, both languages at least have a path to writing a very fast program, which is often what most folks end up caring about at the end of the day.
Do you think you could refactor out bytestring-based string manipulation into its own library? Even better would be something that worked for all encodings (using https://github.com/servo/tendril or something)
IIRC, someone was working on making the Pattern trait work on &[u8], but I'm guessing that work is stalled.
To factor it out into a separate crate means copying the &str substring routines, since there's no way to safely use them on an &[u8] from the standard library. (bluss did that in the `twoway` crate, so we could just use that.)
It does seem like a plausible thing to do, at least until std gets better &[u8] support.
> Even better would be something that worked for all encodings
I suspect the standard practice here is something like "transcode to UTF-8 and then search the UTF-8." (This is what I hope to do with ripgrep.)
> (using https://github.com/servo/tendril or something)
I don't think I know what problems tendril is solving, so it's not clear to me what it's role is.
EDIT: and how can you have time to write this? I just usually close the browser tab when this situation occurs...
My opinion in this case is empirically checked. I am not saying this to start flame war, I am just showing my observations in particular example. I can also say that Rust regex implementation eats Go regex implementation by magnitudes (performance wise) and it will also be true and I am not looking for any flame war in this case also. I am only sharing my experience that I've backed up with proofs (code + perf results) for that particular use case. This is a factual discussion, I don't agree it's pointless.
It's 2.6 seconds for Go and 3.5 seconds for Rust, both perf results and code here: http://pastebin.com/WwhvHH6S
Your Go program is not what I would expect. A bufio.Scanner is the idiomatic (and naive) way to read lines in Go. But this is immaterial. Your results are consistent with mine. They aren't different. I just included more analysis and more programs to provide proper context to this challenge of yours.
Using grep 0.6s
Then I have installed rigrep and...
Using ripgrep 0.4s
Really nice burntsushi. I am surprised by those (ripgrep) results compared to grep.
Using a `lines()` approach is naive because that allocates owned heap-allocated strings. An optimal, non-naive solution would not use heap allocation for buffering lines but use a stack-allocated array. That alone would bring significant speedup versus the line approach.
As for ripgrep, it's a pretty comprehensive application that makes use of SIMD/AVX so it's only natural that it's fast.
It took 4.6s which only confirms what I wrote on beginning when we started this discussion. Perf counters for your solution in here:
As for timing, I'm doubtful that Go is any faster than Rust. I don't have this www.js file so I can't test it on my laptop, but I'm pretty sure you didn't even attempt to do things like enabling LTO, setting O3, disabling jemalloc, and using the musl target. All these things can make significant differences to the performance of the binary that's produced.
For me it's not naive solution. Do you have any proof it is? Can you mathematically prove that it's naive solution? I know I can't. For everyone naive solution is something different, what I saw in burntsushi reply and what I wrote myself is the closest to what I think are naive solutions.
> like enabling LTO, setting O3, disabling jemalloc, and using the musl target.
And this is for sure not part of naive solution either.
> You may not want to accept it because that contradicts your claim of the Go solution being faster
This is not true. You can find perf numbers of his solution in my second reply to him. Or you can compare those solutions yourself.
You can't prove a negative.