What's the Key Difference Between `Thread.start()` and `Thread.run()` in Java?
Understanding the Nuances of Thread.start() and Thread.run()
The distinction between Thread.start() and Thread.run() in Java plays a crucial role in multithreading. While both methods involve executing the run() method, they do so in fundamentally different ways.
Thread.run(): Direct Execution
Calling run() directly executes the run() method in the current thread. This means there is no separate thread created for the task. Instead, the task is executed as part of the calling thread's execution.
Example:
public class MyThread extends Thread { @Override public void run() { System.out.println("Running directly..."); } } public class Main { public static void main(String[] args) { MyThread thread = new MyThread(); thread.run(); } }
Output:
Running directly...
In this example, calling run() directly prints "Running directly..." from the main thread, as no separate thread is created.
Thread.start(): New Thread Creation
In contrast, calling start() creates a new thread and executes the run() method within that new thread. This allows multiple tasks to run concurrently.
Example:
public class MyThread extends Thread { @Override public void run() { System.out.println("Running in new thread..."); } } public class Main { public static void main(String[] args) { MyThread thread = new MyThread(); thread.start(); } }
Output:
Running in new thread...
Note that calling start() does not immediately execute the run() method. Instead, a new thread is created, and the Java Virtual Machine decides when to schedule and execute it.
Practical Difference
The difference between Thread.start() and Thread.run() becomes apparent when considering tasks that take significant time to complete. If a task is exécuté directly using run(), the main thread will be blocked until the task finishes, preventing other tasks from being exécute in the meantime. This can lead to poor performance and responsiveness.
By using start(), the task is exécuté in a separate thread, allowing the main thread to continue executing other tasks concurrently. This improves overall performance and maintains responsiveness.
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