codesearch VS roaring-rs

Whenever I work on huge codebase (think 1M+), I always reach for Russ Cox's codesearch https://github.com/google/codesearch. It requires indexing the codebase first, which takes 15 minutes or so, but after that searches are instant.

There is some older version that's open source, I haven't tried it and I don't know how much of today's code search is based on it.

https://github.com/google/codesearch

There's https://github.com/google/codesearch

If you want to find exact pieces of syntax then you should use a code search engine like GitHub's, Sourcegraph, or Google's codesearch. On the flip side, these won't be as good as Google for finding general ideas because they're focused more toward the precision of answers rather than giving you things that are related.

Check https://github.com/google/codesearch or https://swtch.com/~rsc/regexp/regexp4.html, this is actually possible.

There are issues and pull requests but I advise you to look at the milli folder in the Meilisearch repository, it’s where all the logic is done. We extensively use RoaringBitmaps, heed the LMDB wrapper and grenad when indexing.

On some benchmarks, we are faster but most of the time we aren't. We absolutely need to introduce benchmarks with the croaring-rs library and most of those performances gain could also be achieved with other methods to do multi-ops for example.

We tried to release the new version of roaring-rs, better compressed bitset in Rust, but found out that the core library simd module was blocking us. We now have to work on std::simd to release the blocking features.

Yeah, it can be attributed to using the roaring-rs library, but not just that, we have done so much to improve the search performances by reducing the number of set-operations we do.

Given the shoutouts to Burntsushi and Lemire this is almost certainly a bitmap trigram index based engine similar to https://github.com/google/zoekt

The index is likely based on Roaring bitmaps, presumably https://github.com/RoaringBitmap/roaring-rs in this case.

Nice architecture, exactly how I would have done it also.

I have worked on roaring-rs, a very fast library to do set operations like unions and intersections, and improved the four operations by using the standard ops traits.

I have implemented a better way of specifying ranges to be inserted or removed from a RoaringBitmap by using the RangeBounds trait. The roaring-rs library exposes fast data-structures to do set operations, like intersections and unions.