Скачать или смотреть Exploring Coroutines and Threads: The Battle of Thread.sleep() vs. delay() in Kotlin

Discover the impact of using `Thread.sleep()` versus `delay()` in Kotlin coroutines. Understand thread management, performance, and the extra thread that emerges during execution.
---
This video is based on the question https://stackoverflow.com/q/77127850/ asked by the user 'Mena' ( https://stackoverflow.com/u/8086424/ ) and on the answer https://stackoverflow.com/a/77128864/ provided by the user 'Tenfour04' ( https://stackoverflow.com/u/506796/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Coroutines and number of threads: Thread.sleep() vs delay()

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Understanding Coroutines and Threads in Kotlin: The Impact of Thread.sleep() vs. delay()

When working with Kotlin, especially in concurrent programming, understanding how coroutines interact with threads is crucial. In this guide, we'll explore a common scenario where developers might face a choice: should they use Thread.sleep() or delay() within coroutines? To illustrate this, we will dive into a practical example and examine the differences between these two approaches.

The Problem at Hand

The challenge arises when you need to execute long-running tasks within coroutines. A developer wrote two functions, each containing multiple coroutines that simulate work. Here’s a quick snapshot of the implementation:

Using Thread.sleep(): The first function (fun1) relies on Thread.sleep() to represent long-running operations.

Using delay(): The second function (fun2) employs delay() for long-running operations.

The goal is to compare how these two methods affect thread management and execution time.

Detailed Examination of the Example

Function Implementations

Let’s summarize the key sections of each function:

Using Thread.sleep() in fun1:

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

Using delay() in fun2:

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

Console Output Observations

When running fun1, the console outputs indicate that the maximum number of threads working is 3. Each coroutine creates workloads that completely block the thread they're running on.

In contrast, executing fun2, the output shows a maximum number of working threads reaching 4. This discrepancy leads us to question the underlying mechanisms responsible for managing these threads.

The Role of delay()

The functionality of delay() varies based on the current dispatcher in use. Here is why the number of active threads increases when using delay():

Default Implementation: Both the Default and IO dispatchers do not define their delay mechanism; they utilize a shared Executor for scheduling delays and callbacks. This characteristic allows delay() to be non-blocking.

Shared Executor: In environments without a Dispatchers.Main, the default implementation of delay() relies on a shared Executor. This Executor may utilize additional threads to handle scheduled tasks, hence, resulting in that extra thread observed during execution.

Thus, while Thread.sleep() completely halts the thread, delay() permits the coroutine to yield, allowing other tasks to continue executing.

Why It Matters

Concurrency: Using delay() allows more efficient usage of threads and resources, especially when dealing with asynchronous operations.

Responsiveness: Non-blocking delays enhance responsiveness in your application, enabling it to process other tasks concurrently.

Thread Management: Understanding how to manage and schedule threads effectively can prevent bottlenecks and improve overall application performance.

Conclusion

When deciding between Thread.sleep() and delay(), it is crucial to consider the implications on thread management and application performance. While Thread.sleep() may seem simpler for simulating long-running tasks, it blocks threads and limits concurrency. On the other hand, delay() offers a non-blocking solution that keeps the application responsive.

In summary, leveraging coroutines effectively in Kotlin can lead to more efficient applications. By choosing the right tool for the job, developers can harness the full power of Kotlin’s concurrency features.



Remember, successful coding practices not only improve performance but also enrich the user experience.