The StampedLock class in Java’s concurrency utilities (introduced in Java 8) is a high-performance read/write lock that differs from traditional ReadWriteLock (like ReentrantReadWriteLock) due to its ability to provide three locking modes:

1. Write Lock: Exclusive access.
2. Read Lock: Shared (non-exclusive) access.
3. Optimistic Read Lock: A lightweight, non-blocking read lock for scenarios where reads dominate writes, but data consistency needs to be validated.

Below is an explanation of how to use StampedLock effectively for high-performance locking in different contexts:

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1. Write Lock

The write lock is used when exclusive access to the shared resource is required, such as for updates. It provides behavior similar to a traditional lock but with better performance in many scenarios.

Example:

package org.kodejava.util.concurrent;

import java.util.concurrent.locks.StampedLock;

public class StampedLockExample {
    private int count = 0;
    private final StampedLock lock = new StampedLock();

    public void increment() {
        long stamp = lock.writeLock(); // Acquire write lock
        try {
            count++;
        } finally {
            lock.unlockWrite(stamp); // Release write lock
        }
    }
}

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2. Read Lock

The read lock is used when shared access to a resource is sufficient, and there are no write operations being performed. It provides better throughput than a traditional lock by allowing multiple threads to read concurrently.

Example:

public int getCount() {
    long stamp = lock.readLock(); // Acquire read lock
    try {
        return count;
    } finally {
        lock.unlockRead(stamp); // Release read lock
    }
}

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3. Optimistic Read Lock

The optimistic read lock is a key feature of StampedLock and is designed for scenarios where reads dominate and writes are infrequent. This mode allows a thread to proceed without actually acquiring a lock, provided that the shared resource isn’t later invalidated by a write operation.

Process:

1. Acquire an optimistic read stamp with lock.tryOptimisticRead().
2. Perform the read operation.
3. Validate the stamp with lock.validate(stamp). If the stamp is no longer valid (i.e., a write operation occurred), fall back to a read lock.

Example:

public int optimisticReadCount() {
    long stamp = lock.tryOptimisticRead(); // Try optimistic read
    int currentCount = count; // Perform read operation

    if (!lock.validate(stamp)) { // Check if stamp is still valid
        // Fallback to read lock if a write occurred during the read
        stamp = lock.readLock();
        try {
            currentCount = count;
        } finally {
            lock.unlockRead(stamp);
        }
    }

    return currentCount; // Return the read value
}

This approach is highly efficient in scenarios with minimal contention, as it avoids actual locking unless necessary.

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4. Combining Reads and Writes

Sometimes, a single operation involves both reads and writes. In such cases, you can upgrade from a read lock to a write lock using the convertToWriteLock method:

Example:

public void conditionalIncrement() {
    long stamp = lock.readLock();
    try {
        if (count < 10) {
            // Upgrade to write lock if modification is needed
            stamp = lock.tryConvertToWriteLock(stamp);
            if (stamp == 0L) { // Failed to upgrade, acquire write lock normally
                stamp = lock.writeLock();
            }
            count++;
        }
    } finally {
        lock.unlock(stamp); // Release the appropriate lock
    }
}

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5. Things to Keep in Mind

• Deadlock Avoidance: StampedLock does not support reentrancy (unlike ReentrantLock). Each thread must acquire the lock only once; otherwise, it may lead to deadlocks.
• Performance: Using optimistic reads can offer great performance improvements in read-heavy scenarios, but they require careful validation to ensure correctness.
• Fairness: StampedLock is not fair and does not guarantee lock acquisition order.

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When to Use StampedLock

• Optimistic Reads: If your application has far more reads than writes, and contention is generally low.
• Shared Data Structures: For use cases like caching or maintaining shared state across threads, where high throughput is critical.

StampedLock strikes a balance between ease of use and performance, making it a valuable tool for high-performance concurrency tasks in Java!