ThreadLocalMap是java.lang.ThreadLocal的静态内部类。ThreadLocalMap表面看起来至少实现类似hashmap的功能，但是仔细分析它却有下面的属性。
一般是对value进行弱引用的，而不是key.
也许有一天我们在自己的程序中需要类似ThreadLocalMap的功能。
以下是从
其中Key对应JDK中的ThreadLocal
class Key {
final int hashCode = nextHashCode();
static AtomicInteger nextHashCode =
new AtomicInteger();
static final int HASH_INCREMENT = 0x61c88647;
static int nextHashCode() {
return nextHashCode.getAndAdd(HASH_INCREMENT);
}
}
class ThreadLocalMap {
static class Entry extends WeakReference<Key> {
Object value;
Entry(Key k, Object v) {
super(k);
value = v;
}
}
//初始值，必须是2的n次方
private static final int INITIAL_CAPACITY = 16;
/**
* The table, resized as necessary.
* table.length MUST always be a power of two.
*/
private Entry[] table;
private int size = 0;
/**
* The next size value at which to resize.
*/
private int threshold; // Default to 0
/**
* Set the resize threshold to maintain at worst a 2/3 load factor.
*/
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);
}
/**
* Construct a new map initially containing (firstKey, firstValue).
* ThreadLocalMaps are constructed lazily, so we only create
* one when we have at least one entry to put in it.
*/
ThreadLocalMap(Key firstKey, Object firstValue) {
table = new Entry[INITIAL_CAPACITY];
int i = firstKey.hashCode & (INITIAL_CAPACITY - 1);
table
size = 1;
setThreshold(INITIAL_CAPACITY);
}
private Entry getEntry(Key key) {
int i = key.hashCode & (table.length - 1);
Entry e = table[i]
if (e != null && e.get() == key)
return e;
else
return getEntryAfterMiss(key, i, e);
}
private Entry getEntryAfterMiss(Key key, int i, Entry e) {
Entry[] tab = table[i];
int len = tab.length;
while (e != null) {
Key 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 set(Key key, Object value) {
Entry[] tab = table;
int len = tab.length;
int i = key.hashCode & (len-1);
for (Entry e = tab[i]
Key k = e.get();
if (k == key) {
e.value = value;
return;
}
if (k == null) {
replaceStaleEntry(key, value, i);
return;
}
}
tab
int sz = ++size;
if (!cleanSomeSlots(i, sz) && sz >= threshold)
rehash();
}
private void remove(Key key) {
Entry[] tab = table;
int len = tab.length;
int i = key.hashCode & (len-1);
for (Entry e = tab
e != null;
e = tab[i = nextIndex(i, len)]) {
if (e.get() == key) {
e.clear();
expungeStaleEntry(i);
return;
}
}
}
private void replaceStaleEntry(Key key, Object value,
int staleSlot) {
Entry[] tab = table;
int len = tab.length;
Entry e;
int slotToExpunge = staleSlot;
for (int i = prevIndex(staleSlot, len);
(e = tab
i = prevIndex(i, len))
if (e.get() == null)
slotToExpunge = i;
for (int i = nextIndex(staleSlot, len);
(e = tab
i = nextIndex(i, len)) {
Key k = e.get();
if (k == key) {
e.value = value;
tab
tab[staleSlot] = e;
// Start expunge at preceding stale entry if it exists
if (slotToExpunge == staleSlot)
slotToExpunge = i;
cleanSomeSlots(expungeStaleEntry(slotToExpunge), len);
return;
}
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);
}
/**擦除staleSlot的Entry。
*调整所有不在哈希映射位置的value的位置，让它尽量在哈希映射的位置
*/
private int expungeStaleEntry(int staleSlot) {
Entry[] tab = table;
int len = tab.length;
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 = nextIndex(i, len)) {
Key k = e.get();
if (k == null) {
e.value = null;
tab
size--;
} else {
int h = k.hashCode & (len - 1);
if (h != i) {
tab
// 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
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) {
Key k = e.get();
if (k == null) {
e.value = null; // Help the GC
} else {
int h = k.hashCode & (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);
}
}
}