8 ms·

>> I’m looking forward to someone improving the performance of Go’s regexp package, which is quite slow. Hah, this reminds me how over several years ago, I rew

• throwaway894345 5y ago
  Yeah, if you can call straight into a C module (e.g., regex or csv or etc) and not do anything of consequence in Python, that’s the sweet spot from a performance perspective.
• benhoyt 5y ago
  Interesting, though not too surprising. Do you remember what the regexes were that your assignment used? Go's regexp package does have a couple of advantages over Python, Perl, and so on: 1) it's guaranteed linear time in the length of the input, regardless of the regex, see https://swtch.com/~rsc/regexp/regexp1.html https://swtch.com/~rsc/regexp/regexp1.html, and 2) it's a relatively simple implementation.
  • pcwalton 5y ago
    Simplicity of implementation isn't what users need, though; they need performance. For example, you can make GCC into a much simpler C compiler by compiling at -O0, but in practice nobody does that.
    • benhoyt 5y ago
      Totally agreed: almost all users (me/GoAWK included) want performance and don't care nearly as much about simplicity under the hood. Simplicity of implementation is of value for educational purposes, but we could easily have a small, simple 3rd party package for that. Go's regexp package is kinda too complex for a simple educational demonstration and too simple to be fast. :-) I actually tried BurntSushi's https://github.com/BurntSushi/rure-go https://github.com/BurntSushi/rure-go (bindings to Rust's regex engine) with GoAWK and it made regex handling 4-5x as fast for many regexes, despite the CGo overhead. However, rure-go (and CGo in general) is a bit painful to build, so I'm not going to use that. Maybe I'll create a branch for speed freaks who want it. I've also thought of using https://gitlab.com/cznic/ccgo https://gitlab.com/cznic/ccgo to convert Mawk's fast regex engine to Go source and see how that performs. Maybe on the next rainy day...
      • tedunangst 5y ago
        Have you considered writing your own string matcher for the simple cases like fixed patterns? I got some pretty solid wins just by guarding some regex executions with simple strings.indexof calls.
        • benhoyt 5y ago
          Yeah, that's a good idea, I did consider it, but haven't tried it yet. Do you hook and look at the regex string before it's compiled, or do you hook in at the parsed regex AST level? (eg: regexp/syntax in Go).
          • tedunangst 5y ago
            For something like awk, I think you'd look before compiling, then create your own matcher. With an abstract Matcher interface that regexp implements. It's C, but openbsd grep does something like this because libc regex is super slow. Look for fastcomp on https://github.com/openbsd/src/blob/master/usr.bin/grep/util.c https://github.com/openbsd/src/blob/master/usr.bin/grep/util... It's not super sophisticated, but enough to beat the full regex engine. In the go code where I did this, it was a little different, with a static pattern. Something like "(\w+) apple" to find all apple adjectives or whatever, but the regexp wasted so much time matching words before not apples. A quick scan for "apple" to eliminate impossible matches made it faster. This depends more on knowing regex and corpus, so probably less relevant for awk.
          • alex_muscar 5y ago
            I think GNU grep does something similar. When it has a fixed patter it uses Boyer-Moore [1]. [1]: https://lists.freebsd.org/pipermail/freebsd-current/2010-August/019310.html https://lists.freebsd.org/pipermail/freebsd-current/2010-Aug...
          • burntsushi 5y ago
            Go's regexp package even exposes a routine for this: https://pkg.go.dev/regexp#Regexp.LiteralPrefix https://pkg.go.dev/regexp#Regexp.LiteralPrefix It's been a while since I've looked at the source code, but it is almost certainly already doing basic prefix literal optimizations. The more advanced literal optimizations come into play when every match must start with one of a few possible characters or strings. Then you get into things like Aho-Corasick or fancy SIMD algorithms (Teddy).
    • cfors 5y ago
      Performance is relative, so I'm not really sure the point being made here. Sure if your program has regex as the constrained resource this matters, but again it's all relative.
    • jchw 5y ago
      I agree, but simplicity of implementation is a net positive in a vacuum. When balanced against things like performance, it's definitely worth some trade-offs for better performance... but simplicity of implementation definitely has lots of upsides that users indirectly benefit from. Therefore, I think it's important to at least have a balance.
    • tcmart14 5y ago
      I don't exactly agree. Sure end users don't care about implementation directly. But simplicity of implementation does affect them indirectly. Go is already over 10 years old with maybe many more years ahead. All code bases rot. I think the simpler the implementation, the easier it is to cure rot and code smells which hopefully means Go has a long life as the implementation becomes easier to work on over time. While user's maybe don't care, it does impact them.
      • pcwalton 5y ago
        You can make the same argument about CPUs. Modern CPUs are horrendously complex. But nobody is asking to remove, say, out-of-order execution on simplicity grounds, because that would hurt users and cost millions of dollars at scale for no reason other than engineering aesthetics. It's only in a few areas, like programming languages and operating systems, that we're obsessed with simplicity, and it makes little sense to me.
        • tcmart14 5y ago
          I'd say it is probably because we are all worst at writing code than we'd like to imagine. So writing necessarily complex code, especially in a FOSS compiler or system, makes little sense since some day someone else is going to have to step in and learn it.
        • Beltalowda 5y ago
          Branch prediction is a CPU "complexity" that got us in to some amount of trouble. I don't see simplicity as a "virtue", as such: it's all about the ability to reason about a system. The more complex it is, the harder this becomes. This makes it harder for implementers to work on it, and harder for users to figure out what is going wrong. On the other hand, complexity often offers useful enhancements such as features or performance. There is some amount of tension here, which is hardly unique to software: you see this in, say, tax systems, regulation/law, design of cars and all sort of things, etc.
    • pdpi 5y ago
      Simplicity of implementation also contributes to Go’s fast compile times, which is a different sort of performance. Trying to find a sweet spot between “slow” interpreted languages and “fast” compiled languages with long compile times (e.g. C++ template hell) is a worthy goal.
      • kaba0 5y ago
        I think multi-profile compilations is much better - have a really fast debug build that hardly does any optimizations, and a release one that can take whatever amount of time but will be really optimized.
    • Philip-J-Fry 5y ago
      Simplicity is what users indirectly need. Go is not about providing the fastest implementations out of the box, it's about having a broad toolset in the standard library to solve the problems Go was built for. Faster (and often more complex) implementations are a maintenance burden for Go contributors. It's far better for a high performance regex library to be a third party package for those that need it. For those where regex is a limiting factor in performance they'll soon find out why. But for most people fast regex is nothing compared to the overhead of a simple HTTP request.
    • rplnt 5y ago
      Regexp is one of the things you see attacks on all the time (mostly DOS). Users care a lot about security, and simplicity of implementation correlates with it. It's not something users need, but they do benefit from it.
    • Cthulhu_ 5y ago
      > Simplicity of implementation isn't what users need, though; they need performance. It's a tradeoff, in the end. I mean sure, users don't really need to know how things work under the hood, but the people building and maintaining the language do; Go's philosophies on maintainability extend to the language's internals as well. This is one reason why generics took over ten years to land; they needed to find the middle ground between functionality and sanity within the compiler. Java's generics implementation takes up a huge chunk of the spec and tooling. I don't even want to know about Scala's. It added so much more complexity to the language that I'm not surprised Java stagnated for as long as it did.
      • kaba0 5y ago
        > Java's generics implementation takes up a huge chunk of the spec and tooling. Does it? It is a pretty straightforward generic implementation, imo.
  • frutiger 5y ago
    > 1) it's guaranteed linear time in the length of the input What’s the multiplicative factor? Does it dominate for “typical” regexes?
    • pcwalton 5y ago
      For most regexes, backtracking and Thompson NFA have the same asymptotic complexity, which is why most languages adopted backtracking. The implementors of such languages knew what they were doing, especially when you consider that by adopting the Thompson NFA means you give up backreferences. The differences only arise with pathological regexes. I used to think that backtracking was superior to the Thompson NFA in practice on typical regexes, but modern implementations of the Thompson NFA have shown that I was wrong in that and the Thompson NFA can match backtracking's performance. Still, the situation isn't nearly as simple as Russ's article makes it out to be by only focusing on /a?a?a?aaa/, a regex which nobody would write. (This is not to deny that people do write pathological regexes from time to time. But what's the size of the userbase that writes pathological regexes compared to the size of the userbase that uses backreferences?)
      • tedunangst 5y ago
        People will gleefully write that regex if it causes a denial of your service. People would similarly blow up ftp servers with "ls starstarstarstar" globs.
      • burntsushi 5y ago
        FWIW, I would say that it's difficult for a Thompson NFA on its own to beat backtracking in non-pathological cases. So I actually think your prior is still mostly correct. Now a hybrid NFA/DFA (or a "lazy DFA") that does subset construction at search time using a Thompson NFA can definitely beat out a backtracker. A lazy DFA will generally match the speed of a fully compiled DFA, and is about an order of magnitude faster than a Thompson NFA simulation: [andrew@frink regex-automata]$ regex-cli find nfa thompson pikevm "@$medium" '(?m)^\w{30}$' build pike vm time: 6.584596ms create cache time: 278.231µs search time: 7.798138892s counts: [3] [andrew@frink regex-automata]$ regex-cli find hybrid dfa "@$medium" '(?m)^\w{30}$' parse time: 24.256µs translate time: 20.202µs compile nfa time: 5.966991ms nfa memory: 486196 build hybrid dfa time: 3.137µs hybrid dfa memory: 486196 create cache time: 21.793µs search time: 406.746917ms cache clear count: 0 counts: [3] [andrew@frink regex-automata]$ regex-cli find dfa dense "@$medium" '(?m)^\w{30}$' parse time: 22.824µs translate time: 15.513µs compile nfa time: 6.000195ms nfa memory: 486196 compile dense dfa time: 106.35009ms dense dfa memory: 4501024 dense alphabet length: 117 dense stride: 128 search time: 448.568888ms counts: [3] $ ls -lh $medium -rw-rw-r-- 1 andrew users 280M Jul 14 2021 /home/andrew/data/benchsuite/subtitles/2018/OpenSubtitles2018.raw.sample.medium.en (This is using an yet-unreleased tool as part of ongoing regex development.)
  • mattgreenrocks 5y ago
    Given that Go's original raison d'etre was Internet-facing services, the choice for guaranteed linear time execution makes sense as a default.
    • jeffbee 5y ago
      That ... isn't really true at all. Go's original raison was logs processing.
      • alecthomas 5y ago
        I'd be interested in reading more about that. Do you have a reference?
        • icholy 5y ago
          I think they're referring to Rob Pike's Sawzall language. However, I wouldn't call Go a descendant of it.
  • sanxiyn 5y ago
    As Knuth opined in an often quoted passage, it is criminally negligent to avoid 10% performance improvement to keep implementation simplicity.
    • rastignack 5y ago
      Way to never deliver. Absolute numbers like this are pointless.
  • bboreham 5y ago
    I have done some optimisations in Go regex recently; I have a talk coming up on Saturday: https://fosdem.org/2022/schedule/event/go_finite_automata/ https://fosdem.org/2022/schedule/event/go_finite_automata/ This repo collects all the changes so you can try them out: https://github.com/grafana/regexp/tree/speedup#readme https://github.com/grafana/regexp/tree/speedup#readme
    • benhoyt 5y ago
      That's excellent! Those all look like pretty nice small code changes that all add up. I especially like the very small "avoid copy" change (https://go-review.googlesource.com/c/go/+/355789 https://go-review.googlesource.com/c/go/+/355789) that adds up to a 30% speedup on many benchmarks. I hope they get included in Go 1.19. Good work!
  • truncate 5y ago
    It was 7 years ago, so I don't exactly remember what regex I used. I remember it was information retrieval course, and was supposed to write a crawler and index the webpage. So I think part of it was definitely to find all the links within webpage. I was working on extra credit so there might be some funky stuff.
• catlifeonmars 5y ago
  One of our ACLs at work relies heavily on Go regexp. The performance of evaluation is actually not too bad. What is quite terrible is the performance of *compiling* regexps.
  • benhoyt 5y ago
    I find this a bit surprising -- do you have numbers? Though even if compiling them is relatively slow it doesn't matter too much, because usually you're compiling once and evaluating many many times (e.g., in the case of a typical AWK script, you compile once and evaluate for each line in the input).
    • catlifeonmars 5y ago
      https://gist.github.com/jncornett/4a908250d701aec52a11d61a8953c4bb https://gist.github.com/jncornett/4a908250d701aec52a11d61a89... This is not super surprising, and like you said, in a typical AWK script you would only need to compile once. In short: $ go test -bench . ... BenchmarkRegexpCompile-8 513030 2307 ns/op BenchmarkRegexpEval1-8 2795020 425.5 ns/op BenchmarkRegexpEval2-8 3218155 370.2 ns/op ... Edit: formatting
• xpressvideoz 5y ago
  According to my totally unscientific benchmarks, if the performance of Rust's regular expression module were 1x, Go's was 8x and Ruby's was 32x, and Java's was 42x. Using Google's Java regex module improved the speed quite a bit but still was at ~18x. I was very impressed to see Rust doing so well. And it was sad to see Java so underperforming in such a typical workload. I know we're measuring libraries not languages, but I think regexes are so prevalent that not optimizing for it would hinder the language's real life performance.
  • pcwalton 5y ago
    By performance you mean elapsed time, right? So by 8x you mean 8x slower?
    • xpressvideoz 5y ago
      Yeah that's right. I compiled a pattern and matched it against a huge wall of text, measuring elapsed time.
  • tapirl 5y ago
    convenient to show your benchmarks?
    • xpressvideoz 5y ago
      Unfortunately, the test code belongs to the company I work for so I cannot take it out. It was done to determine what language we should use for an internal tool. I hope to conduct another benchmark one day, publicly this time.
    • dekelpilli 5y ago
      Not OP, but Benchmarks Game has a performance test based on regex: https://benchmarksgame-team.pages.debian.net/benchmarksgame/performance/regexredux.html https://benchmarksgame-team.pages.debian.net/benchmarksgame/... The top times for the mentioned languages are: Rust: 0.78s Ruby: 12.33s Java: 5.34s Go: 3.80s Python: 1.34s
• snarkerson 5y ago
  Version Numbering bothers me. Mathematically 1.2 is greater than 1.18. Yet in versions it is lesser. I find this annoying and counter intuitive.
  • sinsterizme 5y ago
    Yeah I always get tripped up. I feel like we should write it as 1.02, that way it can get up to 1.99 without this issue :)
  • titzer 5y ago
    Me too. For Virgil, because I am a fan of the roman poet, I am using roman numerals for the major versions and append a monotonically-increasing-regardless-of-major-version "00XXX" build number to that. This ensures they always sort lexicographically. ...until I get to version IX, i.e. 9, which would sort incorrectly. So I'll just skip 9, 19, 29...90...heh. :)
    • chrismorgan 5y ago
      If your algorithm is “choose the next number for which its Roman numeral sorts lexicographically higher than the current number”, then if you start at 1 you will only get 35 elements, since 38 (XXXVIII) is the lexicographically-highest Roman numeral. Using this precise rule, the starting point that gets you furthest is 250, which grants you 153 elements before stopping at 1038 (MXXXVIII). It’s possible to devise a longer sequence by skipping some numbers (e.g. after 1000 you’d jump to 1100), but I’m too lazy to calculate how you’d do all that. All this also assumes subtraction rules, which were a late addition to Roman numerals; without subtraction rules, four is written IIII instead of IV, and nine VIIII instead of IX, and so all of 1–49 would be lexicographically sorted. from docutils.utils.roman import toRoman def sequence(start): last = '' out = [] for i in range(start, 5000): this = toRoman(i) if this > last: last = this out.append(i) return out # Brute force way because I’m lazy; takes around ten seconds on my machine. start, s = max(((start, sequence(start)) for start in range(1, 5000)), key=lambda x: len(x[1])) print(f'{start} gives you {len(s)} items, {s}')
  • 5y ago
• darkgray 5y ago
  Me too. I have a project suffering pretty badly from the performance hit taken when a regexp doesn't start with a fixed string. Matching against `[ab]cd` is up to 9x slower than against `ab[cd]`.
• smasher164 5y ago
  There's a lot of room for improvement on the compiler and library end. RE2 and Hyperscan demonstrate the ceiling here. The NFA simulator is heavily optimized for readability, which means lots of recursion, and fewer special cases outside of small regexps. The compiler also doesn't perform certain optimizations like vectorization and emitting jump tables, which might be useful here. There isn't a metaprogramming facility to generate equivalent Go code like in re2go: https://re2c.org/manual/manual_go.html https://re2c.org/manual/manual_go.html. The best we can do is pre-declare the regexps globally as to initialize them once, but we still have to run the interpreter. Moreover, thus far, a DFA matcher is out of a picture, as discussed here: https://github.com/golang/go/issues/11646 https://github.com/golang/go/issues/11646.