Скачать или смотреть Understanding Multi-threading in Async Rust: Why Your Code May Fail to Parallelize

Discover why your async Rust code isn’t executing in parallel and learn effective solutions to leverage multi-threading for better performance.
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Understanding Multi-threading in Async Rust: Why Your Code May Fail to Parallelize

If you're working with Rust and trying to achieve parallelization through async functions, you might run into challenges that can significantly slow down your code. A common question among Rust developers is, “Why is my code failing to execute in parallel?” Let's explore the issues behind this question and unveil effective solutions to harness multi-threading in async Rust.

The Problem: Running Async Blocks in Parallel

You might have written your Rust function with the intention of exhausting an API limit of 900 calls in parallel across its 16 cores. Here’s an example of how the original code looks:

[[See Video to Reveal this Text or Code Snippet]]

Why Is it Not Working?

Although it seems like you're creating multiple threads, the execution is effectively single-threaded due to how async functions are managed in Rust:

Understanding Future: In Rust, an async block creates a type that implements the Future trait. However, Futures do not start executing on their own; they must be awaited or passed to an executor.

Thread Execution: Using thread::spawn here wrongly leads to the threads merely creating the async block. Consequently, the threads are not executing any tasks until they are awaited in the loop over handles.

As a result, your code runs just as slowly as a pure single-threaded version because all async execution is effectively serialized rather than running concurrently.

The Solution: Leveraging join_all

To effectively parallelize your API calls, you can utilize the join_all function from the futures crate. This function allows for the simultaneous execution of multiple Futures rather than forcing them to run sequentially through threading. Here’s how to do it:

Updated Code Example

[[See Video to Reveal this Text or Code Snippet]]

Key Changes Made

Removed thread::spawn: Instead of placing the async block inside a thread, we directly push the futures to a vector.

Utilizing join_all: Use futures::future::join_all to await all futures concurrently, allowing them to execute in parallel across the available cores.

Benefits of This Approach

Improved Performance: By executing tasks concurrently, you significantly reduce the total time taken to exhaust the API limit.

Cleaner Code: The updated approach results in simpler, more maintainable code that leverages Rust’s strengths in asynchronous programming.

Conclusion

When working with async Rust, understanding how Futures operate and their interaction with threading is pivotal. It enables you to write efficient and concurrent code that maximizes the potential of your machine's resources. By shifting from thread-based concurrency to a proper async execution leveraging join_all, you can solve the problem of slow execution and fully harness the power of multi-threading.

For any Rust developer battling with async and threading, this adjustment can be a game-changer. Embrace these practices, and enhance the performance of your applications!