高併發場景下需加鎖保證業務邏輯正確性,但鎖粒度過大會嚴重影響效能。Java 原生鎖粒度較粗,難以滿足按業務鍵(如時間戳、ID)加鎖需求。本文實現三種細粒度鎖策略:分段鎖、哈希鎖、弱引用鎖。
借鑑 ConcurrentHashMap 分段思想,預創建固定數量鎖,根據 key 的 hash 值映射到對應鎖。最簡單、效能最高,最終採用方案。
public class SegmentLock<T> {
private Integer segments = 16;
private final HashMap<Integer, ReentrantLock> lockMap = new HashMap<>();
public SegmentLock() { init(null, false); }
public SegmentLock(Integer counts, boolean fair) { init(counts, fair); }
private void init(Integer counts, boolean fair) {
if (counts != null) segments = counts;
for (int i = 0; i < segments; i++) lockMap.put(i, new ReentrantLock(fair));
}
public void lock(T key) {
ReentrantLock lock = lockMap.get((key.hashCode() >>> 1) % segments);
lock.lock();
}
public void unlock(T key) {
ReentrantLock lock = lockMap.get((key.hashCode() >>> 1) % segments);
lock.unlock();
}
}
注意:被鎖物件的 hashCode 若發生變化,會導致鎖無法釋放。
基於分段鎖演進,目標實現真正細粒度:每個 hash 值不同的物件擁有獨立鎖。測試中,鎖住代碼執行極快時比分段鎖慢約 30%,若有長耗時操作表現應更好。
public class HashLock<T> {
private boolean isFair = false;
private final SegmentLock<T> segmentLock = new SegmentLock<>();
private final ConcurrentHashMap<T, LockInfo> lockMap = new ConcurrentHashMap<>();
public void lock(T key) {
LockInfo lockInfo;
segmentLock.lock(key);
try {
lockInfo = lockMap.get(key);
if (lockInfo == null) {
lockInfo = new LockInfo(isFair);
lockMap.put(key, lockInfo);
} else {
lockInfo.count.incrementAndGet();
}
} finally { segmentLock.unlock(key); }
lockInfo.lock.lock();
}
public void unlock(T key) {
LockInfo lockInfo = lockMap.get(key);
if (lockInfo.count.get() == 1) {
segmentLock.lock(key);
try {
if (lockInfo.count.get() == 1) lockMap.remove(key);
} finally { segmentLock.unlock(key); }
}
lockInfo.count.decrementAndGet();
lockInfo.unlock();
}
private static class LockInfo {
public ReentrantLock lock;
public AtomicInteger count = new AtomicInteger(1);
private LockInfo(boolean fair) { this.lock = new ReentrantLock(fair); }
public void lock() { this.lock.lock(); }
public void unlock() { this.lock.unlock(); }
}
}
利用 Java 弱引用創建鎖,將鎖銷毀交給 JVM GC,避免額外開銷。因使用 ConcurrentHashMap 作為容器,未能完全擺脫分段鎖。效能比 HashLock 快約 10%。
public class WeakHashLock<T> {
private ConcurrentHashMap<T, WeakLockRef<T, ReentrantLock>> lockMap = new ConcurrentHashMap<>();
private ReferenceQueue<ReentrantLock> queue = new ReferenceQueue<>();
public ReentrantLock get(T key) {
if (lockMap.size() > 1000) clearEmptyRef();
WeakReference<ReentrantLock> lockRef = lockMap.get(key);
ReentrantLock lock = (lockRef == null ? null : lockRef.get());
while (lock == null) {
lockMap.putIfAbsent(key, new WeakLockRef<>(new ReentrantLock(), queue, key));
lockRef = lockMap.get(key);
lock = (lockRef == null ? null : lockRef.get());
if (lock != null) return lock;
clearEmptyRef();
}
return lock;
}
@SuppressWarnings("unchecked")
private void clearEmptyRef() {
Reference<? extends ReentrantLock> ref;
while ((ref = queue.poll()) != null) {
WeakLockRef<T, ? extends ReentrantLock> weakLockRef = (WeakLockRef<T, ? extends ReentrantLock>) ref;
lockMap.remove(weakLockRef.key);
}
}
private static final class WeakLockRef<T, K> extends WeakReference<K> {
final T key;
private WeakLockRef(K referent, ReferenceQueue<? super K> q, T key) {
super(referent, q); this.key = key;
}
}
}
初期嘗試基於 LockSupport 和 AQS 實現,發現與原生鎖差異不大,轉而封裝 JDK 鎖。後續思考:可透過分段思想將數據提交給專門線程處理,減少線程阻塞,留待後續探索。