This wouldn't build for me, so I had to apply the patch suggested by a sibling comment.<p>Once I got it building, my first benchmark attempt shows it as being slower:<p><pre><code> $ curl -LO 'https://burntsushi.net/stuff/subtitles2016-sample.en.gz'
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 265M 100 265M 0 0 48.6M 0 0:00:05 0:00:05 --:--:-- 49.9M
$ gzip -d subtitles2016-sample.en.gz
$ hyperfine --ignore-failure "rg -c 'ZQZQZQZQ' subtitles2016-sample.en" "krep -c 'ZQZQZQZQ' subtitles2016-sample.en"
Benchmark 1: rg -c 'ZQZQZQZQ' subtitles2016-sample.en
Time (mean ± σ): 80.7 ms ± 1.6 ms [User: 57.7 ms, System: 22.7 ms]
Range (min … max): 75.3 ms … 83.3 ms 35 runs
Warning: Ignoring non-zero exit code.
Benchmark 2: krep -c 'ZQZQZQZQ' subtitles2016-sample.en
Time (mean ± σ): 122.8 ms ± 1.4 ms [User: 372.6 ms, System: 24.4 ms]
Range (min … max): 120.2 ms … 125.5 ms 24 runs
Summary
rg -c 'ZQZQZQZQ' subtitles2016-sample.en ran
1.52 ± 0.03 times faster than krep -c 'ZQZQZQZQ' subtitles2016-sample.en
</code></pre>
That's a benchmark with no matches, which is the best case essentially for throughput. Now I want to try a benchmark with a high match frequency:<p><pre><code> $ hyperfine "rg -c 'the' subtitles2016-sample.en" "krep -c 'the' subtitles2016-sample.en"
Benchmark 1: rg -c 'the' subtitles2016-sample.en
Time (mean ± σ): 411.8 ms ± 3.6 ms [User: 389.7 ms, System: 21.1 ms]
Range (min … max): 404.8 ms … 415.7 ms 10 runs
Benchmark 2: krep -c 'the' subtitles2016-sample.en
Time (mean ± σ): 121.2 ms ± 1.9 ms [User: 364.6 ms, System: 24.9 ms]
Range (min … max): 113.2 ms … 123.0 ms 24 runs
Summary
krep -c 'the' subtitles2016-sample.en ran
3.40 ± 0.06 times faster than rg -c 'the' subtitles2016-sample.en
</code></pre>
Which is very nice. So I decided to poke at it:<p><pre><code> $ krep -c the subtitles2016-sample.en
Found 29794426 matches
$ rg -c the subtitles2016-sample.en
6123710
$ grep -c the subtitles2016-sample.en
6123710
</code></pre>
The counts are way off here. At first I thought maybe it was counting every occurrence of `the` instead of every matching line, but when I ask ripgrep to do that, it gets a different answer:<p><pre><code> $ rg -oc the subtitles2016-sample.en
7739791
$ rg -o the subtitles2016-sample.en | wc -l
7739791
$ grep -o the subtitles2016-sample.en | wc -l
7739791
</code></pre>
So not sure what's going on here, but it looks like `krep` might not be giving accurate results.<p>Pushing it a bit more, it seems like it just kind of falls over?<p><pre><code> $ time rg -c 'You read Sherlock Holmes to deduce that\?' subtitles2016-sample.en
10
real 0.076
user 0.049
sys 0.026
maxmem 923 MB
faults 0
$ time krep -c 'You read Sherlock Holmes to deduce that?' subtitles2016-sample.en
Found 0 matches
real 0.935
user 3.597
sys 0.029
maxmem 918 MB
faults 0
</code></pre>
I ran the above benchmarks in `/dev/shm` on Linux with an i9-12900K.<p>In terms of the approach here, ripgrep is already using a pretty sophisticated substring search algorithm: <a href="https://github.com/BurntSushi/memchr?tab=readme-ov-file#algorithms-used" rel="nofollow">https://github.com/BurntSushi/memchr?tab=readme-ov-file#algo...</a><p>And it uses memory maps (sometimes, when it thinks it will be fast, but it will do so in the single file case on Linux).<p>ripgrep also uses parallelism, but at inter-file level. It sounds like `krep` also uses parallelism, but will use multiple threads when searching a single file. I've considered doing the same in ripgrep, but haven't done enough experiments (or seen enough from someone else) to be convinced that it's the right way to go in general. It might edge out single threaded search in some cases for sure though.<p>EDIT: Looking at the timings in <a href="https://dev.to/daviducolo/introducing-krep-building-a-high-performance-string-search-utility-2pdo" rel="nofollow">https://dev.to/daviducolo/introducing-krep-building-a-high-p...</a>, I see, for example, ripgrep taking >40 seconds to search for the literal pattern `error` in a 5GB file. Even if you're reading from disk (which the OP is using an SSD), that does not seem right at all. Even for an exceptionally common word like `the` in this haystack, ripgrep can chew through a 13GB file in 5 seconds on my machine:<p><pre><code> $ time rg -c the full.txt
83499915
real 5.404
user 5.092
sys 0.302
maxmem 12511 MB
faults 0
</code></pre>
Even if I force reading from disk, we get nowhere near 40 seconds:<p><pre><code> $ sudo sh -c 'echo 3 > /proc/sys/vm/drop_caches'
$ time rg -c the full.txt
83499915
real 10.577
user 5.191
sys 2.105
maxmem 12511 MB
faults 42
</code></pre>
I'm not saying the benchmark results are definitely wrong, but something <i>looks</i> off here that I can't easily explain. OP, can you please share a way to fully reproduce your benchmark? (Like I did above for `subtitles2016-sample.en`.)