是否可以使用 ccache 或类似方法来加速 clang-tidy？

Question

Since employing ccache on our CI server, we find that the bottleneck in terms of build time is now our static analysis pass, that uses clang-tidy , among other tools. Does anyone know of a way to accelerate clang-tidy in a similar way to how ccache does so with a regular compiler?

Answer 1

有clang-tidy-cache虽然我不知道它是如何与 ccache 一起工作的。

Answer 2

I found another important detail here:

https://gitlab.kitware.com/cmake/cmake/-/merge_requests/1791/diffs

which is used here:

https://reviews.bitcoinabc.org/D5150?id=15995

So in order to be able to cache the output of the compiler when integrating clang-tidy using the : set(CMAKE_CXX_CLANG_TIDY ...

method you need to use the COMPILER_LAUNCHER method to configure ccache

find_program(CCACHE ccache)
if(CCACHE)
    set(CMAKE_C_COMPILER_LAUNCHER ${CCACHE})
    set(CMAKE_CXX_COMPILER_LAUNCHER ${CCACHE})
endif(CCACHE)

and NOT the launcher rule method:

find_program(CCACHE ccache)
if(CCACHE)
    set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE ${CCACHE})
    set_property(GLOBAL PROPERTY RULE_LAUNCH_LINK ${CCACHE})
endif(CCACHE)

Answer 3

Finally, I have found a solution for this: it's switching the build system to bazel . bazel is a build system which is very generic and defines an action graph. Essentially every action has a set of inputs and outputs. Based on the inputs the outputs can be cached. Hence, bazel solves the problem at it's root.

The necessary rules for integrating clang-tidy in a cachable way can be found here: https://github.com/erenon/bazel_clang_tidy

In order to make use of caching you need to setup a remote cache . This can be done using a docker-compose script. The necessary docker container already exists. The command to get it running can be found here: https://github.com/buchgr/bazel-remote/

Finally, bazel also solves the problem of caching the result of the linking phase.

Not only that but bazel also allows building other languages like java. Hence, in complex projects it allows to replace all other build system with a single one.

Finally, bazel also allows parallelizing your build on a cluster.

Last but not least you can define several platforms and toolchains . All in all this allows to do cross-platform builds.