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countwords reviews and mentions
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How fast is really ASP.NET Core?
"dang, I didn't know that was 50x faster than the idiomatic way" or "hey, I didn't know that this implementation in the stdlib prioritized this over that and made this so slow, that's interesting" -- .e.g, there's some kinda neat language details to be found in something like Ben Hoyt's community word count benchmarks repo and 'simple' vs 'optimal' code: https://github.com/benhoyt/countwords
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Correct name for word matching problem
It benchmarks programs that count the total number of unique words in some input. It's not exactly equivalent to your problem, but it's similarish. All of the programs used some kind of hash map for lookups, but I contributed a program that used a trie. Its performance in my experience varies depending on the CPU interestingly enough. On my old CPU (i7-6900K) it was a little slower, but on my new cpu (i9-12900KS) it was faster.
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Performance comparison: counting words in Python, C/C++, Awk, Rust, and more
Are you looking at the "simple" or the "optimized" versions? For the optimized, yes, the Go one is very similar to the C. For the simple, idiomatic version, the Go version [1] is much simpler than the C one [2]: 40 very straight-forward LoC vs 93 rather more complex ones including pointer arithmetic, tricky manual memory management, and so on.
[1] https://github.com/benhoyt/countwords/blob/c66dd01d868aa83dc...
I don't think the performance is due to start up time at all. I actually cloned the repo, and ran the benchmark and found that Swift's execution time scales drastically with the size of the input.
The benchmark tests each executable by piping in the full King James Bible duplicated 10 times[1] (each copy is 4.13 MB[2]). When I ran it using just a single copy of the input text, the execution time dropped to 58-59 milliseconds, but when I ran the benchmark without modifications it jumped up to over 4 seconds. A hello world script for comparison runs in about 13 milliseconds. The Swift team actually boasts about its quick start up time on the official website [3].
[1] https://github.com/benhoyt/countwords/blob/master/test.sh#L5
[2] https://github.com/benhoyt/countwords/blob/master/kjvbible.t...
Re: the Rust performance implementation, I was able to get ~25% better performance by rewriting the for loops as iterators and by using a buffered writer, which seems crazy put it's true.[0] I chalked it up to some crazy ILP/SIMD tricks the compiler is doing.
I even submitted a PR, but Ben decided he was tired of maintaining and decided to archive the project (which fair enough!).
Why not read the source code? :-)
I wrote comments explaining things: https://github.com/benhoyt/countwords/blob/8553c8f600c40a462...
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The difference between Go and Rust
And yet Go was faster than Rust in a simple app that count words: https://benhoyt.com/writings/count-words/
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How to Rapidly Improve at Any Programming Language
> but the performance profiles & characteristics that we must know about in order to make a choice on which tool to use. And it shouldn't be that each user has to figure it out on their own, dig into PR's or whatever.
That's an interesting take – I like the idea of a catalog of standard tasks with implementations in several languages as well as their performance characteristics. I suppose Rosetta Code gets the ball rolling with this, but it's missing some performance metrics. It reminds me of [Ben Hoyt's piece](https://benhoyt.com/writings/count-words/) on counting unique words in the KJV Bible in different languages.
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Faster string keyed maps in Go
This article shows that map lookups can be optimized by using the (unintuitive) pattern:
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A note from our sponsor - WorkOS
workos.com | 28 Mar 2024
Stats
benhoyt/countwords is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of countwords is Rust.