Data structure | Concurrent HashMap
by Botao Xiao
JDK1.6/JDK1.7 ConcurrentHashMap是HashMap的线程安全实现，相比于Hashtable每次锁住整张表的情况，concurrentHashMap使用了分段锁（降低锁粒度），每次只锁住一个结点。 JDK1.8中已经摒弃了分段所，采取CAS替代了分段锁实现了无锁操作。
Node
和HashMap的内部结点一致，定义了Node结点。
static class Node<K,V> implements Map.Entry<K,V> {
final int hash;
final K key;
volatile V val;
volatile Node<K,V> next;
Node(int hash, K key, V val, Node<K,V> next) {
this.hash = hash;
this.key = key;
this.val = val;
this.next = next;
}
public final K getKey() { return key; }
public final V getValue() { return val; }
public final int hashCode() { return key.hashCode() ^ val.hashCode(); }
public final String toString(){ return key + "=" + val; }
public final V setValue(V value) {
throw new UnsupportedOperationException();
}
//比较两个节点是否相同
public final boolean equals(Object o) {
Object k, v, u; Map.Entry<?,?> e;
return ((o instanceof Map.Entry) &&
(k = (e = (Map.Entry<?,?>)o).getKey()) != null &&
(v = e.getValue()) != null &&
(k == key || k.equals(key)) &&
(v == (u = val) || v.equals(u)));
}
/**
* Virtualized support for map.get(); overridden in subclasses.
*/
//从链表中查找是否有哈希值和k均相同的结点
Node<K,V> find(int h, Object k) {
Node<K,V> e = this;
if (k != null) {
do {
K ek;
if (e.hash == h &&
((ek = e.key) == k || (ek != null && k.equals(ek))))
return e;
} while ((e = e.next) != null);
}
return null;
}
}
JDK 1.8 CAS实现无锁操作。
插入
- put() 调用了putVal方法
public V put(K key, V value) { return putVal(key, value, false); } - putVal()
final V putVal(K key, V value, boolean onlyIfAbsent) { if (key == null || value == null) throw new NullPointerException(); int hash = spread(key.hashCode()); //通过spread方法计算出hash值。 int binCount = 0; for (Node<K,V>[] tab = table;;) { //不断循环，和CAS配套使用 Node<K,V> f; int n, i, fh; if (tab == null || (n = tab.length) == 0) tab = initTable(); //第一次插入数据，创建新表。(参见initTable解析) //根据hash原子性的获取表中对应的Node结点 else if ((f = tabAt(tab, i = (n - 1) & hash)) == null) { //此时该结点为空，CAS，新建结点并存入表中 if (casTabAt(tab, i, null, new Node<K,V>(hash, key, value, null))) break; // no lock when adding to empty bin } else if ((fh = f.hash) == MOVED) //当前结点不为空，且rehash正在进行 //如果要扩容的新表存在，则将新值存入新表，并返回新表。 tab = helpTransfer(tab, f); else { V oldVal = null; //给要修改的结点上锁 synchronized (f) { //当前数据还没有被修改过，未出现脏读。不然进入下一次循环，重新进行。 if (tabAt(tab, i) == f) { //此处插入的代码和HashMap一致 if (fh >= 0) { binCount = 1; for (Node<K,V> e = f;; ++binCount) { K ek; if (e.hash == hash && ((ek = e.key) == key || (ek != null && key.equals(ek)))) {//如果存在所需结点，则更新值 oldVal = e.val; if (!onlyIfAbsent) e.val = value; break; } Node<K,V> pred = e; if ((e = e.next) == null) {//如果遍历到链表结尾仍没有找到，则添加新的对象。 pred.next = new Node<K,V>(hash, key, value, null); break; } } } else if (f instanceof TreeBin) {//如果冲突大于8，则转成树形结构，此时插入或更新结点至红黑树。 Node<K,V> p; binCount = 2; if ((p = ((TreeBin<K,V>)f).putTreeVal(hash, key, value)) != null) { oldVal = p.val; if (!onlyIfAbsent) p.val = value; } } } } if (binCount != 0) { if (binCount >= TREEIFY_THRESHOLD) //如果在插入元素后造成了链表长度大于8，则树化链表 treeifyBin(tab, i); if (oldVal != null) return oldVal; break; } } } addCount(1L, binCount);//check and rehash return null; } - initTable()
```Java
/**
- Initializes table, using the size recorded in sizeCtl. */ private final Node<K,V>[] initTable() { Node<K,V>[] tab; int sc; while ((tab = table) == null || tab.length == 0) { //当sizeCtl小于0，说明表正在创建或rehash，放弃当前线程的控制权 if ((sc = sizeCtl) < 0) Thread.yield(); // lost initialization race; just spin //其中第一个参数为需要改变的对象，第二个为偏移量(即之前求出来的valueOffset的值)，第三个参数为期待的值，第四个为更新后的值。->将sizeCtl设置为-1，开始创建表。 else if (U.compareAndSwapInt(this, SIZECTL, sc, -1)) { try { if ((tab = table) == null || tab.length == 0) { //理论上sc的值应该为-1，但是由于多线程操作，可能当前值被别的线程修改，如果更新后的值是大于0，则选用sc的值作为哈希表的大小。 int n = (sc > 0) ? sc : DEFAULT_CAPACITY; @SuppressWarnings(“unchecked”) Node<K,V>[] nt = (Node<K,V>[])new Node<?,?>[n]; table = tab = nt; sc = n - (n »> 2); //sc = 0.75 * sc } } finally { sizeCtl = sc; } break; } } return tab; } ```
- transfer() 扩容
//tab为当前的表地址，nextTab为扩容后的表 private final void transfer(Node<K,V>[] tab, Node<K,V>[] nextTab) { int n = tab.length, stride; //NCPU可以使用的CPU的数量，通过哈希表中的Node总量和CPU的数量来确定步长，即每个线程所允许处理的bucket的数量。 if ((stride = (NCPU > 1) ? (n >>> 3) / NCPU : n) < MIN_TRANSFER_STRIDE) stride = MIN_TRANSFER_STRIDE; // subdivide range if (nextTab == null) { // 新表为空，则创建一个新表 try { @SuppressWarnings("unchecked") Node<K,V>[] nt = (Node<K,V>[])new Node<?,?>[n << 1];//扩容至两倍 nextTab = nt; } catch (Throwable ex) { // try to cope with OOME sizeCtl = Integer.MAX_VALUE; return; } nextTable = nextTab; transferIndex = n;//rehash过程中正在转移的结点的指针，转移是从尾部向前开始的。 } int nextn = nextTab.length; ForwardingNode<K,V> fwd = new ForwardingNode<K,V>(nextTab); boolean advance = true; boolean finishing = false; // to ensure sweep before committing nextTab for (int i = 0, bound = 0;;) { Node<K,V> f; int fh; while (advance) { int nextIndex, nextBound; if (--i >= bound || finishing) advance = false; // transferIndex = 0表示table中所有数组元素都已经有其他线程负责扩容 else if ((nextIndex = transferIndex) <= 0) { i = -1; advance = false; } //更新transferIndex的值 //更新成功，则当前线程负责完成索引为(nextBound，nextIndex)之间的桶首节点扩容 else if (U.compareAndSwapInt (this, TRANSFERINDEX, nextIndex, nextBound = (nextIndex > stride ? nextIndex - stride : 0))) { bound = nextBound; i = nextIndex - 1; advance = false; } } if (i < 0 || i >= n || i + n >= nextn) { int sc; if (finishing) { nextTable = null; table = nextTab; sizeCtl = (n << 1) - (n >>> 1); //设置load factor为0.75 return; } if (U.compareAndSwapInt(this, SIZECTL, sc = sizeCtl, sc - 1)) { if ((sc - 2) != resizeStamp(n) << RESIZE_STAMP_SHIFT) return; finishing = advance = true; i = n; // recheck before commit } } else if ((f = tabAt(tab, i)) == null) //如果当前结点为空，添加一个转移结点，被再次被遍历到的时候将会读到hash值为MOVED advance = casTabAt(tab, i, null, fwd); else if ((fh = f.hash) == MOVED) //遍历到了一个已经被转移了的结点 advance = true; // already processed else { //添加分段锁机制，锁住bucket，开始扩容 synchronized (f) { if (tabAt(tab, i) == f) {//保证了在上锁之前值未被更改（宏观的原子性保证） Node<K,V> ln, hn; if (fh >= 0) {//拷贝链表的值 int runBit = fh & n; Node<K,V> lastRun = f; for (Node<K,V> p = f.next; p != null; p = p.next) { int b = p.hash & n; if (b != runBit) { runBit = b; lastRun = p; } } if (runBit == 0) { ln = lastRun; hn = null; } else { hn = lastRun; ln = null; } for (Node<K,V> p = f; p != lastRun; p = p.next) { int ph = p.hash; K pk = p.key; V pv = p.val; if ((ph & n) == 0) ln = new Node<K,V>(ph, pk, pv, ln); else hn = new Node<K,V>(ph, pk, pv, hn); } setTabAt(nextTab, i, ln); setTabAt(nextTab, i + n, hn); setTabAt(tab, i, fwd); advance = true; } else if (f instanceof TreeBin) {//拷贝树 TreeBin<K,V> t = (TreeBin<K,V>)f; TreeNode<K,V> lo = null, loTail = null; TreeNode<K,V> hi = null, hiTail = null; int lc = 0, hc = 0; for (Node<K,V> e = t.first; e != null; e = e.next) { int h = e.hash; TreeNode<K,V> p = new TreeNode<K,V> (h, e.key, e.val, null, null); if ((h & n) == 0) { if ((p.prev = loTail) == null) lo = p; else loTail.next = p; loTail = p; ++lc; } else { if ((p.prev = hiTail) == null) hi = p; else hiTail.next = p; hiTail = p; ++hc; } } ln = (lc <= UNTREEIFY_THRESHOLD) ? untreeify(lo) : (hc != 0) ? new TreeBin<K,V>(lo) : t; hn = (hc <= UNTREEIFY_THRESHOLD) ? untreeify(hi) : (lc != 0) ? new TreeBin<K,V>(hi) : t; setTabAt(nextTab, i, ln); setTabAt(nextTab, i + n, hn); setTabAt(tab, i, fwd); advance = true; } } } } } } - get() 哈希表的查询是O(1)级别的（没有哈希冲突的情况下）
public V get(Object key) { Node<K,V>[] tab; Node<K,V> e, p; int n, eh; K ek; int h = spread(key.hashCode()); if ((tab = table) != null && (n = tab.length) > 0 && (e = tabAt(tab, (n - 1) & h)) != null) {//通过CAS读取值，原子性 if ((eh = e.hash) == h) {//当前bucket是单一结点，直接返回。 if ((ek = e.key) == key || (ek != null && key.equals(ek))) return e.val; } else if (eh < 0)//说明当前元素是树形结构 return (p = e.find(h, key)) != null ? p.val : null; while ((e = e.next) != null) {//当前bucket是链表元素，通过遍历得到结果 if (e.hash == h && ((ek = e.key) == key || (ek != null && key.equals(ek)))) return e.val; } } return null; }
JDK1.6/1.7 分段锁实现
Segment
继承自ReentrantLock Hashtable之所以慢是因为在进行CRUD时通过synchronized锁住了整张表，我们要优化时应减小锁粒度，这样每次只对最小的范围进行上锁，允许了高并发的实现。
Segment<K,V> s0 = new Segment<K,V>(loadFactor, (int)(cap * loadFactor),(HashEntry<K,V>[])new HashEntry[cap]);
没有Java8中的Node结点，取代的是继承自ReentrantLock的分段锁。
final Segment<K,V> segmentFor(int hash) { //定位锁
return segments[(hash >>> segmentShift) & segmentMask];
}
- get() 它的get方法里将要使用的共享变量都定义成volatile.
- put() get()和put()方法相较JAVA8简单很多，均是获得Segment后上锁进行操作。
Reference
1.ConcurrentHashMap源码解读(put/transfer/get)-jdk8 2.JDK7下ConcurrentHashMap源码分析
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