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InfluxDB
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NEW ugrep 5.1: an ultra fast, user-friendly, compatible grep. Ugrep combines the best features of other grep, adds new features, and searches fast. Includes a TUI and adds Google-like search, fuzzy search, hexdumps, searches nested archives (zip, 7z, tar, pax, cpio), compressed files (gz, Z, bz2, lzma, xz, lz4, zstd, brotli), pdfs, docs, and more
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encoding
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regex-benchmark
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SaaSHub
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rebar reviews and mentions
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Re2c
They are extremely fast too: https://github.com/BurntSushi/rebar?tab=readme-ov-file#summa...
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C# Regex engine is now 3rd fastest in the world
I love the flourish of "in the world." I had never thought about it that way. Which makes me think if there are any regex engines that aren't in rebar that could conceivably by competitive with the top engines in rebar. I do maintained a WANTED list of engines[1], but none of them jump out to me except for maybe Nim's engine.
Of course, there's also the question of whether the benchmarks are representative enough to make such extrapolations. I don't have a good answer for that one. All models are wrong, but, some are useful.
[1]: https://github.com/BurntSushi/rebar/blob/96c6779b7e1cdd850b8...
It seems the comment reference in the link got trimmed away...or it was OSI level 8 issue :D
Either way, the data is in this comment: https://github.com/BurntSushi/rebar/pull/10#issuecomment-187...
.NET now takes 3rd place, behind Mr. Gallant's Regex crate and Intel's Hyperscan.
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Ugrep – a more powerful, ultra fast, user-friendly, compatible grep
Did you know that not all of those use the same definition of what a "word" character is? Regex engines differ on the inclusion of things like \p{Join_Control}, \p{Mark} and \p{Connector_Puncuation}. Although in the case of \p{Connector_Punctuation}, regex engines will usually at least include underscore. See: https://github.com/BurntSushi/rebar/blob/f9a4f5c9efda069e798...
And then there's \p{Letter}. It can be spelled in a lot of ways: \pL, \p{L}, \p{Letter}, \p{gc=Letter}, \p{gc:Letter}, \p{LeTtEr}. All equivalent. Very few regex engines support all of them. Several support \p{L} but not \pL. See: https://github.com/BurntSushi/rebar/blob/f9a4f5c9efda069e798...
I'm the author of ripgrep and its regex engine.
Your claim is true to a first approximation. But greps are line oriented, and that means there are optimizations that can be done that are hard to do in a general regex library.
If you read my commentary in the ripgrep discussion above, you'll note that it isn't just about the benchmarks themselves being accurate, but the model they represent. Nevertheless, I linked the hypergrep benchmarks not because of Hyperscan, but because they were done by someone who isn't the author of either ripgrep or ugrep.
As for regex benchmarks, you'll want to check out rebar: https://github.com/BurntSushi/rebar
You can see my full thoughts around benchmark design and philosophy if you read the rebar documentation. Be warned though, you'll need some time.
There is a fork of ripgrep with Hyperscan support: https://sr.ht/~pierrenn/ripgrep/
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Translations of Russ Cox's Thompson NFA C Program to Rust
Before getting to your actual question, it might help to look at a regex benchmark that compares engines (perhaps JITs are not the fastest in all cases!): https://github.com/BurntSushi/rebar
In particular, the `regex-lite` engine is strictly just the PikeVM without any frills. No prefilters or literal optimizations. No other engines. Just the PikeVM.
As to your question, the PikeVM is, essentially, an NFA simulation. The PikeVM just refers to the layering of capture state on top of the NFA simulation. But you can peel back the capture state and you're still left with a slow NFA simulation. I mention this because you seem to compare the PikeVM with "big graph structures with NFAs/DFAs." But the PikeVM is using a big NFA graph structure.
At a very high level, the time complexity of a Thompson NFA simulation and a DFA hints strongly at the answer to your question: searching with a Thompson NFA has worst case O(m*n) time while a DFA has worst case O(n) time, where m is proportional to the size of the regex and n is proportional to the size of the haystack. That is, for each character of the haystack, the Thompson NFA is potentially doing up to `m` amount of work. And indeed, in practice, it really does need to do some work for each character.
A Thompson NFA simulation needs to keep track of every state it is simultaneously in at any given point. And in order to compute the transition function, you need to compute it for every state you're in. The epsilon transitions that are added as part of the Thompson NFA construction (and are, crucially, what make building a Thompson NFA so fast) exacerbate this. So what happens is that you wind up chasing epsilon transitions over and over for each character.
A DFA pre-computes these epsilon closures during powerset construction. Of course, that takes worst case O(2^m) time, which is why real DFAs aren't really used in general purpose engines. Instead, lazy DFAs are used.
As for things like V8, they are backtrackers. They don't need to keep track of every state they're simultaneously in because they don't mind taking a very long time to complete some searches. But in practice, this can make them much faster for some inputs.
Feel free to ask more questions. I'll stop here.
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Compile time regular expression in C++
I'd love for someone to add this to rebar[1] so that we can get a good sense of how well it does against other general purpose regex engines. It will be a little tricky to add (since the build step will require emitting a C++ program and compiling it), but it should be possible.
- Stringzilla: Fastest string sort, search, split, and shuffle using SIMD
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Rust vs. Go in 2023
https://github.com/BurntSushi/rebar#summary-of-search-time-b...
Further, Go refusing to have macros means that many libraries use reflection instead, which often makes those parts of the Go program perform no better than Python and in some cases worse. Rust can just generate all of that at compile time with macros, and optimize them with LLVM like any other code. Some Go libraries go to enormous lengths to reduce reflection overhead, but that's hard to justify for most things, and hard to maintain even once done. The legendary https://github.com/segmentio/encoding seems to be abandoned now and progress on Go JSON in general seems to have died with https://github.com/go-json-experiment/json .
Many people claiming their projects are IO-bound are just assuming that's the case because most of the time is spent in their input reader. If they actually measured they'd see it's not even saturating a 100Mbps link, let alone 1-100Gbps, so by definition it is not IO-bound. Even if they didn't need more throughput than that, they still could have put those cycles to better use or at worst saved energy. Isn't that what people like to say about Go vs Python, that Go saves energy? Sure, but it still burns a lot more energy than it would if it had macros.
Rust can use state-of-the-art memory allocators like mimalloc, while Go is still stuck on an old fork of tcmalloc, and not just tcmalloc in its original C, but transpiled to Go so it optimizes much less than LLVM would optimize it. (Many people benchmarking them forget to even try substitute allocators in Rust, so they're actually underestimating just how much faster Rust is)
Finally, even Go Generics have failed to improve performance, and in many cases can make it unimaginably worse through -- I kid you not -- global lock contention hidden behind innocent type assertion syntax: https://planetscale.com/blog/generics-can-make-your-go-code-...
It's not even close. There are many reasons Go is a lot slower than Rust and many of them are likely to remain forever. Most of them have not seen meaningful progress in a decade or more. The GC has improved, which is great, but that's not even a factor on the Rust side.
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A note from our sponsor - InfluxDB
www.influxdata.com | 28 Mar 2024
Stats
BurntSushi/rebar is an open source project licensed under The Unlicense which is not an OSI approved license.
The primary programming language of rebar is Python.