This talk and workshop was presented in Stockholm, Sweden. The goal of the presentation was to introduce Rust to Web engineers, talking about Tokio, Async, Lifetime, AWS SDK, Open Telemetry and etecetera.
OS threads don't require any changes to the programming model, which makes it very easy to express concurrency. However, synchronizing between threads can be difficult, and the performance overhead is large. Thread pools can mitigate some of these costs, but not enough to support massive IO-bound workloads. other concurrency models
OS threads don't require any changes to the programming model, which makes it very easy to express concurrency. However, synchronizing between threads can be difficult, and the performance overhead is large. Thread pools can mitigate some of these costs, but not enough to support massive IO-bound workloads. other concurrency models
OS threads don't require any changes to the programming model, which makes it very easy to express concurrency. However, synchronizing between threads can be difficult, and the performance overhead is large. Thread pools can mitigate some of these costs, but not enough to support massive IO-bound workloads. other concurrency models
other concurrency models Event-driven programming, in conjunction with callbacks, can be very performant, but tends to result in a verbose, "non-linear" control flow.
Data flow and error propagation is often hard to follow.
Coroutines, like threads, don't require changes to the programming model, which makes them easy to use. Like async, they can also support a large number of tasks.
However, they abstract away low-level details that are important for systems programming and custom runtime implementors. other concurrency models
Coroutines, like threads, don't require changes to the programming model, which makes them easy to use. Like async, they can also support a large number of tasks.
However, they abstract away low-level details that are important for systems programming and custom runtime implementors. other concurrency models
The actor model divides all concurrent computation into units called actors, which communicate through fallible message passing, much like in distributed systems.
The actor model can be efficiently implemented, but it leaves many practical issues unanswered, such as flow control and retry logic. other concurrency models
The actor model divides all concurrent computation into units called actors, which communicate through fallible message passing, much like in distributed systems.
The actor model can be efficiently implemented, but it leaves many practical issues unanswered, such as flow control and retry logic. other concurrency models
Asynchronous programming allows highly performant implementations that are suitable for low-level languages like Rust, while providing most of the ergonomic benefits of threads and coroutines.
Async vs threads in Rust A thread pool library can help mitigate some of these costs, but not all. However, threads let you reuse existing synchronous code without significant code changes—no particular programming model is required. In some operating systems, you can also change the priority of a thread, which is useful for drivers and other latency sensitive applications.
Async vs threads in Rust Async provides significantly reduced CPU and memory overhead, especially for workloads with a large amount of IO-bound tasks, such as servers and databases.
All else equal, you can have orders of magnitude more tasks than OS threads, because an async runtime uses a small amount of (expensive) threads to handle a large amount of (cheap) tasks.
Async vs threads in Rust However, async Rust results in larger binary blobs due to the state machines generated from async functions and since each executable bundles an async runtime.
On a last note, asynchronous programming is not better than threads, but different. If you don't need async for performance reasons, threads can often be the simpler alternative.
Inside an async fn, you can use .await to wait for the completion of another type that implements the Future trait, such as the output of another async fn. Unlike block_on, .await doesn't block the current thread, but instead asynchronously waits for the future to complete, allowing other tasks to run if the future is currently unable to make progress.
In this example, learning the song must happen before singing the song, but both learning and singing can happen at the same time as dancing. If we used block_on(learn_song()) rather than learn_song().await in learn_and_sing, the thread wouldn't be able to do anything else while learn_song was running.
This would make it impossible to dance at the same time. By .await-ing the learn_song future, we allow other tasks to take over the current thread if learn_song is blocked. This makes it possible to run multiple futures to completion concurrently on the same thread.
- Synchronization primitives, channels and timeouts, sleeps, and intervals. - APIs for performing asynchronous I/O, including TCP and UDP sockets, filesystem operations, and process and signal management. - A runtime for executing asynchronous code, including a task scheduler, an I/O driver backed by the operating system’s event queue (epoll, kqueue, IOCP, etc…), and a high performance timer.
- Synchronization primitives, channels and timeouts, sleeps, and intervals. - APIs for performing asynchronous I/O, including TCP and UDP sockets, filesystem operations, and process and signal management. - A runtime for executing asynchronous code, including a task scheduler, an I/O driver backed by the operating system’s event queue (epoll, kqueue, IOCP, etc…), and a high performance timer.
- Synchronization primitives, channels and timeouts, sleeps, and intervals. - APIs for performing asynchronous I/O, including TCP and UDP sockets, filesystem operations, and process and signal management. - A runtime for executing asynchronous code, including a task scheduler, an I/O driver backed by the operating system’s event queue (epoll, kqueue, IOCP, etc…), and a high performance timer.
Router::new() // request processed inside span .route("/", get(health)) // opentelemetry_tracing_layer setup `TraceLayer`, // that is provided by tower-http so you have // to add that as a dependency. .layer(opentelemetry_tracing_layer()) .route("/health", get(health))
use aws_sdk_dynamodb as dynamodb; #[tokio::main] async fn main() -> Result { let config = aws_config::load_from_env().await; // aws_config::from_conf(config_params); let client = dynamodb::Client::new(&config);
use aws_sdk_dynamodb as dynamodb; #[tokio::main] async fn main() -> Result { let config = aws_config::load_from_env().await; // aws_config::from_conf(config_params); let client = dynamodb::Client::new(&config);
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