rust-jemalloc-pprof

A rust library to collect and convert Heap profiling data from the jemalloc allocator and convert it to the pprof format.

To understand how to use this together with Polar Signals Cloud to continuously collect profiling data, refer to the Use with Polar Signals Cloud section.

This code was originally developed as part of Materialize, and then in a collaboration extracted into this standalone library.

Usage

Internally this library uses tikv-jemalloc-ctl to interact with jemalloc, so to use it, you must use the jemalloc allocator via the tikv-jemallocator library.

When adding tikv-jemallocator as a dependency, make sure to enable the profiling feature.

[dependencies]
[target.'cfg(not(target_env = "msvc"))'.dependencies]
tikv-jemallocator = { version = "0.5.4", features = ["profiling", "unprefixed_malloc_on_supported_platforms"] }

Note: We also recommend enabling the unprefixed_malloc_on_supported_platforms feature, not strictly necessary, but will influence the rest of the usage.

Then configure the global allocator and configure it with profiling enabled.

#[cfg(not(target_env = "msvc"))]
#[global_allocator]
static ALLOC: tikv_jemallocator::Jemalloc = tikv_jemallocator::Jemalloc;

#[allow(non_upper_case_globals)]
#[export_name = "malloc_conf"]
pub static malloc_conf: &[u8] = b"prof:true,prof_active:true,lg_prof_sample:19\0";

If you do not use the unprefixed_malloc_on_supported_platforms feature, you have to name it _rjem_malloc_conf it instead of malloc_conf.

2^19 bytes (512KiB) is the default configuration for the sampling period, but we recommend being explicit. To understand more about jemalloc sampling check out the detailed docs on it.

We recommend serving the profiling data on an HTTP server such as axum, that could look like this, and we'll intentionally include a 4mb allocation to trigger sampling.

#[tokio::main]
async fn main() {
    let mut v = vec![];
    for i in 0..1000000 {
        v.push(i);
    }

    let app = axum::Router::new()
        .route("/debug/pprof/heap", axum::routing::get(handle_get_heap));

    // run our app with hyper, listening globally on port 3000
    let listener = tokio::net::TcpListener::bind("0.0.0.0:3000").await.unwrap();
    axum::serve(listener, app).await.unwrap();
}

use axum::http::StatusCode;
use axum::response::IntoResponse;

pub async fn handle_get_heap() -> Result<impl IntoResponse, (StatusCode, String)> {
    let mut prof_ctl = jemalloc_pprof::PROF_CTL.as_ref().unwrap().lock().await;
    require_profiling_activated(&prof_ctl)?;
    let pprof = prof_ctl
        .dump_pprof()
        .map_err(|err| (StatusCode::INTERNAL_SERVER_ERROR, err.to_string()))?;
    Ok(pprof)
}

/// Checks whether jemalloc profiling is activated an returns an error response if not.
fn require_profiling_activated(prof_ctl: &jemalloc_pprof::JemallocProfCtl) -> Result<(), (StatusCode, String)> {
    if prof_ctl.activated() {
        Ok(())
    } else {
        Err((axum::http::StatusCode::FORBIDDEN, "heap profiling not activated".into()))
    }
}

Then running the application, we can capture a profile and view it the pprof toolchain.

curl localhost:3000/debug/pprof/heap > heap.pb.gz
pprof -http=:8080 heap.pb.gz

Note: The profiling data is not symbolized, so either addr2line or llvm-addr2line needs to be available in the path and pprof needs to be able to discover the respective debuginfos.

Writeable temporary directory

The way this library works is that it creates a new temporary file (in the platform-specific default temp dir), and instructs jemalloc to dump a profile into that file. Therefore the platform respective temporary directory must be writeable by the process. After reading and converting it to pprof, the file is cleaned up via the destructor. A single profile tends to be only a few kilobytes large, so it doesn't require a significant space, but it's non-zero and needs to be writeable.

Use with Polar Signals Cloud

Polar Signals Cloud allows continuously collecting heap profiling data, so you always have the right profiling data available, and don't need to search for the right data, you already have it!

Polar Signals Cloud supports anything in the pprof format, so a process exposing the above explained pprof endpoint, can then be scraped as elaborated in the scraping docs.