Asynchronous programming with Java & Spring

Jan 29, 20230 likes42 views

Asynchronous programming allows starting a thread to assign a task without blocking the main thread. It uses resources optimally and avoids freezing user interfaces. Asynchronous programming evolved from threads to thread pools and futures. It differs from multithreading by staying mostly in a single thread without synchronization issues. Asynchronous tasks can be created using thread pools like fixed, cached, and scheduled pools. Completable futures improved on futures by making chaining of asynchronous tasks easier through completion stages that represent tasks and their states.

Asynchronous programming with Java & Spring

Asynchronous - Definition
● Start a thread and assign a task.
● Get notified once the result is ready
● Process the result

Why asynchrony?
● It’s faster
● Use available resources optimally
● Avoid freezing UI - Swing components should be manipulated only via the
event dispatching thread. Offload long running tasks to a separate thread

A brief History
● Started with Threads and tasks
● Thread pools and futures
● Completable Future API

Multithreading vs asynchronous programming
● Asynchronous programming - mostly stays in a single thread.
● No visibility and atomicity issues
● No synchronization is required
● Thread confinement
● No context switch as it is single threaded
● Async is non-blocking - due to the callbacks

Thread per task approach - drawbacks
● Thread lifecycle overhead - creation and teardown cost is high
● Resource consumption - memory
● There’s a limit on number of threads can be created

Thread pools
● Manages a homogenous pool of worker threads
● Bound to a work queue holding tasks waiting to be executed
● Decouples task submission from execution

Types of thread pools
● Fixed thread pool - grows up to the max size and then keep the pool size
constant
● Cached thread pool - more flexibility to reap idle threads. No bounds on the
pool size
● Single thread executor - Sequential task execution
● Scheduled thread pool - Fixed size thread pool supporting periodic tasks

Result bearing tasks
● Callable and future
● Future allows checking whether the task is cancelled, completed, retrieve it’s
results and cancel the task
● Blocking synchronizer - future.get() is blocking !
● Future - bridge between master thread and worker thread executing the task
● Makes chaining of tasks much difficult - need to pass future object around
● Completable future addresses this issue !

What is a completion stage
● A model for task
● Performs an action
● May trigger other tasks
● It’s an element of a chain

Completable future - states
● The task may be running
● The task may have completed normally
● The task may have completed exceptionally

Composition API
● Supplier, function and a consumer used for rendering links on a web page

References
[1] https://www.youtube.com/watch?v=HdnHmbFg_hw

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Lecture 23-24.pptxtalha ijaz

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The document discusses async-await in C# and how it works under the hood. It begins with questions about what happens when await is used. It then explains that async-await is used to compose asynchronous code using task continuations generated by the compiler. It discusses how await marks a continuation and depends on the context to determine threading. Windows I/O is used as an example of asynchronous operations without threads. The document concludes with recommendations to avoid deadlocks by not blocking on async code and to only use async-void for event handlers.

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This document provides an overview of concurrency concepts in C#, including multithreading, parallel programming, asynchronous programming, and reactive programming. It discusses how concurrency allows applications to do multiple tasks simultaneously. Modern .NET libraries and language features like async/await have made concurrency much easier. The key benefits of concurrency are improving responsiveness and maximizing hardware. Multithreading uses multiple threads of execution running concurrently. Parallel programming splits work across threads to maximize CPU usage. Asynchronous programming uses futures/callbacks to avoid blocking threads. Reactive programming treats event streams declaratively.

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Here are a few steps I would take to analyze the issue: 1. Collect a thread dump of the application to see what threads are currently running and in what state. This will give clues about any threads that may be blocked or spinning. 2. Analyze the thread dump looking for threads that are in a RUNNABLE or BLOCKED state long-term. These could indicate spinning or long waits. 3. Check for threads waiting on locks, semaphores or other synchronization primitives. This could point to a potential deadlock. 4. Trace the code path and logic for threads of interest to understand what they are trying to accomplish and why they may be spinning or blocked. 5. Check

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Asynchronous programming with Java & Spring

1. Asynchronous programming with Java & Spring

2. Asynchronous - Definition ● Start a thread and assign a task. ● Get notified once the result is ready ● Process the result

3. Why asynchrony? ● It’s faster ● Use available resources optimally ● Avoid freezing UI - Swing components should be manipulated only via the event dispatching thread. Offload long running tasks to a separate thread

4. A brief History ● Started with Threads and tasks ● Thread pools and futures ● Completable Future API

5. Multithreading vs asynchronous programming ● Asynchronous programming - mostly stays in a single thread. ● No visibility and atomicity issues ● No synchronization is required ● Thread confinement ● No context switch as it is single threaded ● Async is non-blocking - due to the callbacks

6. Creation of an synchronous task

7. Thread per task approach - drawbacks ● Thread lifecycle overhead - creation and teardown cost is high ● Resource consumption - memory ● There’s a limit on number of threads can be created

8. Thread pools ● Manages a homogenous pool of worker threads ● Bound to a work queue holding tasks waiting to be executed ● Decouples task submission from execution

9. Creation of an synchronous task

10. Types of thread pools ● Fixed thread pool - grows up to the max size and then keep the pool size constant ● Cached thread pool - more flexibility to reap idle threads. No bounds on the pool size ● Single thread executor - Sequential task execution ● Scheduled thread pool - Fixed size thread pool supporting periodic tasks

11. Result bearing tasks ● Callable and future ● Future allows checking whether the task is cancelled, completed, retrieve it’s results and cancel the task ● Blocking synchronizer - future.get() is blocking ! ● Future - bridge between master thread and worker thread executing the task ● Makes chaining of tasks much difficult - need to pass future object around ● Completable future addresses this issue !

12. Completable future API

13. How to test it

14. What is a completion stage ● A model for task ● Performs an action ● May trigger other tasks ● It’s an element of a chain

15. Completable future - states ● The task may be running ● The task may have completed normally ● The task may have completed exceptionally

16. Building completion stage chains

17. Composition API ● Supplier, function and a consumer used for rendering links on a web page

18. Conclusion

19. References [1] https://www.youtube.com/watch?v=HdnHmbFg_hw

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