ThreadLocal万字总结
https://blog.csdn.net/sinat_33921105/article/details/103295070
key的唯一性
一个线程中的多个ThreadLocal变量如何存储、如何保证唯一性？
每一个 ThreadLocal<T> tl = new ThreadLocal<>(); 创建出来都有一个不变且唯一的threadLocalHashCode，这个threadLocalHashCode在本线程局部变量的存储中作为唯一识别标志参与到key-value存储的key的计算，非常重要！
public class ThreadLocal<T> {
private final int threadLocalHashCode = nextHashCode();
private static AtomicInteger nextHashCode = new AtomicInteger();
private static final int HASH_INCREMENT = 0x61c88647;
private static int nextHashCode() {
return nextHashCode.getAndAdd(HASH_INCREMENT);
}
public ThreadLocal() {
}
}
线程独有
从源码的角度看，为什么ThreadLocal变量是线程独有，不同线程之间不会互相干扰，降低编程复杂性和从根源上避免线程安全问题。
ThreadLocal.set(value)取得是当前线程的ThreadLocalMap,如果存在设置值，如果不存在创建。
public void set(T value) {
Thread t = Thread.currentThread();
ThreadLocalMap map = getMap(t);
if (map != null)
map.set(this, value);
else
createMap(t, value);
}取当前线程的ThreadLocalMap:
ThreadLocalMap getMap(Thread t) {
return t.threadLocals;
}
当前线程中ThreadLocalMap的定义：
public class Thread implements Runnable {
ThreadLocal.ThreadLocalMap threadLocals = null;
}当前线程中ThreadLocalMap如果不存在创建：
void createMap(Thread t, T firstValue) {
t.threadLocals = new ThreadLocalMap(this, firstValue);
}set方法原理
以当前变量为key存储在当前Thread.ThreadLocalMap中的键值对。key的唯一性通过threadLocalHashCode与容量的计算来保证。
int i = firstKey.threadLocalHashCode & (INITIAL_CAPACITY - 1);
作为下标存储在数组中，这是threadLocalHashCode唯一性重要性的体现，与数组的容量取余操作保证下标不越界（如果容量不足会有其他方法进行扩容）
ThreadLocalMap(ThreadLocal<?> firstKey, Object firstValue) {
table = new Entry[INITIAL_CAPACITY];
int i = firstKey.threadLocalHashCode & (INITIAL_CAPACITY - 1);
table[i] = new Entry(firstKey, firstValue);
size = 1;
//阈值，容量超过threshold的3/4会扩容，threshold = INITIAL_CAPACITY * 2/3;
setThreshold(INITIAL_CAPACITY);
}ThreadLocalMap.set:当ThreadLocal变量中存在Map时会直接调用Map的set方法，
private void set(ThreadLocal<?> key, Object value) {
Entry[] tab = table;
int len = tab.length;
//获取新的下标（预估本变量本该有的下标）
int i = key.threadLocalHashCode & (len-1);
for (Entry e = tab[i];e != null; e = tab[i = nextIndex(i, len)]) {
ThreadLocal<?> k = e.get();
//如果已存在该变量的值，覆盖
if (k == key) {
e.value = value;
return;
}
//set方法会清除泄露的值
if (k == null) {
replaceStaleEntry(key, value, i);
return;
}
}
tab[i] = new Entry(key, value);
int sz = ++size;
//容量大于阈值，扩容需要重新散列存储
if (!cleanSomeSlots(i, sz) && sz >= threshold)
rehash();
}get方法原理
知道了set的存储机制，get就容易理解了，直接通过核心代码表示：
ThreadLocal.get方法：
public T get() {
Thread t = Thread.currentThread();
ThreadLocalMap map = getMap(t);
if (map != null) {
ThreadLocalMap.Entry e = map.getEntry(this);
if (e != null) {
@SuppressWarnings("unchecked")
T result = (T)e.value;
return result;
}
}
return setInitialValue();
}ThreadLocalMap.getEntry方法：
private Entry getEntry(ThreadLocal<?> key) {
//依然通过threadLocalHashCode计算获取下标
int i = key.threadLocalHashCode & (table.length - 1);
Entry e = table[i];
if (e != null && e.get() == key)
return e;
else//如果取不到值，通过其他方式获得
return getEntryAfterMiss(key, i, e);
}remove方法
建议大家使用最后都主动调用ThreadLocal.remove()方法，防止内存泄露，虽然ThreadLocal是弱引用，每次GC都会回收，set在ThreadLocal里的数据并没有被同时清除。详细了解可以看文章开头引用的文章。
Java的四种引用类型
强引用：我们常常 new 出来的对象就是强引用类型，只要强引用存在，垃圾回收器将永远不会回收被引用的对象，哪怕内存不足的时候
软引用：使用 SoftReference 修饰的对象被称为软引用，软引用指向的对象在内存要溢出的时候被回收
弱引用：使用 WeakReference 修饰的对象被称为弱引用，只要发生垃圾回收，若这个对象只被弱引用指向，那么就会被回收
虚引用：虚引用是最弱的引用，在 Java 中使用 PhantomReference 进行定义。虚引用中唯一的作用就是用队列接收对象即将死亡的通知
以下是源码其他方法上文未作出解释的，如果需要自行查看。
public class ThreadLocal<T> {
protected T initialValue() {
return null;
}
public static <S> ThreadLocal<S> withInitial(Supplier<? extends S> supplier) {
return new SuppliedThreadLocal<>(supplier);
}
public ThreadLocal() {
}
private T setInitialValue() {
T value = initialValue();
Thread t = Thread.currentThread();
ThreadLocalMap map = getMap(t);
if (map != null)
map.set(this, value);
else
createMap(t, value);
return value;
}
public void remove() {
ThreadLocalMap m = getMap(Thread.currentThread());
if (m != null)
m.remove(this);
}
static ThreadLocalMap createInheritedMap(ThreadLocalMap parentMap) {
return new ThreadLocalMap(parentMap);
}
T childValue(T parentValue) {
throw new UnsupportedOperationException();
}
static final class SuppliedThreadLocal<T> extends ThreadLocal<T> {
private final Supplier<? extends T> supplier;
SuppliedThreadLocal(Supplier<? extends T> supplier) {
this.supplier = Objects.requireNonNull(supplier);
}
@Override
protected T initialValue() {
return supplier.get();
}
}
static class ThreadLocalMap {
static class Entry extends WeakReference<ThreadLocal<?>> {
/** The value associated with this ThreadLocal. */
Object value;
Entry(ThreadLocal<?> k, Object v) {
super(k);
value = v;
}
}
private static final int INITIAL_CAPACITY = 16;
private Entry[] table;
private int size = 0;
private int threshold; // Default to 0
private void setThreshold(int len) {
threshold = len * 2 / 3;
}
private static int nextIndex(int i, int len) {
return ((i + 1 < len) ? i + 1 : 0);
}
private static int prevIndex(int i, int len) {
return ((i - 1 >= 0) ? i - 1 : len - 1);
}
private ThreadLocalMap(ThreadLocalMap parentMap) {
Entry[] parentTable = parentMap.table;
int len = parentTable.length;
setThreshold(len);
table = new Entry[len];
for (int j = 0; j < len; j++) {
Entry e = parentTable[j];
if (e != null) {
@SuppressWarnings("unchecked")
ThreadLocal<Object> key = (ThreadLocal<Object>) e.get();
if (key != null) {
Object value = key.childValue(e.value);
Entry c = new Entry(key, value);
int h = key.threadLocalHashCode & (len - 1);
while (table[h] != null)
h = nextIndex(h, len);
table[h] = c;
size++;
}
}
}
}
private Entry getEntryAfterMiss(ThreadLocal<?> key, int i, Entry e) {
Entry[] tab = table;
int len = tab.length;
while (e != null) {
ThreadLocal<?> k = e.get();
if (k == key)
return e;
if (k == null)
expungeStaleEntry(i);
else
i = nextIndex(i, len);
e = tab[i];
}
return null;
}
private void remove(ThreadLocal<?> key) {
Entry[] tab = table;
int len = tab.length;
int i = key.threadLocalHashCode & (len-1);
for (Entry e = tab[i];
e != null;
e = tab[i = nextIndex(i, len)]) {
if (e.get() == key) {
e.clear();
expungeStaleEntry(i);
return;
}
}
}
private void replaceStaleEntry(ThreadLocal<?> key, Object value,
int staleSlot) {
Entry[] tab = table;
int len = tab.length;
Entry e;
// Back up to check for prior stale entry in current run.
// We clean out whole runs at a time to avoid continual
// incremental rehashing due to garbage collector freeing
// up refs in bunches (i.e., whenever the collector runs).
int slotToExpunge = staleSlot;
for (int i = prevIndex(staleSlot, len);
(e = tab[i]) != null;
i = prevIndex(i, len))
if (e.get() == null)
slotToExpunge = i;
// Find either the key or trailing null slot of run, whichever
// occurs first
for (int i = nextIndex(staleSlot, len);
(e = tab[i]) != null;
i = nextIndex(i, len)) {
ThreadLocal<?> k = e.get();
// If we find key, then we need to swap it
// with the stale entry to maintain hash table order.
// The newly stale slot, or any other stale slot
// encountered above it, can then be sent to expungeStaleEntry
// to remove or rehash all of the other entries in run.
if (k == key) {
e.value = value;
tab[i] = tab[staleSlot];
tab[staleSlot] = e;
// Start expunge at preceding stale entry if it exists
if (slotToExpunge == staleSlot)
slotToExpunge = i;
cleanSomeSlots(expungeStaleEntry(slotToExpunge), len);
return;
}
// If we didn't find stale entry on backward scan, the
// first stale entry seen while scanning for key is the
// first still present in the run.
if (k == null && slotToExpunge == staleSlot)
slotToExpunge = i;
}
// If key not found, put new entry in stale slot
tab[staleSlot].value = null;
tab[staleSlot] = new Entry(key, value);
// If there are any other stale entries in run, expunge them
if (slotToExpunge != staleSlot)
cleanSomeSlots(expungeStaleEntry(slotToExpunge), len);
}
private int expungeStaleEntry(int staleSlot) {
Entry[] tab = table;
int len = tab.length;
// expunge entry at staleSlot
tab[staleSlot].value = null;
tab[staleSlot] = null;
size--;
// Rehash until we encounter null
Entry e;
int i;
for (i = nextIndex(staleSlot, len);
(e = tab[i]) != null;
i = nextIndex(i, len)) {
ThreadLocal<?> k = e.get();
if (k == null) {
e.value = null;
tab[i] = null;
size--;
} else {
int h = k.threadLocalHashCode & (len - 1);
if (h != i) {
tab[i] = null;
// Unlike Knuth 6.4 Algorithm R, we must scan until
// null because multiple entries could have been stale.
while (tab[h] != null)
h = nextIndex(h, len);
tab[h] = e;
}
}
}
return i;
}
private boolean cleanSomeSlots(int i, int n) {
boolean removed = false;
Entry[] tab = table;
int len = tab.length;
do {
i = nextIndex(i, len);
Entry e = tab[i];
if (e != null && e.get() == null) {
n = len;
removed = true;
i = expungeStaleEntry(i);
}
} while ( (n >>>= 1) != 0);
return removed;
}
private void rehash() {
expungeStaleEntries();
// Use lower threshold for doubling to avoid hysteresis
if (size >= threshold - threshold / 4)
resize();
}
private void resize() {
Entry[] oldTab = table;
int oldLen = oldTab.length;
int newLen = oldLen * 2;
Entry[] newTab = new Entry[newLen];
int count = 0;
for (int j = 0; j < oldLen; ++j) {
Entry e = oldTab[j];
if (e != null) {
ThreadLocal<?> k = e.get();
if (k == null) {
e.value = null; // Help the GC
} else {
int h = k.threadLocalHashCode & (newLen - 1);
while (newTab[h] != null)
h = nextIndex(h, newLen);
newTab[h] = e;
count++;
}
}
}
setThreshold(newLen);
size = count;
table = newTab;
}
private void expungeStaleEntries() {
Entry[] tab = table;
int len = tab.length;
for (int j = 0; j < len; j++) {
Entry e = tab[j];
if (e != null && e.get() == null)
expungeStaleEntry(j);
}
}
}
}
