Concurrent and Serial queues help us to manage how we execute tasks and help to make our applications run faster, more efficiently, and with improved responsiveness. We can create queues easily using the DispatchQueue class which is built on top of the Grand Central Dispatch (GCD) queue.
The benefit of dispatch queues is that they’re a lot simpler to understand and more efficient at executing tasks on different threads compared to the lower level GCD threading code. Still, there’s a lot to learn, so let’s dive into the differences between concurrent and serial queues.
What is a dispatch queue?
A DispatchQueue is an abstraction layer on top of the GCD queue that allows you to perform tasks asynchronously and concurrently in your application. Tasks are always executed in the order they’re added to the queue.
What is a serial queue?
A serial Dispatch Queue performs only one task at the time. Serial queues are often used to synchronize access to a specific value or resource to prevent data races to occur.
Creating a serial dispatch queue
A DispatchQueue defaults to a serial queue and can be initialized as follows:
let serialQueue = DispatchQueue(label: "swiftlee.serial.queue")
serialQueue.async {
print("Task 1 started")
// Do some work..
print("Task 1 finished")
}
serialQueue.async {
print("Task 2 started")
// Do some work..
print("Task 2 finished")
}
/*
Serial Queue prints:
Task 1 started
Task 1 finished
Task 2 started
Task 2 finished
*/As you can see, the second task only starts after the first task is finished.
What is a concurrent queue?
A concurrent queue allows us to execute multiple tasks at the same time. Tasks will always start in the order they’re added but they can finish in a different order as they can be executed in parallel. Tasks will run on distinct threads that are managed by the dispatch queue. The number of tasks running at the same time is variable and depends on system conditions.
Creating a concurrent dispatch queue
A concurrent dispatch queue can be created by passing in an attribute as a parameter to the DispatchQueue initializer:
let concurrentQueue = DispatchQueue(label: "swiftlee.concurrent.queue", attributes: .concurrent)
concurrentQueue.async {
print("Task 1 started")
// Do some work..
print("Task 1 finished")
}
concurrentQueue.async {
print("Task 2 started")
// Do some work..
print("Task 2 finished")
}
/*
Concurrent Queue prints:
Task 1 started
Task 2 started
Task 1 finished
Task 2 finished
*/As you can see, the second task already starts before the first task is finished. This means that both tasks have run in parallel.
The best of both worlds
In some cases, it’s valuable to benefit from the concurrent queue to perform multiple tasks at the same time while still preventing data races. This is possible by making use of a so-called barrier. Before we dive in, it’s good to know what a data race exactly is.
What is a data race?
A data race can occur when multiple threads access the same memory without synchronization and at least one access is a write. You could be reading values from an array from the main thread while a background thread is adding new values to that same array.
Data races can be the root cause behind flaky tests and weird crashes. Therefore, it’s good practice to regularly spend time using the Thread Sanitizer.
Using a barrier on a concurrent queue to synchronize writes
A barrier flag can be used to make access to a certain resource or value thread-safe. We synchronize write access while we keep the benefit of reading concurrently.
The following code demonstrates a messenger class that can be accessed from multiple threads at the same time. Adding new messages to the array is done using the barrier flag which blocks new reads until the write is finished.
final class Messenger {
private var messages: [String] = []
private var queue = DispatchQueue(label: "messages.queue", attributes: .concurrent)
var lastMessage: String? {
return queue.sync {
messages.last
}
}
func postMessage(_ newMessage: String) {
queue.sync(flags: .barrier) {
messages.append(newMessage)
}
}
}
let messenger = Messenger()
// Executed on Thread #1
messenger.postMessage("Hello SwiftLee!")
// Executed on Thread #2
print(messenger.lastMessage) // Prints: Hello SwiftLee!You can see a barrier as a task that gets in the way of parallel tasks and, for a moment, makes a concurrent queue a serial queue. A task executed with a barrier is delayed until all previously submitted tasks are finished executing. After the last task is finished, the queue executes the barrier block and resumes its normal execution behavior after that.
Asynchronous vs synchronous tasks
A DispatchQueue task can be run synchronously or asynchronously. The main difference occurs when you create the task.
- Synchronously starting a task will block the calling thread until the task is finished
- Asynchronously starting a task will directly return on the calling thread without blocking
Say you would add a task to the queue from the main thread, you want to prevent yourself from using the sync method for long-running tasks. This would block the main thread and makes your UI unresponsive.
How about the main thread?
The main dispatch queue is a globally available serial queue executing tasks on the application’s main thread. As the main thread is used for UI updates it’s important to be conscious when executing tasks on this queue. Therefore, it’s valuable to use the earlier described dispatch APIs to perform tasks on a different thread.
You can start doing the heavy lifting on a background queue and dispatch back to the main queue when you’re done.
let concurrentQueue = DispatchQueue(label: "swiftlee.concurrent.queue", attributes: .concurrent)
concurrentQueue.async {
// Perform the data request and JSON decoding on the background queue.
fetchData()
DispatchQueue.main.async {
/// Access and reload the UI back on the main queue.
tableView.reloadData()
}
}Avoiding excessive thread creation
After reading this blog post it might be tempting to create a lot of queues to gain better performance in your app. Unfortunately, creating threads comes with a cost and you should, therefore, avoid excessive thread creation.
There are two common scenarios in which excessive thread creation occurs:
- Too many blocking tasks are added to concurrent queues forcing the system to create additional threads until the system runs out of threads for your app
- Too many private concurrent dispatch queues exist that all consume thread resources.
How to prevent excessive thread creation?
It’s best practice to make use of the global concurrent dispatch queues. This prevents you from creating too many private concurrent queues. Apart from this, you should still be conscious of executing long-blocking tasks.
You can make use of the global concurrent queue as follows:
DispatchQueue.global().async {
/// Concurrently execute a task using the global concurrent queue. Also known as the background queue.
}This global concurrent queue is also known as the background queue and used next to the DispatchQueue.main.
Conclusion
That’s it, a deep dive into dispatch queues in Swift. There’s a lot more to cover but the basics are described here. Make sure to check out the Thread Sanitizer to see where you can improve your app for data races.
If you like to improve your Swift knowledge, even more, check out the Swift category page. Feel free to contact me or tweet to me on Twitter if you have any additional tips or feedback.
Thanks!