26 karma · joined April 3, 2013
I have a similar use case in mind, so I'm planning on trying to get this working by writing a simple script that proxies language server messages over SSH/TCP. Ideally it should work with any language server.
> Regarding indexing time, all of these tools seem to parse source code using either libclang (C API) or "native" C++ API (RecursiveASTVisitor etc.), so IMHO any difference in indexing time between rtags and cquery should come from such factors as number of parsing threads, database for storing tags, caching etc.
Yea, it is amazing how big of a difference the architecture around indexing makes - any sort of global lock/shared state really hurts performance. I spent a significant amount of time finding the right architecture to make each index job as independent as possible. Most of the design decisions in cquery are oriented towards either latency or throughput at the cost of things like memory and total system load (I've since reduced memory usage, but at one point cquery used 30gb after indexing Chrome - now it is around 5gb).
> Anyway I'm really excited about cquery and even consider moving to VSCode just because of it (being a long-term VIM user). Reliable "Find references" feature is (IMHO) a must-have functionality for large codebases and currently (thanks to cquery and rtags) is supported much better in modern C++ than in other system languages (such as Go and Rust).
I'd like to see cquery support in vim as well using a vim LSP implementation :). But yes, I agree with you - cquery makes me want to continue using C++ over Rust simply because the tooling works a lot better.
When a cc file is indexed cquery will index the associated header files. There is some logic to deduplicate multiple header file parsing so it only happens once, but that is fundamentally how it works. cquery then knows which header files are associated to which cc files.
> I know that some tools, like YCM, attempt to intelligently map a header file to it's associated .cpp/.cc/.c file to guess what the compiler commands are, but this doesn't always work.
cquery does this as well, because you can, for example, create a new file that is not in compile_commands.json. cquery has sophisticated logic here, as it will also try to infer if the file is test or platform specific (use general postfix matching) as those often have a very different set of arguments.
> What is the state of generating compiler_commands.json for Chromium? I remember running into this issue a few years back.
Chrome compiles using ninja, which natively supports compile_commands.json, so generating the file works well and is easy to do. I have not run into any issue here.
cquery is designed to support very large projects, so it makes very specific design decisions w.r.t. the data model, indexing pipeline, and multithreading model. I hope clangd can match the performance - but so far every project I've seen simply does not run nearly fast enough on a code-base the size of Chrome/ChromeOS.
This can be done similar to what rtags does (hooking into gcc/clang invocations). Alternatively if you use ninja this relatively simple by generating a compile_commands.json file.
ninja -C out/Release -t compdb cxx cc > compile_commands.json
My eventual plan is to automate compile_commands.json generation if using ninja, so cquery is install and go.- cquery interacts with an editor via the language server protocol, letting it work with any editor with relatively minimal work - cquery handles larger repositories better (ie, indexing all of Chrome takes 20-30 minutes on a high-end workstation) - cquery responds to semantic requests within 10ms or so
There are some other differences but those are related to the features implemented, ie, cquery supports code lens.
I'm not sure how code completion is in rtags, but I've spent a fair amount of time making it work as fast as possible in cquery. There is quite a bit of caching built on-top of the clang API which often makes it feel instantaneous.
Let me know if you have any questions.