一、样例及原理
// 成员变量
ThreadLocal<Object> TL = new ThreadLocal<>();
@Test
public void testTL(){
TL.set(new Object());
TL.get();
}
ThreadLocal以一种空间换工夫的思维(变量在不同的线程开拓正本),解决并发问题。
线程持有名为threadLocals的援用,指向一个ThreadLocalMap
- ThreadLocalMap的实质是一个Entry对象数组
ThreadLocalMap解决hash抵触的形式与HashMap的形式不同(链、树),ThreadLocalMap它会从落点桶地位程序查找。
如:hash取余计算出落点桶是5,但地位5曾经有其它entry,那么会尝试放入桶6……
- key是ThreadLocal对象自身,由Entry对象以弱援用的形式指向key
采纳弱援用的形式,是为了帮忙回收,防内存溢出(源码中有扫描逻辑)。
如果持有ThreadLocal的对象被回收了(样例中的成员变量不存在了),意味着指向ThreadLocalMap的key的强援用不存在了,那么弱援用被GC扫描到时也会被回收。
- value则是要存储的对象
二、set()
public void set(T value) {
Thread t = Thread.currentThread();
// 获取线程的threadLocals变量
ThreadLocalMap map = getMap(t);
if (map != null)
// == 2.找到Entry数组中的entry,并赋值
map.set(this, value);
else
// == 1.创立ThreadLocalMap,并赋值
// - 线程有个threadLocals变量,这个变量指向Entry数组(一个Thread关联的多个ThreadLocal对象,默认16);
// - Entry对象是弱援用的
createMap(t, value);
}
1.创立ThreadLocalMap
java.lang.ThreadLocal#createMap
void createMap(Thread t, T firstValue) {
// ## 调用ThreadLocalMap的构造函数,将以后的threadLocal作为key
// 最终赋值给线程的threadLocals变量
t.threadLocals = new ThreadLocalMap(this, firstValue);
}
// ThreadLocalMap的构造函数
ThreadLocalMap(ThreadLocal<?> firstKey, Object firstValue) {
table = new Entry[INITIAL_CAPACITY];
int i = firstKey.threadLocalHashCode & (INITIAL_CAPACITY - 1);
// 构建弱援用的数组
table[i] = new Entry(firstKey, firstValue);
size = 1;
// 扩大因子,size * 2/3
setThreshold(INITIAL_CAPACITY);
}
要害类、属性
# Thread类
ThreadLocal.ThreadLocalMap threadLocals = null;
# ThreadLocal类
static class ThreadLocalMap {
private Entry[] table;
// table的size,也就是本线程对应的ThreadLocal数量
private int size = 0;
// 弱援用:一旦发现了只具备弱援用的对象,不论以后内存空间足够与否,都会回收它的内存
// 如果不应用弱援用,那么当持有value的强援用开释掉后,当线程没有回收开释时,
// threadLocalMap会始终持有ThreadLocal以及value的强利用,导致value不可能被回收,从而造成内存透露。
static class Entry extends WeakReference<ThreadLocal<?>> {
Object value;
Entry(ThreadLocal<?> k, Object v) {
super(k);
value = v;
}
}
}
2.ThreadLocalMap#set
private void set(ThreadLocal<?> key, Object value) {
Entry[] tab = table;
int len = tab.length;
// 依据hash值和len找落点
int i = key.threadLocalHashCode & (len-1);
// 线性查找
for (Entry e = tab[i];
e != null;
// 循环中做线性查找,落点i在数组中挪动(如果曾经是数组的最初一个地位,会从地位0持续查找)
e = tab[i = nextIndex(i, len)]) {
// 获取以后地位的key->ThreadLocal
ThreadLocal<?> k = e.get();
// == 1.1、Entry数组中找到了对应的ThreadLocal,赋值替换
if (k == key) {
e.value = value;
return;
}
// ## 2、原地位的entry为空(stale-生效),替换
if (k == null) {
replaceStaleEntry(key, value, i);
return;
}
}
// == 1.2、Entry数组中没找到,新建Entry,放入空槽i(经验下面的循环后,i为最近的空位)地位
tab[i] = new Entry(key, value);
int sz = ++size;
// -- a、满足扩容条件(条件:无奈清理 && 达到阈值),做扩容操作
if (!cleanSomeSlots(i, sz) && sz >= threshold)
// -- b、扩容
rehash();
}
a、桶清理
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];
// entry不为空,但entry的key为空(## 弱援用被回收,前提条件是持有ThreadLocal的对象被回收,见下图)
if (e != null && e.get() == null) {
n = len;
// 执行清理操作,返回值设置为true
removed = true;
// == 清理有效entry
i = expungeStaleEntry(i);
}
}
// 通过size(理论的Entry对象个数,也就是线程持有的ThreadLocal个数)二进制右移来确定循环次数
// 举例:2->0循环2次;8->0循环4次
while ( (n >>>= 1) != 0);
return removed;
}
看下理论的清理办法
private int expungeStaleEntry(int staleSlot) {
Entry[] tab = table;
int len = tab.length;
// 分明以后的有效节点
tab[staleSlot].value = null;
tab[staleSlot] = null;
size--;
Entry e;
int i;
for (i = nextIndex(staleSlot, len);
(e = tab[i]) != null;
i = nextIndex(i, len)) {
ThreadLocal<?> k = e.get();
// -- 帮忙清理其它有效节点
if (k == null) {
e.value = null;
tab[i] = null;
size--;
}
// -- 帮忙k找到理论的桶
// 原来在i地位,但当年抉择i地位是无奈之举——hash抵触,理论是h地位;
// 当初有机会把它落在该落的h地位,i地位清空
else {
int h = k.threadLocalHashCode & (len - 1);
if (h != i) {
tab[i] = null;
// 好吧,理论落点h也被占用了,只能持续找到新的h位
while (tab[h] != null)
h = nextIndex(h, len);
tab[h] = e;
}
}
}
return i;
}
b、rehash()
private void rehash() {
// 理论的清理办法,曾经剖析过
expungeStaleEntries();
// Use lower threshold for doubling to avoid hysteresis
if (size >= threshold - threshold / 4)
// 扩容
resize();
}
## 扩容 && 旧桶对象迁新桶
private void resize() {
Entry[] oldTab = table;
int oldLen = oldTab.length;
// 2倍扩容
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 {
// 计算落点
int h = k.threadLocalHashCode & (newLen - 1);
// hash抵触,找最近空位
while (newTab[h] != null)
h = nextIndex(h, newLen);
newTab[h] = e;
count++;
}
}
}
setThreshold(newLen);
size = count;
table = newTab;
}
原地位的entry为空(stale-生效),替换
private void replaceStaleEntry(ThreadLocal<?> key, Object value,
int staleSlot) {
Entry[] tab = table;
int len = tab.length;
Entry e;
// 往左查找一波(与其它方向相同,按我的了解作更全面的清理)
int slotToExpunge = staleSlot;
for (int i = prevIndex(staleSlot, len);
(e = tab[i]) != null;
i = prevIndex(i, len))
if (e.get() == null)
slotToExpunge = i;
// 其它不剖析了(懒):看上去都是调用后面的各种已剖析过的办法,总之就是确保扫描的全面
for (int i = nextIndex(staleSlot, len);
(e = tab[i]) != null;
i = nextIndex(i, len)) {
ThreadLocal<?> k = e.get();
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 (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);
}
三、get()
public T get() {
Thread t = Thread.currentThread();
ThreadLocalMap map = getMap(t);
if (map != null) {
// == 获取entry节点。从set的逻辑推断——必定有在Entry环上查找的逻辑
ThreadLocalMap.Entry e = map.getEntry(this);
if (e != null) {
@SuppressWarnings("unchecked")
T result = (T)e.value;
return result;
}
}
return setInitialValue();
}
java.lang.ThreadLocal.ThreadLocalMap#getEntry
private Entry getEntry(ThreadLocal<?> key) {
int i = key.threadLocalHashCode & (table.length - 1);
Entry e = table[i];
// -- 找到间接返回
if (e != null && e.get() == key)
return e;
// -- 找不到,作线性查找
else
return getEntryAfterMiss(key, i, e);
}
java.lang.ThreadLocal.ThreadLocalMap#getEntryAfterMiss
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;
// 帮忙清理
if (k == null)
expungeStaleEntry(i);
// 线性查找
else
i = nextIndex(i, len);
e = tab[i];
}
return null;
}
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