多线程工具ThreadLocal

一、样例及原理

// 成员变量 ThreadLocal TL = new ThreadLocal<>(); @Test public void testTL(){ TL.set(new Object()); TL.get(); }
【多线程工具ThreadLocal】多线程工具ThreadLocal
文章图片

ThreadLocal以一种空间换时间的思想(变量在不同的线程开辟副本),解决并发问题。
线程持有名为threadLocals的引用,指向一个ThreadLocalMap
  • ThreadLocalMap的本质是一个Entry对象数组
ThreadLocalMap解决hash冲突的方式与HashMap的方式不同(链、树),ThreadLocalMap它会从落点桶位置顺序查找。
如:hash取余计算出落点桶是5,但位置5已经有其它entry,那么会尝试放入桶6……
  • key是ThreadLocal对象本身,由Entry对象以弱引用的方式指向key
采用弱引用的方式,是为了帮助回收,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的强引用不存在了,那么弱引用被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.创建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对象是弱引用的 createMap(t, value); }

1.创建ThreadLocalMap
java.lang.ThreadLocal#createMap void createMap(Thread t, T firstValue) { // ## 调用ThreadLocalMap的构造函数,将当前的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); // 构建弱引用的数组 table[i] = new Entry(firstKey, firstValue); size = 1; // 扩展因子,size * 2/3 setThreshold(INITIAL_CAPACITY); }

关键类、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; // 弱引用:一旦发现了只具有弱引用的对象,不管当前内存空间足够与否,都会回收它的内存// 如果不使用弱引用,那么当持有value的强引用释放掉后,当线程没有回收释放时, // threadLocalMap会一直持有ThreadLocal以及value的强应用,导致value不能够被回收,从而造成内存泄漏。 static class Entry extends WeakReference> { Object value; Entry(ThreadLocal k, Object v) { super(k); value = https://www.it610.com/article/v; } } }

2.ThreadLocalMap#set
private void set(ThreadLocal key, Object value) { Entry[] tab = table; int len = tab.length; // 根据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在数组中移动(如果已经是数组的最后一个位置,会从位置0继续查找) e = tab[i = nextIndex(i, len)]) {// 获取当前位置的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 = https://www.it610.com/article/value; return; }// ## 2、原位置的entry为空(stale-失效),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(经历上面的循环后,i为最近的空位)位置 tab[i] = new Entry(key, value); int sz = ++size; // -- a、满足扩容条件(条件:无法清理 && 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(## 弱引用被回收,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; // == 清理无效entry i = expungeStaleEntry(i); } } // 通过size(实际的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; }

看下实际的清理方法
private int expungeStaleEntry(int staleSlot) { Entry[] tab = table; int len = tab.length; // 清楚当前的无效节点 tab[staleSlot].value = https://www.it610.com/article/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(); // -- 帮助清理其它无效节点 if (k == null) { e.value = https://www.it610.com/article/null; tab[i] = null; size--; } // -- 帮助k找到实际的桶 // 原来在i位置,但当年选择i位置是无奈之举——hash冲突,实际是h位置; // 现在有机会把它落在该落的h位置,i位置清空 else { int h = k.threadLocalHashCode & (len - 1); if (h != i) { tab[i] = null; // 好吧,实际落点h也被占用了,只能继续找到新的h位 while (tab[h] != null) h = nextIndex(h, len); tab[h] = e; } } } return i; }

b、rehash()
private void rehash() { // 实际的清理方法,已经分析过 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 = https://www.it610.com/article/null; // Help the GC } else { // 计算落点 int h = k.threadLocalHashCode & (newLen - 1); // hash冲突,找最近空位 while (newTab[h] != null) h = nextIndex(h, newLen); newTab[h] = e; count++; } } }setThreshold(newLen); size = count; table = newTab; }

原位置的entry为空(stale-失效),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(与其它方向相反,按我的理解作更全面的清理) int slotToExpunge = staleSlot; for (int i = prevIndex(staleSlot, len); (e = tab[i]) != null; i = prevIndex(i, len)) if (e.get() == null) slotToExpunge = i; // 其它不分析了(懒):看上去都是调用前面的各种已分析过的方法,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 = https://www.it610.com/article/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——肯定有在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]; // -- 找到直接返回 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; // 帮助清理 if (k == null) expungeStaleEntry(i); // 线性查找 else i = nextIndex(i, len); e = tab[i]; } return null; }

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