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java多线程之threadlocal的原理分析

2021-09-07  本文已影响0人  程序花生

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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