ThreadLocal算是为多线程解决并发问题提供了一种新的思路，为了更好地使用它，读其优秀的实现。
其构造方法是空的，那么直接看其set()方法
public void set(T value) {
Thread t = Thread.currentThread();
ThreadLocalMap map = getMap(t);
if (map != null)
map.set(this, value);
else
createMap(t, value);
} ThreadLocalMap getMap(Thread t) {
return t.threadLocals;
} void createMap(Thread t, T firstValue) {
t.threadLocals = new ThreadLocalMap(this, firstValue);
} 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;
setThreshold(INITIAL_CAPACITY);
}ThreadLocalMap是ThreadLocal的内部类，可以从构造看到，给ThreadLocalMap的table成员赋值为Entry数组，且长度默认为16，然后firstKey为传入的ThreadLocal实例，取其threadLocalHashCode跟16取余(通过与其长度-1与实现)，得到对应key存储在Entry数组中的下标i，然后赋值，并设为size为1，然后将threshold设为Entry数组长度的2/3倍。
实际上ThreadLocalMap类似于一个hashMap。每个键值对是一Entry形式存储。Entry是ThreadLocalMap的内部类
static class Entry extends WeakReference<ThreadLocal<?>> {
/** The value associated with this ThreadLocal. */
Object value;
Entry(ThreadLocal<?> k, Object v) {
super(k);
value = v;
}
}其元素的key是对于的ThreadLocal实例，且其实弱引用的形式。我们可以大致猜到为什么要用弱引用。
java引用分为强软弱虚，弱引用一旦可达性分析不到，那么在下次gc时，会被回收。这样我们就好猜到，这里使用弱引用的原因，为了避免把节点的生命周期跟线程绑定在一起，即只有线程销毁后，该节点才引用不可达。设为弱引用，那么只要某个ThreadLocal失去可达性，那么随着它的回收，某个对应的entry将会失效，这为ThreadLocalMap本身的垃圾清理提供了便利。
private void set(ThreadLocal<?> key, Object value) {
// We don't use a fast path as with get() because it is at
// least as common to use set() to create new entries as
// it is to replace existing ones, in which case, a fast
// path would fail more often than not.
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)]) {
ThreadLocal<?> k = e.get();
if (k == key) {
e.value = value;
return;
}
if (k == null) {
replaceStaleEntry(key, value, i);
return;
}
}
tab[i] = new Entry(key, value);
int sz = ++size;
if (!cleanSomeSlots(i, sz) && sz >= threshold)
rehash();
} private static int nextIndex(int i, int len) {
return ((i + 1 < len) ? i + 1 : 0);
} private final int threadLocalHashCode = nextHashCode();
private static int nextHashCode() {
return nextHashCode.getAndAdd(HASH_INCREMENT);
}这儿有个魔数HASH_INCREMENT = 0x61c88647，关于这个魔数的选取网上说法：与斐波那契散列有关，0x61c88647对应的十进制为1640531527。斐波那契散列的乘数可以用(long) ((1L << 31) * (Math.sqrt(5) - 1))可以得到2654435769，如果把这个值给转为带符号的int，则会得到-1640531527。
(我倒是发现个有趣的巧合，0x61c88647如果单位是秒的话，那么化成年约为51年，如果按照第一台计算机诞生1946年算，这是数字恰好是ThreadLocal上写的年份，1997。程序员的调皮~)
反正不管怎么样，通过理论与实践，当我们用0x61c88647作为魔数累加为每个ThreadLocal分配各自的ID也就是threadLocalHashCode再与2的幂取模，得到的结果分布很均匀。
我们再来看下replaceStaleEntry()方法
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;
}这个函数是核心清理函数，现将stateSlot位置的entry设为null，因此这个位置的entry已经无效，然后从stateSlot后位置开始向后遍历，如果是无效entry(即弱引用的ThreadLocal已经被回收)清理，即对应entry中的value置为null，将指向这个table[i]的entry置为null，如果不是，即k(ThreadLocal)不为null，那么将重新hash散列，如果重新散列的位置不为当前位置，那么将当前位置设为null，且从重新散列的位置开始找找到对应的table[i]为null的slot，插入。返回的i是stateSlot后的第一个空的slot的下标。
然后调用了cleanSomeSlots()，传入expungeStaleEntry的返回值跟len
private boolean cleanSomeSlots(int i, int n) {
boolean removed = false;
Entry[] tab = table;
int len = tab.length;
do {
//当前i对应的entry不可能为无效，要么指向的ThreadLocal没被回收，或者entry本身为空,
//所以从下一个位置开始判断
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;
}回到ThreadLocalMap的set方法中，直到找到空的slot，然后构造新的Entry键值对，插入，然后size自增，然后如果没有清理出新的位置，并且size大小大于负载容限threshold，于是调用rehash()，内部先清理，再判断是否需要扩容。看下rehash()函数。
private void rehash() {
expungeStaleEntries();
// Use lower threshold for doubling to avoid hysteresis
if (size >= threshold - threshold / 4)
resize();
} 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);
}
} 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;
}这个流程很清晰，扩容为原来的两倍。
set方法到这里就结束了了我们来简单看下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();
} private Entry getEntry(ThreadLocal<?> key) {
int i = key.threadLocalHashCode & (table.length - 1);
Entry e = table[i];
if (e != null && e.get() == key)
return e;
else
return getEntryAfterMiss(key, i, e);
} 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 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;
}在get中thread内的map为null时调用setInitialValue()初始化。
get()流程到这介绍完了。
我们再来看下remove方法
public void remove() {
ThreadLocalMap m = getMap(Thread.currentThread());
if (m != null)
m.remove(this);
}
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;
}
}
}找到相应位置，清理弱引用。
看到Thread内的成员threadLocals时还注意到inheritableThreadLocals成员
/* ThreadLocal values pertaining to this thread. This map is maintained
* by the ThreadLocal class. */
ThreadLocal.ThreadLocalMap threadLocals = null;
/*
* InheritableThreadLocal values pertaining to this thread. This map is
* maintained by the InheritableThreadLocal class.
*/
ThreadLocal.ThreadLocalMap inheritableThreadLocals = null; if (parent.inheritableThreadLocals != null)
this.inheritableThreadLocals =
ThreadLocal.createInheritedMap(parent.inheritableThreadLocals); static ThreadLocalMap createInheritedMap(ThreadLocalMap parentMap) {
return new ThreadLocalMap(parentMap);
}
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++;
}
}
}
} T childValue(T parentValue) {
throw new UnsupportedOperationException();
}