【优雅代码】15-guavaCache本地缓存使用及源码解析
【优雅代码】15-guavaCache本地缓存使用及源码解析
欢迎关注b站账号/公众号【六边形战士夏宁】,一个要把各项指标拉满的男人。该文章已在github目录收录。
屏幕前的大帅比和大漂亮如果有帮助到你的话请顺手点个赞、加个收藏这对我真的很重要。别下次一定了,都不关注上哪下次一定。
- 视频讲解
- 可直接运行的完整代码
- 上一篇guava精选方法及eventBus观察者模式源码解析
- 下一篇guava布隆过滤与限流算法源码解析
1.背景
承接前一篇章的guava精选方法
2.cache
这一块的功能设计真的很精巧,特别是队列的设计
2.1使用
@SneakyThrows
public static void cache() {
// 注意两个如果一起用有时候会有bug
Cache<Integer, Integer> accessBuild = CacheBuilder.newBuilder().expireAfterAccess(1, TimeUnit.SECONDS).build();
Cache<Integer, Integer> writeBuild = CacheBuilder.newBuilder().expireAfterWrite(1, TimeUnit.SECONDS).build();
accessBuild.put(1, 1);
accessBuild.put(2, 2);
writeBuild.put(1, 1);
writeBuild.put(2, 2);
// 输出1
System.out.println(accessBuild.getIfPresent(1));
// 输出1
System.out.println(writeBuild.getIfPresent(1));
Thread.sleep(500);
// 输出2
System.out.println(accessBuild.getIfPresent(2));
Thread.sleep(600);
// 输出null
System.out.println(accessBuild.getIfPresent(1));
// 输出2
System.out.println(accessBuild.getIfPresent(2));
// 输出null
System.out.println(writeBuild.getIfPresent(1));
}
输出如下
1
1
2
null
2
null
2.2核心源码详解
- 构造方法
// 整体构造链相对简单
// build方法
public <K1 extends K, V1 extends V> Cache<K1, V1> build() {
checkWeightWithWeigher();
checkNonLoadingCache();
return new LocalCache.LocalManualCache<>(this);
}
// 给expireAfterAccessNanos赋值失效时间
public CacheBuilder<K, V> expireAfterAccess(long duration, TimeUnit unit) {
checkState(
expireAfterAccessNanos == UNSET_INT,
"expireAfterAccess was already set to %s ns",
expireAfterAccessNanos);
checkArgument(duration >= 0, "duration cannot be negative: %s %s", duration, unit);
this.expireAfterAccessNanos = unit.toNanos(duration);
return this;
}
// 给expireAfterWriteNanos赋值失效时间
public CacheBuilder<K, V> expireAfterWrite(long duration, TimeUnit unit) {
checkState(
expireAfterWriteNanos == UNSET_INT,
"expireAfterWrite was already set to %s ns",
expireAfterWriteNanos);
checkArgument(duration >= 0, "duration cannot be negative: %s %s", duration, unit);
this.expireAfterWriteNanos = unit.toNanos(duration);
return this;
}
- put
// put方法,和老版本的ConcurrentHashMap一样的设计模式,用segment桶
@Override
public V put(K key, V value) {
checkNotNull(key);
checkNotNull(value);
int hash = hash(key);
return segmentFor(hash).put(key, hash, value, false);
}
V put(K key, int hash, V value, boolean onlyIfAbsent) {
lock();
try {
long now = map.ticker.read();
// **********重点方法:清除过期内容********
preWriteCleanup(now);
int newCount = this.count + 1;
if (newCount > this.threshold) { // ensure capacity
expand();
newCount = this.count + 1;
}
AtomicReferenceArray<ReferenceEntry<K, V>> table = this.table;
int index = hash & (table.length() - 1);
ReferenceEntry<K, V> first = table.get(index);
// Look for an existing entry.
// 这里判断一下是不是已经有同样的key了
for (ReferenceEntry<K, V> e = first; e != null; e = e.getNext()) {
K entryKey = e.getKey();
if (e.getHash() == hash
&& entryKey != null
&& map.keyEquivalence.equivalent(key, entryKey)) {
// We found an existing entry.
ValueReference<K, V> valueReference = e.getValueReference();
V entryValue = valueReference.get();
if (entryValue == null) {
++modCount;
if (valueReference.isActive()) {
enqueueNotification(
key, hash, entryValue, valueReference.getWeight(), RemovalCause.COLLECTED);
setValue(e, key, value, now);
newCount = this.count; // count remains unchanged
} else {
setValue(e, key, value, now);
newCount = this.count + 1;
}
this.count = newCount; // write-volatile
evictEntries(e);
return null;
} else if (onlyIfAbsent) {
// Mimic
// "if (!map.containsKey(key)) ...
// else return map.get(key);
recordLockedRead(e, now);
return entryValue;
} else {
// clobber existing entry, count remains unchanged
++modCount;
enqueueNotification(
key, hash, entryValue, valueReference.getWeight(), RemovalCause.REPLACED);
setValue(e, key, value, now);
evictEntries(e);
return entryValue;
}
}
}
// Create a new entry.
++modCount;
ReferenceEntry<K, V> newEntry = newEntry(key, hash, first);
// **********重点方法:赋值********
setValue(newEntry, key, value, now);
table.set(index, newEntry);
newCount = this.count + 1;
this.count = newCount; // write-volatile
evictEntries(newEntry);
return null;
} finally {
unlock();
// **********重点方法:调用监听者********
postWriteCleanup();
}
}
- setValue
@GuardedBy("this")
void setValue(ReferenceEntry<K, V> entry, K key, V value, long now) {
// 获取这个包装entry原先的值,如果原先这个key不存在,则获取不到东西
ValueReference<K, V> previous = entry.getValueReference();
int weight = map.weigher.weigh(key, value);
checkState(weight >= 0, "Weights must be non-negative");
ValueReference<K, V> valueReference =
map.valueStrength.referenceValue(this, entry, value, weight);
// 将value写入到entry包装对象中
entry.setValueReference(valueReference);
// 核心方法
recordWrite(entry, weight, now);
previous.notifyNewValue(value);
}
@GuardedBy("this")
void recordWrite(ReferenceEntry<K, V> entry, int weight, long now) {
// we are already under lock, so drain the recency queue immediately
drainRecencyQueue();
totalWeight += weight;
if (map.recordsAccess()) {
// 设置访问时间
entry.setAccessTime(now);
}
if (map.recordsWrite()) {
// 设置写时间
entry.setWriteTime(now);
}
// **************重点方法***************这个地方将指针存了两份队列到末尾,因为缓存时间是一致的,所以只要判断队列头部就可以了
accessQueue.add(entry);
writeQueue.add(entry);
}
- WriteQueue与accessQueue
这两个用的实现类基本一致,这里重写了add方法,重写的目的是如果key一样的entry就进行重排而不是插入
@Override
public boolean offer(ReferenceEntry<K, V> entry) {
// unlink
// 将entry的前一个和后一个进行互指
connectWriteOrder(entry.getPreviousInWriteQueue(), entry.getNextInWriteQueue());
// add to tail
// entry和对头互指,和队尾互指,即添加到队尾
connectWriteOrder(head.getPreviousInWriteQueue(), entry);
connectWriteOrder(entry, head);
return true;
}
// 两个对象进行互指
static <K, V> void connectWriteOrder(ReferenceEntry<K, V> previous, ReferenceEntry<K, V> next) {
previous.setNextInWriteQueue(next);
next.setPreviousInWriteQueue(previous);
}
- preWriteCleanup
void preWriteCleanup(long now) {
runLockedCleanup(now);
}
void runLockedCleanup(long now) {
if (tryLock()) {
try {
drainReferenceQueues();
// 核心方法继续进入
expireEntries(now); // calls drainRecencyQueue
readCount.set(0);
} finally {
unlock();
}
}
}
void expireEntries(long now) {
drainRecencyQueue();
ReferenceEntry<K, V> e;
// 就两个队列不停的判断头节点是不是失效
while ((e = writeQueue.peek()) != null && map.isExpired(e, now)) {
if (!removeEntry(e, e.getHash(), RemovalCause.EXPIRED)) {
throw new AssertionError();
}
}
while ((e = accessQueue.peek()) != null && map.isExpired(e, now)) {
if (!removeEntry(e, e.getHash(), RemovalCause.EXPIRED)) {
throw new AssertionError();
}
}
}
- 监听者模式
void postWriteCleanup() {
// 核心方法继续进入
runUnlockedCleanup();
}
void runUnlockedCleanup() {
// locked cleanup may generate notifications we can send unlocked
if (!isHeldByCurrentThread()) {
// 核心方法继续进入
map.processPendingNotifications();
}
}
void processPendingNotifications() {
RemovalNotification<K, V> notification;
// 前面所有涉及notify的操作都会进到相应的queue中,然后在该主方法中进行回调
while ((notification = removalNotificationQueue.poll()) != null) {
try {
// 核心流程,只要实现removalListener,通过构造方法传进来,然后这里就会同步调用实现的回调方法
// PS第一遍看源码一度卡在这个位置,不知道这玩意儿就一个通知机制怎么就移除元素了
removalListener.onRemoval(notification);
} catch (Throwable e) {
logger.log(Level.WARNING, "Exception thrown by removal listener", e);
}
}
}