ThreadLocal 源码解析

ThreadLocal 为每个使用变得的线程保存一个副本，这样每个线程操作的就是自己的副本. 简述 ： 每个 Thread 都有一个 ThreadLocalMap 的变量,当在线程中调用 ThreadLocal.set() 的时候初始化。 ThreadLocalMap 存储键值对 key = ThreadLacal value = “用户设置的变量” 。 这里的key是一个 WeakRefrences 意味着key可能被GC回收。 对应的 get() 从Thread.ThreadLocalMap从取。这里可能存在几种情况 没有值，key被GC回收了 有值。具体看下面的代码逻辑

/**
    取到Thread  的threadLocals 如果 = null 初始化 将value put进去 ，
    已经初始化过了 ，直接put
  **/
 public void set(T value) {
        Thread t = Thread.currentThread();
            // Thread.threadLocals
        ThreadLocalMap map = getMap(t);
        if (map != null)
            map.set(this, value);  （1）
        else
            // 初始化 Thead.threadLocals 这里逻辑很简单 
            createMap(t, value);  （2）
    }
    
//-------------------------------------------------------
 //ThreadLocalmMap.set
 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;
            // 散列取得key映射到数据的位置 i 这里 相当于 
            // key.threadLocalHashCode % (len) 但用位运算效率更高
            int i = key.threadLocalHashCode & (len-1);
            // 当前i位置不为空 说明 hash 碰撞了 向后线性探索 遇到e = null 停止     
            for (Entry e = tab[i];
                 e != null;
                 e = tab[i = nextIndex(i, len)]) {
                ThreadLocal<?> k = e.get();
                if (k == key) {
                    //找到匹配的key  
                    e.value = value;
                    return;
                }
                if (k == null) {
                     // 这key = null key别GC回收了 
                    replaceStaleEntry(key, value, i);
                    return;
                }
            }
            // 位置上没有Entry 
            tab[i] = new Entry(key, value);
            int sz = ++size;
            if (!cleanSomeSlots(i, sz) && sz >= threshold)
                rehash();
        }
    
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一个简单的图 说明 set 过程

private void replaceStaleEntry(ThreadLocal<?> key, Object value,
                                       int staleSlot) {
            Entry[] tab = table;
            int len = tab.length;
            Entry e;

            //从 staleSlot 位置 向前搜索stale 节点位置  (连续空间因为这里遇到e = null 会停止 )
            int slotToExpunge = staleSlot;
            for (int i = prevIndex(staleSlot, len);
                 (e = tab[i]) != null;
                 i = prevIndex(i, len))
                if (e.get() == null)
                    slotToExpunge = i;

             // 向后搜索 
            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.
                // 找到对应的key,与 stale entity 交换
                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 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
            // 清除别的 stale entity
            if (slotToExpunge != staleSlot)
                cleanSomeSlots(expungeStaleEntry(slotToExpunge), len);
        }
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说明下 replaceStatleEntity 的流程

private boolean cleanSomeSlots(int i, int n) {
            boolean removed = false;
            Entry[] tab = table;
            int len = tab.length;
            do {
                // i 用永远不能是一个无效的位置
                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;
        }

//-----------------------------------------------------------------------
 private int expungeStaleEntry(int staleSlot) {
            Entry[] tab = table;
            int len = tab.length;

            // expunge entry at staleSlot 
            // 擦除staleSlot 位置的entry 
            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();
                // 从staleSlot 位置向后搜索 
                // key = null 擦除
                // key != null rehash 如果位置变了  向后搜索找到一个空位置放
                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;
        }
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remove

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) {
                    // 擦除key 相同的位置   
                    e.clear();
                    expungeStaleEntry(i);
                    return;
                }
            }
        }
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rehash

private void rehash() {
            expungeStaleEntries();

            // Use lower threshold for doubling to avoid hysteresis
            if (size >= threshold - threshold / 4)
                resize();
        }
/**
 从头到尾 清除一下无效Entity
**/
 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);
            }
        }

 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 {
                        // 重新hash 找到扩容后的table 位置 
                        int h = k.threadLocalHashCode & (newLen - 1);
                        while (newTab[h] != null)
                            h = nextIndex(h, newLen);
                        newTab[h] = e;
                        count++;
                    }
                }
            }

            setThreshold(newLen);
            size = count;
            table = newTab;
        }
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总结： 代码大概都能看懂，但是设计中为什么这么设计，为什么选择了这样的算法,我也不懂，可能是基础太差