jdk1.2版本就有解决多线程并发的工具类，threadlocal类本质上以空间换时间，让每一个线程拥有一份共享变量的副本，然后这样就没有多线程并发的问题，每一个线程都各自修改自己变量副本，互不影响
ThreadLocal的属性
ThreadLocal属性非常简单就是nextHashCode, 还有一个魔数HASH_INCREMENT变量，它是每次增加的这个固定的 数，就得到下一个Hash值，下面代码官方注释说明相比于连续的递增的hashcode,每次增加 固定魔数，对于2的n次方幂的数组效率更优，至于为什么选取加这个魔数,这个跟斐波那契数列有关，感兴趣可以另外搜索相关资料研究
private final int threadLocalHashCode = nextHashCode();
/**
* The next hash code to be given out. Updated atomically. Starts at
* zero.
*/
private static AtomicInteger nextHashCode =
new AtomicInteger();
/**
* The difference between successively generated hash codes - turns
* implicit sequential thread-local IDs into near-optimally spread
* multiplicative hash values for power-of-two-sized tables.
*/
private static final int HASH_INCREMENT = 0x61c88647;
ThreadLocal的set方法
get set方法是了解threadLocal的核心原理的方法，
首先获取当前线程，
获取Thread的内部对象ThreadLocalMap的变量，
如果ThreadLocalMap变量为空,则创建ThreadLocalMap对象， 注意这里的参数this是threadLocal的事例
如果ThreadLocalMap变量不为空，则直接设置值
public void set(T value) {
//获取当前线程
Thread t = Thread.currentThread();
//获取ThreadLocalMap对象
ThreadLocalMap map = getMap(t);
if (map != null) {
//设置值
map.set(this, value);
} else {
//创建
createMap(t, value);
}
}
//创建ThreadLocalMap对象
void createMap(Thread t, T firstValue) {
t.threadLocals = new ThreadLocalMap(this, firstValue);
}
ThreadLocalMap类成员变量
从下面可以看到ThreadLocalMap的数组的对象是Entry对象,它是继承了WeakReference这个，初始化Entry对象时，调用了父类的构造函数,也就是Entry对象中k是弱引用,而上面创建该对象时，传入的参数就是ThreadLocal对象的this指针，所以放入ThreadLocalMap中Entry 对象中ThreadLocal时弱引用，
static class ThreadLocalMap {
/**
* The entries in this hash map extend WeakReference, using
* its main ref field as the key (which is always a
* ThreadLocal object). Note that null keys (i.e. entry.get()
* == null) mean that the key is no longer referenced, so the
* entry can be expunged from table. Such entries are referred to
* as "stale entries" in the code that follows.
*/
static class Entry extends WeakReference<ThreadLocal<?>> {
/** The value associated with this ThreadLocal. */
Object value;
Entry(ThreadLocal<?> k, Object v) {
super(k);
value = v;
}
}
/**
* The initial capacity -- MUST be a power of two.
*/
private static final int INITIAL_CAPACITY = 16;
/**
* The table, resized as necessary.
* table.length MUST always be a power of two.
*/
private Entry[] table;
/**
* The number of entries in the table.
*/
private int size = 0;
/**
* The next size value at which to resize.
*/
private int threshold; // Default to 0
Thread和ThreadLocalMap以及ThreadLocal之间的关系如下:
从上图可以看出ThreadLocalMap中key是ThreadLocal对象，value就是保存的变量值，这两个构成一个Entry对象,设置到ThreadLocalMap中，解决冲突方法是开发地址法，即往右面偏移，而HashMap则是拉链法,这只是两种其中一点不同,其他的可以继续往下看。
首先去key的threadLocalHashCode值与(len-1)做&运算，然后得到具体落到哪一个桶上, 如果产生碰撞，则通过开放地址法，index加1往后偏移一个桶地址，如果找到key等于k, 则将新value替换旧值后返回。
如果查询过程中key为null，此时会调用replaceStaleEntry替换老的Entry.
如果i的位置为空，则创建一个新的Entry，放到i的位置,size加1.
调用cleanSomeSlots清除[i,size)区间一些槽位, 如果数组的长度大于threshold(即数组的2/3),则调用rehas进行扩容.
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();
}
接下来看下replaceStaleEntry是如果替换老的Entry。
首先，以上面hash地址&(len-1)得出的位置i开始, 从后往前找，找到Entry不为空，但是Entry的key为空的（这样就是会造成内存泄漏的数据）,slotToExpunge标记一个index，这样[slotToExpunge,i]这个就是需要清理的索引区间。
从staleSlot的位置后面一个位置，开始从前往后遍历，如果找到这个key,我们可以将这个Entry交换到staleSlot的位置
如果脏数据的开始位置和slotToExpunge的索位置相等,则slotToExpunge索引赋值为从上一步从前往后找到第一个key相等的位置的索引.然后调用expungeStaleEntry从staleSlot开始清除脏数据,最后调用cleanSomeSlots启发式扫描清除某些槽位。
如果没有清理的槽位，并且size大于threshod(即size的2/3).则进行rehash进行扫描全部数组进行清理过期数据，如果还是threshod的3/4,则通过resize进行扩容。
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) {
//交换位置
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);
}
staleSlot是已知key为空的Entry的索引, 从staleSlot开始从前往后搜索
如果key为空，则设置清设置Entry的value为null。并且设置对应位置为空
如果key不为空，并且i位置和hash&(len-1)不相等，说明这是通过开发地址法放进来的元素，则通过rehash，循环直到找一个hash&(len-1)的位置为空，并把它放到这个位置(这里这这一步主要是解决减少hash碰撞产生,使得查询时间复杂度为 O(1)).
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;
}
这里就是搜素索引i(即expungeStaleEntry函数返回索引的位置,即staleSlot位置后第一个Entry为空的位置，即不是脏数据的索引),n就是tab的length，从i开始往后遍历，如果Entry不为空，但是key为空,保存len,赋值removed变量为true,然后调用expungeStaleEntry再次 清除脏数据,然后将n缩减一半的长度,重新探索，直至0为止。
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;
}
扫描全部数据进行清理过期数据，
size 大于 threshod的3/4，则调用resize进行扩容。
private void rehash() {
expungeStaleEntries();
// Use lower threshold for doubling to avoid hysteresis
if (size >= threshold - threshold / 4)
resize();
}
ThreadLocal resize进行扩容
ThreadLocal的扩容机制,是将申请原先长度乘以2的数组,然后重新计算hash值，然后放入新的数组中即可，然后重新计算扩容阈值。
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;
}
ThreadLocal get进行获取值
首先获取Thread的threadLocalMap对象,然后通过getEntry方法获Entry对象，
然后获取Entry不为空，则直接返回
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();
}
首先通过key的threadLocalHashCode&(len-1),定位到对应的桶，
如果key相等，说明已经找到该元素，直接返回
如果key不等，则开发地址法，调用getEntryAfterMiss继续往查找。
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);
}
继续从i的位置往后搜索直到entry为空时停止
如果遇到k为空null时，则expungeStaleEntry进行清理过期数据
如果循环结束还咩有找到，则直接返回null结束
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;
}
ThreadLocal的remove删除值
首先还是通过threadLocalHashCode&(len-1)定位对应的数组索引i,
从i开始从前往后搜索，知道key相等，然后删除Entry，然后执行expungeStaleEntry进行 一次过期数据的清理结束
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;
}
}
}
总结
今天主要是对ThreadLocal的set get remove等重要方法进行一个详细的分析，也对ThreadLocal的解决Hash冲突的方法，key的弱引用，扩容、探测清理和启发式清理过期元素有了一个清理的认识。
作者：xjz1842
链接：https://juejin.cn/post/7005091348118241288
来源：掘金
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