Comparing Performance: Loops vs. Iterators
Benchmark results comparing explicit for loops vs. iterator implementation searching for “the” in The Adventures of Sherlock Holmes:
test bench_search_for ... bench: 19,620,300 ns/iter (+/- 915,700)
test bench_search_iter ... bench: 19,234,900 ns/iter (+/- 657,200)
Key findings:
- Iterator version performs slightly better
- Performance difference is negligible
- Both compile to nearly identical assembly
Zero-Cost Abstractions
Iterators exemplify Rust’s zero-cost abstractions—high-level constructs that impose no runtime overhead. The compiler applies optimizations including:
- Loop unrolling
- Bounds check elimination
- Inline expansion
- Dead code elimination
These optimizations often produce assembly equivalent to hand-optimized code.
Summary
Closures and iterators provide functional programming patterns with systems-level performance. They enable expressive, maintainable code without sacrificing runtime efficiency—a core principle of Rust’s design philosophy.
Use iterators and closures confidently in performance-critical code. The abstractions compile away, leaving only the essential operations.
Now that we’ve improved the expressiveness of our I/O project, let’s look at
some more features of cargo that will help us share the project with the
world.