ThreadLocal系列-ThreadLocalMap源码

1.ThreadLocalMap.Entry

key：指向key的是弱引用

value：强引用

public class ThreadLocal<T> {
    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);  //指向key的弱引用
                value = v; //指向value的是强引用
            }
        }
    }
}

2.hash计算

• nextHashCode是static的，说明是ThreadLocal类共用
• 在上一个ThreadLocal的hash的基础上增加HASH_INCREMENT

public class ThreadLocal<T> {
    //所有ThreadLocal类公用
    private static AtomicInteger nextHashCode = new AtomicInteger();

    private static final int HASH_INCREMENT = 0x61c88647;

    private final int threadLocalHashCode = nextHashCode();

    //每次在上一个hash的基础上增加HASH_INCREMENT
    private static int nextHashCode() {
        return nextHashCode.getAndAdd(HASH_INCREMENT);
    }
}

HASH_INCREMENT 的值是 0x61c88647，它是黄金分割比例乘以 2^31，这样可以使得步长增量更加分散，减小碰撞的概率，提高 ThreadLocal 的性能。

黄金分割率是一个数学和艺术上的常数，通常用希腊字母 φ（phi）表示，其近似值为1.618033988749895。

3.怎么处理hash冲突

ThreadLocalMap 使用线性探测法（linear probing）来处理哈希冲突。线性探测法是一种解决哈希冲突的简单方法，其中如果一个槽已经被占用，就线性地查找下一个可用的槽，直到找到一个可用槽为止。

Entry[] tab = table;

int len = tab.length;

int i = key.threadLocalHashCode & (len-1); //这里计算index跟HashMap一样

如果i被占用，则用nextIndex(i, len)计算下一个索引，看是否被占用

public class ThreadLocal<T> {
    static class ThreadLocalMap {
        /**
         * The table, resized as necessary.
         * table.length MUST always be a power of two.
         */
        private Entry[] table;

        /**
         * Increment i modulo len.
         * 每次i+1，如果i+1<len，则返回0
         */
        private static int nextIndex(int i, int len) {
            return ((i + 1 < len) ? i + 1 : 0);
        }

        /**
         * Set the value associated with key.
         *
         * @param key the thread local object
         * @param value the value to be 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;
            int i = key.threadLocalHashCode & (len-1); //这里计算index跟HashMap一样

            //下一个元素：i+1，如果i+1越界，怎为0
            for (Entry e = tab[i]; e != null; e = tab[i = nextIndex(i, len)]) {
                ThreadLocal<?> k = e.get(); //获取key

                if (k == key) { //key相等
                    e.value = value; //更新value的值
                    return;
                }

                if (k == null) {//说明这里放入的是无效数据，可以放入新数据
                    replaceStaleEntry(key, value, i);//放入数据，再做些无效数据清理工作
                    return;
                }

                //e不为null；k不为null；说明被正常的元素占用了，则到下一个索引
            }
            
            //tab[i]为null，退出了循环
            tab[i] = new Entry(key, value); //放入数组
            int sz = ++size;
            //如果没有移除数据，同时size大于threshold
            if (!cleanSomeSlots(i, sz) && sz >= threshold){
                rehash(); //扩容
            }
        }
    }
}

4.扩容

• 先清理所有的stale数据；
• 如果size大于等于threshold*3/4，进行扩容；

public class ThreadLocal<T> {
    static class ThreadLocalMap {
        private void rehash() {
            expungeStaleEntries(); //清理stale数据

            // Use lower threshold for doubling to avoid hysteresis
            //数据大小大于或者等于threshold的3/4后，进行扩容
            if (size >= threshold - threshold / 4)
                resize();
        }
    }
}

4.1.expungeStaleEntries-清理所有的stale数据

循环遍历执行expungeStaleEntry方法；

expungeStaleEntry方法：

(1)从table清除位于staleSlot的Entry；

(2)从staleSlot往后遍历table，直到table[i]为null

如果table[i]为stale元素，从table清除该元素；

如果table[i]不为stale元素，计算table[i]中的Entry本来应该放入的index，从那个index开始往后找Entry应该放入的位置A，将该Entry放入位置A；

expungeStaleEntries

public class ThreadLocal<T> {
    static class ThreadLocalMap {
        /**
         * 清除table里面的所有无效数据()
         */
        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){//e不为null且key为null
                    expungeStaleEntry(j);
                }
            }
        }

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

            // expunge entry at staleSlot
            tab[staleSlot].value = null; //value设为null
            tab[staleSlot] = null;  //entry设为null
            size--; //size减1

            // 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) {//如果元素不为null，但是key为null
                    e.value = null;
                    tab[i] = null;
                    size--;
                } else {
                    //不是stale元素的话，重新将这个元素放到合适的位置
                    int h = k.threadLocalHashCode & (len - 1); //计算index
                    if (h != i) {//本来应该放在h的位置，因为冲突的关系被放到了i
                        //h->>>>>>>>>>>i 看这中间有没有为null的
                        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) {//从h开始找e为null的index
                            h = nextIndex(h, len);
                        }
                        tab[h] = e; //把e放在合适的index
                    }
                }
            }
            return i; //返回的i是Entry为null的索引
        }
    }
}

4.2.ThreadLocalMap.resize-扩容

扩容：

新table的长度为老table长度的2倍；

遍历老table：

table[j]不为null：

key为null，设置value为null；

key不为null，根据新table的length计算index，将该元素放入合适的位置；

public class ThreadLocal<T> {
    static class ThreadLocalMap {
        private void resize() {
            Entry[] oldTab = table;
            int oldLen = oldTab.length;
            int newLen = oldLen * 2; //新len为老len的2倍
            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) {//stale元素
                        e.value = null; // Help the GC
                    } else {
                        int h = k.threadLocalHashCode & (newLen - 1); //重新计算index
                        while (newTab[h] != null){//找到该元素该放的位置
                            h = nextIndex(h, newLen);
                        }
                        newTab[h] = e;
                        count++;
                    }
                }
            }

            setThreshold(newLen); //更新threshold
            size = count;
            table = newTab;
        }
    }
}

5.ThreadLocalMap.replaceStaleEntry

public class ThreadLocal<T> {

    /**
     * ThreadLocalMap is a customized hash map suitable only for
     * maintaining thread local values. No operations are exported
     * outside of the ThreadLocal class. The class is package private to
     * allow declaration of fields in class Thread.  To help deal with
     * very large and long-lived usages, the hash table entries use
     * WeakReferences for keys. However, since reference queues are not
     * used, stale entries are guaranteed to be removed only when
     * the table starts running out of space.
     */
    static class ThreadLocalMap {

        /**
         * Decrement i modulo len.
         */
        private static int prevIndex(int i, int len) {
            return ((i - 1 >= 0) ? i - 1 : len - 1);
        }

        /**
         * Replace a stale entry encountered during a set operation
         * with an entry for the specified key.  The value passed in
         * the value parameter is stored in the entry, whether or not
         * an entry already exists for the specified key.
         *
         * As a side effect, this method expunges all stale entries in the
         * "run" containing the stale entry.  (A run is a sequence of entries
         * between two null slots.)
         *
         * @param  key the key
         * @param  value the value to be associated with key
         * @param  staleSlot index of the first stale entry encountered while
         *         searching for key.
         */
        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;
            //每次i-1，直到i-1<0时，i=len-1
            //跳出遍历：tab[i]为null
            //往前找stale元素，直到Entry为null
            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
            //往后，直到Entry为null
            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) { //往后找到个key相等的
                    e.value = value; //更新value

                    tab[i] = tab[staleSlot]; //那i的位置是stale元素
                    tab[staleSlot] = e; //把元素放到staleSlot位置

                    // 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); //放入元素

            // If there are any other stale entries in run, expunge them
            if (slotToExpunge != staleSlot){
                cleanSomeSlots(expungeStaleEntry(slotToExpunge), len);
            }
        }   
    }        
}

6.ThreadLocalMap.cleanSomeSlots

每次n=n/2来循环调用expungeStaleEntry清理stale数据

public class ThreadLocal<T> {
    static class ThreadLocalMap {
        private boolean cleanSomeSlots(int i, int n) {
            boolean removed = false;
            Entry[] tab = table;
            int len = tab.length;
            do {
                i = nextIndex(i, len);//从i往后找stale的元素
                Entry e = tab[i];
                if (e != null && e.get() == null) {//stale元素
                    n = len;
                    removed = true;
                    i = expungeStaleEntry(i);
                }
            } while ( (n >>>= 1) != 0); //从方法的注释来看，每次对n/2是为了在清除无用数据和速 
                                        //度之间做个平衡，这样既清理了无用数据，又不会因为清理 
                                        //太多无用数据，耽误了插入数据的时间
            return removed;
        }
    }
}

7.ThreadLocalMap.getEntry

public class ThreadLocal<T> {
    static class ThreadLocalMap {
        private Entry getEntry(ThreadLocal<?> key) {
            int i = key.threadLocalHashCode & (table.length - 1);
            Entry e = table[i];
            // Android-changed: Use refersTo()
            if (e != null && e.refersTo(key)){//i这个位置刚好放的Entry的key一致
                return e;
            } else {
                return getEntryAfterMiss(key, i, e);
            }
        }
    }
}

getEntryAfterMiss

往后遍历，直到Entry为null

• 如果key相等，返回Entry；
• 如果key为null，是stale元素，清理一下；
• 最终没找到，就返回null；

public class ThreadLocal<T> {
    static class ThreadLocalMap {
        private Entry getEntryAfterMiss(ThreadLocal<?> key, int i, Entry e) {
            Entry[] tab = table;
            int len = tab.length;

            while (e != null) {
                // Android-changed: Use refersTo()
                if (e.refersTo(key)){ //key相等
                    return e;
                }
                if (e.refersTo(null)){
                    expungeStaleEntry(i); //清理
                } else{
                    i = nextIndex(i, len); //下一个索引
                }
                e = tab[i];
            }
            return null;
        }
    }
}
    

8.ThreadLocalMap构造方法

初始化数组table，初始容量为16；

计算index，在table[index]处放入new Entry(key, value)；

更新threshold为10；

public class ThreadLocal<T> {
    
    static class ThreadLocalMap {
        /**
         * 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 initial capacity -- MUST be a power of two.
         */
        private static final int INITIAL_CAPACITY = 16;

        /**
         * The next size value at which to resize.
         */
        private int threshold; // Default to 0


        /**
         * Construct a new map initially containing (firstKey, firstValue).
         * ThreadLocalMaps are constructed lazily, so we only create
         * one when we have at least one entry to put in it.
         */
        ThreadLocalMap(ThreadLocal<?> firstKey, Object firstValue) {
            table = new Entry[INITIAL_CAPACITY]; //默认数组容量大小为16
            int i = firstKey.threadLocalHashCode & (INITIAL_CAPACITY - 1); //计算index
            table[i] = new Entry(firstKey, firstValue);//放入数组
            size = 1; //更新size
            setThreshold(INITIAL_CAPACITY); //设置threshold 16*2/3 = 10
        }

        /**
         * Set the resize threshold to maintain at worst a 2/3 load factor.
         */
        private void setThreshold(int len) {
            threshold = len * 2 / 3;
        }
    }
}