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Optimization on Memory Usage During Rust Cargo Code Compiling

This article provides a comprehensive guide on managing out-of-memory issues when compiling large projects with Rust's Cargo.

By digoal


When compiling large projects using Cargo of Rust, you may encounter out-of-memory conditions. This problem can be optimized from multiple perspectives:

1.  Increase physical memory: The most straightforward solution is to increase RAM on your machine.

2.  Increase virtual memory: If you cannot increase the physical memory, you can increase the swap space. For Linux, you can use fallocate and mkswap to increase the swap partition; for Windows systems, you can adjust the virtual memory settings.

3.  Batch compilation: The Rust compiler supports incremental compilation, which can reduce memory usage. Make sure your version of Cargo is up to date, as the Rust team continues to improve the compiler's performance.

4.  Optimize the code structure:

  • Reduce the size of a single crate and split it into multiple smaller crates.
  • Reduce the number of dependencies, especially large ones.
  • Reduce the use of generics, because generics cause the compiler to generate a lot of code.

5.  Use cargo check: If you just want to check the correctness of the code without generating an executable file, you can use cargo check, which consumes much less memory than a full compilation.

6.  Adjust compilation options:

  • If you do not need debugging information, you can disable it by adding [profile.release] debug = false to the Cargo.toml, which can reduce memory usage.
  • Use the -j option to limit the number of crates for parallel compilation, for example: cargo build -j 1.

7.  Adjust the operating system's OOM(Out of Memory) behavior: On the Linux, you can adjust the /proc/sys/vm/overcommit_memory and /proc/sys/vm/overcommit_ratio to control the memory allocation policy.

8.  Use a lighter operating system: If you compile in a virtual machine or container, using a lighter operating system or a minimal Linux distribution may reduce the memory usage of the system itself.

9.  Cross-compilation: If your host really has limited resources, consider cross-compiling on a more powerful machine.

10.  Optimize build scripts: If your project contains build scripts, make sure that they are efficient and free of memory leaks.

11.  Use a lld linker: lld is an efficient linker that uses less memory and links faster than the default linker. It can be used by setting the environment variable RUSTFLAGS="-C link-arg=-fuse-ld=lld".

12.  Clean up project: Clean up old compiled files with cargo clean and then recompile.

Please try the preceding suggestions according to your specific situation. In some cases, even with optimizations, compilation may still fail due to resource constraints. In this case, using a more powerful compilation machine may be the simplest solution.

Optimizations on Memory Usage During Rust Cargo PGRX Installation

PGRX is not a widely known Cargo package name, and this seems to be referring to one of the packages on crates.io, or just a typo. But in any case, when you encounter the problem of insufficient memory when installing any Rust package, you can try the following optimizations:

1.  Reduce the number of parallel compilation tasks: You can use environment variables to reduce the number of parallel compilation tasks for Cargo.

export CARGO_BUILD_JOBS=1# Restrict to a single compilation task

Or specify directly on the command line:

cargo install --jobs 1 <crate_name>

2.  Optimize compiler configuration: In the Cargo.toml, enable compiler optimization by using command line parameters, such as reducing code generation units (Codegen Units).

codegen-units = 1

If you are installing the package, you can also try adding the --profile option to specify the compiler configuration.

3.  Use an efficient linker: Consider using a linker that is more efficient than the system default linker, such as lld.

RUSTFLAGS="-Clinker=lld" cargo install <crate_name>

Make sure you have the lld linker installed.

4.  Batch installation: If you are installing multiple packages, try to install them one by one instead of using wildcards or lists to install them all at once.

5.  Increase virtual memory /swap space: If the physical memory is insufficient, try to increase the virtual memory. On Linux, you can manage swap space using the swapon and swapoff commands.

6.  Clean up the build cache: Clean up the cache in the target and ~/.cargo directories, which helps to free up some occupied disk space and sometimes improves memory usage.

cargo clean

7.  Check the build script of a specific package: If the problem is caused by a specific package, check whether the package has specific build instructions or dependencies, which lead to increased memory consumption.

8.  Monitor memory usage: During the compilation process, use system monitoring tools (such as htop or top) to track memory usage to determine spikes in memory usage and which steps consume the most memory.

If the preceding methods still do not solve the problem, you may want to consider upgrading your hardware, especially adding more physical memory.

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