Rust Concurrency

Concurrency vs Async

Key Insight: Threads for parallelism, async for concurrency.

Send/Sync Quick Reference

Send - Can Transfer Ownership Between Threads

Basic types → automatically Send
Contains references → automatically Send
Raw pointers → NOT Send
Rc → NOT Send (non-atomic ref counting)

Rule: If all fields are Send, the type is Send.

Sync - Can Share References Between Threads

&T where T: Sync → automatically Sync
RefCell → NOT Sync (runtime checking not thread-safe)
MutexGuard → NOT Sync (intentionally)

Rule: &T is Send if T is Sync.

Solution Patterns

Pattern 1: Shared Mutable State

use std::sync::{Arc, Mutex};

let counter = Arc::new(Mutex::new(0));
let mut handles = vec![];

for _ in 0..10 {
    let counter = Arc::clone(&counter);
    let handle = std::thread::spawn(move || {
        let mut num = counter.lock().unwrap();
        *num += 1;
    });
    handles.push(handle);
}

for handle in handles {
    handle.join().unwrap();
}

When to use: Multiple threads need to mutate shared data.

Trade-offs: Lock contention can limit scalability.

Pattern 2: Message Passing

use std::sync::mpsc;

let (tx, rx) = mpsc::channel();

thread::spawn(move || {
    tx.send("hello").unwrap();
});

println!("{}", rx.recv().unwrap());

When to use: Threads communicate without shared state.

Trade-offs: Copy/move overhead for messages.

Pattern 3: Async Runtime (Tokio)

use tokio;

#[tokio::main]
async fn main() {
    let handle = tokio::spawn(async {
        // Async task
        fetch_data().await
    });

    let result = handle.await.unwrap();
}

When to use: I/O-bound operations (network, filesystem).

Trade-offs: Requires async runtime, function coloring.

Workflow

Step 1: Choose Concurrency Model

CPU-intensive task?
  → Use threads (rayon for data parallelism)

I/O-intensive task?
  → Use async/await (tokio, async-std)

Both?
  → Use async with spawn_blocking for CPU work

Step 2: Determine Data Sharing Strategy

No shared state?
  → Message passing (mpsc channels)

Read-heavy shared state?
  → Arc<RwLock<T>>

Write-heavy shared state?
  → Arc<Mutex<T>> or lock-free alternatives

Simple counters/flags?
  → Atomic types (AtomicUsize, AtomicBool)

Step 3: Verify Thread Safety

Check Send bounds
  → Can transfer ownership?

Check Sync bounds
  → Can share references?

Test for data races
  → Use miri, loom, or thread sanitizers

Common Errors & Solutions

Deadlock Prevention

Rule 1: Consistent Lock Ordering

// Always lock A before B
let _lock_a = resource_a.lock();
let _lock_b = resource_b.lock();
// Never lock B before A elsewhere

Rule 2: Minimize Lock Scope

// ❌ Bad: lock held too long
let guard = data.lock();
do_work(&guard);
more_work();  // still locked

// ✅ Good: release early
{
    let guard = data.lock();
    do_work(&guard);
}  // lock released
more_work();

Rule 3: Avoid Locks Across Await

// ❌ Bad: lock across await
let guard = mutex.lock().unwrap();
async_call().await;  // DEADLOCK RISK

// ✅ Good: drop lock before await
let value = {
    let guard = mutex.lock().unwrap();
    guard.clone()
};  // lock dropped
async_call().await;

Performance Considerations

Async-Specific Patterns

Spawning Tasks

// Spawn independent task
tokio::spawn(async move {
    process_data(data).await
});

// Spawn with 'static requirement
tokio::spawn(async move {
    let data = Arc::clone(&data);  // Share ownership
    work_with(data).await
});

Concurrent Operations

use tokio::join;

// Wait for all to complete
let (result1, result2, result3) = tokio::join!(
    fetch_user(),
    fetch_posts(),
    fetch_comments()
);

// First to complete
let result = tokio::select! {
    r = fetch_from_primary() => r,
    r = fetch_from_backup() => r,
};

Timeout and Cancellation

use tokio::time::{timeout, Duration};

match timeout(Duration::from_secs(5), long_operation()).await {
    Ok(result) => result,
    Err(_) => {
        // Operation timed out
    }
}

Review Checklist

When reviewing concurrent code:

• All shared data properly synchronized (Arc/Mutex/RwLock)
• Send/Sync bounds satisfied for types crossing threads
• No locks held across await points
• Consistent lock ordering to prevent deadlocks
• Appropriate choice between threads and async
• Message passing channels used correctly (no deadlocks)
• Atomic operations used for simple shared state
• Thread pool sized appropriately for workload
• Error handling for lock poisoning
• Graceful shutdown and resource cleanup

Verification Commands

# Check compilation with thread safety
cargo check

# Run tests with thread sanitizer (requires nightly)
RUSTFLAGS="-Z sanitizer=thread" cargo +nightly test

# Test with miri (detect undefined behavior)
cargo +nightly miri test

# Use loom for exhaustive concurrency testing
cargo test --features loom

# Check for race conditions
cargo clippy -- -W clippy::mutex_atomic

Common Pitfalls

1. Rc in Multi-threaded Context

Symptom: E0277 error, Rc cannot be sent between threads

Fix: Replace Rc with Arc

// ❌ Bad
let data = Rc::new(value);
thread::spawn(move || { /* use data */ });

// ✅ Good
let data = Arc::new(value);
thread::spawn(move || { /* use data */ });

2. Lock Across Await Points

Symptom: Deadlock or "future cannot be sent between threads safely"

Fix: Drop lock before await

// ❌ Bad
let guard = mutex.lock().unwrap();
async_fn().await;

// ✅ Good
let value = mutex.lock().unwrap().clone();
drop(guard);  // Explicit drop
async_fn().await;

3. Missing Arc Clone

Symptom: Borrow checker errors when spawning threads

Fix: Clone Arc before moving into closure

// ❌ Bad
let data = Arc::new(vec![1, 2, 3]);
thread::spawn(move || { /* data moved */ });
// data is gone

// ✅ Good
let data = Arc::new(vec![1, 2, 3]);
let data_clone = Arc::clone(&data);
thread::spawn(move || { /* data_clone moved */ });
// data still available

Related Skills

• rust-async - Advanced async patterns (Stream, select, backpressure)
• rust-async-pattern - Async architecture and design patterns
• rust-ownership - Understanding ownership for thread safety
• rust-mutability - Interior mutability patterns (Cell, RefCell)
• rust-performance - Concurrency performance optimization
• rust-unsafe - Writing safe concurrent abstractions

Localized Reference

• Chinese version: SKILL_ZH.md - 完整中文版本，包含所有内容