


Java Memory Model and Visibility: A closer look at data consistency in multi-threaded programming
php editor Xigua will take you to deeply explore the Java memory model and visibility, and analyze the data consistency issues in multi-threaded programming. In a multi-threaded environment, data visibility is critical to program correctness. By deeply analyzing the Java memory model, we can better understand the mechanism of data interaction in multi-threaded programming, thereby avoiding unexpected problems. In this article, we will discuss key issues in multi-threaded programming to help readers better understand and apply the relevant knowledge of the Java memory model.
- Visibility:
Visibility means that modifications to shared variables by one thread can be immediately seen by other threads. In JMM, visibility is achieved through memory barriers. A memory barrier is a special instruction that forces the JVM to flush the cache before or after performing a memory operation.
public class VisibilityDemo { private int sharedVar = 0; public void writerThread() { sharedVar = 42; } public void readerThread() { int localVar = sharedVar; // 可能读取到旧值 System.out.println("Reader thread: " + localVar); } public static void main(String[] args) { VisibilityDemo demo = new VisibilityDemo(); Thread writer = new Thread(demo::writerThread); Thread reader = new Thread(demo::readerThread); writer.start(); reader.start(); writer.join(); reader.join(); } }
In the above example, writerThread
and readerThread
access the shared variable sharedVar
at the same time. Without a memory barrier, readerThread
may read old sharedVar
values, causing the program to output incorrect results. To solve this problem, a memory barrier can be inserted between writerThread
and readerThread
.
public class VisibilityDemoWithMemoryBarrier { private int sharedVar = 0; public void writerThread() { // 插入内存屏障 synchronized (this) {} sharedVar = 42; } public void readerThread() { // 插入内存屏障 synchronized (this) {} int localVar = sharedVar; System.out.println("Reader thread: " + localVar); } public static void main(String[] args) { VisibilityDemoWithMemoryBarrier demo = new VisibilityDemoWithMemoryBarrier(); Thread writer = new Thread(demo::writerThread); Thread reader = new Thread(demo::readerThread); writer.start(); reader.start(); writer.join(); reader.join(); } }
In the above example, we inserted a memory barrier between writerThread
and readerThread
(by calling the synchronized
method). In this way, readerThread
will be able to immediately see writerThread
's modifications to sharedVar
without erroneous results.
- Atomicity:
Atomicity means that an operation is either completely executed or not executed at all. In JMM, atomicity is achieved through atomic variables and atomic operations (atomic operation).
Atomic variable is a special variable that can only be accessed by one thread at the same time. An atomic operation is a special operation that can be performed without interruption.
import java.util.concurrent.atomic.AtomicInteger; public class AtomicityDemo { private AtomicInteger sharedVar = new AtomicInteger(0); public void incrementSharedVar() { sharedVar.incrementAndGet(); } public static void main(String[] args) { AtomicityDemo demo = new AtomicityDemo(); Thread[] threads = new Thread[10]; for (int i = 0; i < threads.length; i++) { threads[i] = new Thread(demo::incrementSharedVar); } for (Thread thread : threads) { thread.start(); } for (Thread thread : threads) { thread.join(); } System.out.println("Final value of sharedVar: " + demo.sharedVar.get()); } }
In the above example, we use atomic variables sharedVar
to ensure that modifications to sharedVar
by multiple threads are atomic. Even if multiple threads modify sharedVar
at the same time, the final result will be correct.
- Applications of JMM:
JMM is widely used in multi-threaded programming, such as:
- Thread-safe class design: JMM can help us design thread-safe classes to ensure that shared variables in the class can be accessed correctly in a multi-threaded environment.
- Concurrent data structure implementation: JMM can help us implement ConcurrencyData structures, such as concurrent queues, concurrent stacks, etc. These data structures can be used in multiple threads safe to use in the environment.
- High-performance concurrent algorithm design: JMM can help us design high-performance concurrent algorithms , such as no lock algorithms, etc. These algorithms can make full use of multi-core CPU advantages for higher performance.
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