How the Rust Compiler Avoids Rebuilding the Universe (Most of the Time)
If you’ve ever worked on a big Rust project, you’ve felt it: that agonizing pause after you hit cargo build — watching your fans spin up as if you’ve just launched a space probe instead of a CLI tool.
And then — a small change. One line. A single println!. And Rust rebuilds everything. At least, it used to.
Today, the Rust compiler (a.k.a. rustc) is far smarter — it avoids recompiling the universe every time you sneeze. The magic behind that efficiency is incremental compilation, a system built on a graph of dependencies so detailed it could make a relational database jealous. Let’s explore how Rust does it, why it sometimes fails, and what’s really happening when you type cargo build.
The Problem: Compiling Rust Is Expensive
Rust’s compilation model is built on strong guarantees: safety, optimization, and reproducibility. But those guarantees come at a cost.
Here’s what a single build roughly does:
1. Parse all source files. 2. Expand macros and desugar syntax. 3. Build the dependency graph (modules, crates). 4. Perform type checking, lifetime inference. 5. Generate MIR, then LLVM IR. 6. Optimize and codegen machine code. 7. Link everything together.
Now imagine doing that every time you change one line. That’s millions of compiler operations you don’t need to repeat.
So the core question became:
“Can Rust remember what it already did?”
That’s the idea behind incremental compilation.
The Architecture: Rust’s Dependency Graph Let’s visualize what happens during an incremental build:
┌───────────────────────────────────────┐
│ Rust Source Code │
│ (modules, crates, dependencies) │
└───────────────────────────────────────┘
│
▼
┌───────────────────────────┐
│ Dependency Graph Builder │
│ (Tracks nodes & hashes) │
└───────────┬───────────────┘
│
▼
┌───────────────────────────┐
│ On-Disk Cache Store │
│ (Compiled crate data) │
└───────────┬───────────────┘
│
▼
┌───────────────────────────┐
│ Incremental Rebuilder │
│ (Reuses unchanged nodes) │
└───────────────────────────┘
Each crate (and item inside it) becomes a node in a massive dependency graph. When you make a change, Rust doesn’t recompile everything — it just invalidates the nodes affected by the change.
That’s what saves your CPU from reliving the apocalypse every time you add a semicolon.
Example: A Minimal Case Study
Let’s look at a tiny program:
// main.rs mod utils;
fn main() {
println!("{}", utils::greet("Rust"));
} // utils.rs pub fn greet(name: &str) -> String {
format!("Hello, {name}!")
}
The first time you build, Rust compiles both main.rs and utils.rs, and stores the results in your incremental cache (usually in target/debug/incremental). Now, let’s say you change just this:
fn main() {
println!("{}", utils::greet("World"));
}
That’s a change inside main.rs only — utils.rs hasn’t changed. So Rust checks its dependency graph:
main.rs → depends on → utils.rs
It detects that utils.rs’s fingerprint (a hash of its contents + compiler metadata) hasn’t changed. So it reuses the compiled version from cache. ✅ Result: Rust rebuilds only main.rs ❌ Not the entire project.
Under the Hood: Hashing Everything
Rust’s incremental system relies on content hashing — every function, type, and module is fingerprinted based on its contents and dependencies.
So when you compile, Rust stores something like this internally:
utils::greet ├── hash: a3b42... ├── depends_on: core::fmt, alloc::string └── output: object code blob
Next build, rustc compares the stored hashes with the current source. If nothing changes, it reuses the object file from the cache.
But here’s the catch — if you change something indirectly (like a generic type or a macro used by greet), Rust may detect a cascading invalidation. That’s when it feels like it rebuilt the universe again.
Code Flow Diagram: Incremental Compilation Path
┌────────────────────────────┐
│ Source Code Change │
└────────────┬───────────────┘
▼
┌────────────────────────────┐
│ Hash Old vs New Source │
│ (Compare fingerprints) │
└────────────┬───────────────┘
▼
┌────────────────────────────┐
│ Identify Dirty Nodes │
│ (Only recompile affected) │
└────────────┬───────────────┘
▼
┌────────────────────────────┐
│ Reuse Cached Artifacts │
│ (From target/incremental) │
└────────────┬───────────────┘
▼
┌────────────────────────────┐
│ Compile + Link Final Bin │
└────────────────────────────┘
It’s a bit like Makefiles on steroids — except Rust tracks every type, every macro, and every borrow-check result. The Real Reason It Sometimes Fails Here’s where emotion meets engineering. You’ll occasionally see Rust rebuild everything even for a trivial change. Why?
Because incremental compilation is hard in a language that guarantees correctness at compile time.
A few reasons:
- Cross-Crate Metadata: Changes in public APIs can invalidate everything downstream.
- Macro Expansion: Macros can alter entire module structures, forcing recompilation.
- Optimization Dependencies: LLVM optimizations sometimes depend on entire-call graphs.
- Compiler Version Drift: Incremental caches are invalidated between compiler updates.
So Rust’s incremental system is conservative. If it’s unsure — it rebuilds. That’s not a bug; that’s caution by design. Real Example: Incremental Hash Diff
Let’s take a slightly complex case:
pub fn multiply(a: i32, b: i32) -> i32 {
a * b
}
pub fn double(x: i32) -> i32 {
multiply(x, 2)
}
Now change multiply:
pub fn multiply(a: i32, b: i32) -> i32 {
a.saturating_mul(b)
}
Even though double() wasn’t changed, its dependency (multiply) changed. MIR fingerprints will differ, causing Rust to recompile both functions. That’s the kind of internal precision that keeps the compiler trustworthy. The Architecture of the Incremental Compiler
Inside rustc, incremental compilation is built on two main systems:
| Component | Responsibility | | ---------------- | ---------------------------------------------------------------------------------------------------------------- | | Query System | The heart of `rustc`, where every compiler computation (e.g., type-checking a function) is expressed as a query. | | DepGraph | The dependency graph that records how each query depends on others. |
A simplified pseudo-architecture:
query: type_of(foo) ──┐
├──> DepGraph Node: "foo"
query: mir_of(foo) ───┘
When a change is detected in foo, Rust invalidates these queries and only recomputes the ones affected downstream.
That’s how it avoids doing the entire type-check, borrow-check, and codegen process again.
Cargo’s Role: Smart Build Orchestration
cargo sits on top of all this, orchestrating crate-level builds. It tracks:
- dependencies between crates (Cargo.lock)
- fingerprints for features and flags
- hashes for compiler options (RUSTFLAGS)
So if you change a dependency in your Cargo.toml, Cargo recalculates what’s dirty. But if you just tweak local logic, Cargo tells rustc: “Relax. Just recompile that one file.”
Real Impact: Measurable Wins
Teams at large Rust-based companies like Figma, Cloudflare, and Embark have reported significant time savings after enabling incremental builds.
| Project | Cold Build | Incremental Build | | ------------------- | ---------- | ----------------- | | Figma Infra Tooling | 12m 45s | 1m 40s | | Cloudflare Proxy | 9m 10s | 55s | | Embark Game Engine | 15m+ | 2m 30s |
That’s not theory — that’s engineers shipping faster without compromising Rust’s safety.
Future: The Next Steps (Query Persistence & Cranelift) Rust’s incremental story isn’t finished. Ongoing work is focusing on:
- Query Persistence: Persisting more compiler state between builds.
- Cranelift Backend: Faster, debug-friendly codegen.
- Parallel Query Execution: Truly multi-core incremental builds.
In other words, Rust’s compiler is slowly learning to trust its own memory.
Final Thoughts
Rust’s incremental compiler is like a friend who remembers everything you said but only reacts when you contradict yourself.
It doesn’t always get it right — sometimes it panics and rebuilds the world. But that’s because it’s playing defense in a language that promises zero undefined behavior.
Every skipped rebuild is a tiny miracle — a balance between paranoia and performance.
So the next time your build finishes faster than expected, remember: Rust didn’t just compile your code. It remembered your past.
Read the full article here: https://medium.com/@theopinionatedev/how-the-rust-compiler-avoids-rebuilding-the-universe-most-of-the-time-c3f6fa1a02b5