一、样例及原理

// 成员变量ThreadLocal<Object> TL = new ThreadLocal<>();@Testpublic 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#createMapvoid 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#getEntryprivate 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#getEntryAfterMissprivate 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;}