ConcurrentHashMap是1.5引入的用于高并发状况下的检索和更新。本文是基于jdk8的代码进行分析的,从put方法入手,来看下该结构是如何实现的。java
final V putVal(K key, V value, boolean onlyIfAbsent) { if (key == null || value == null) throw new NullPointerException(); //计算hash int hash = spread(key.hashCode()); //默认就是0,表明链表的长度,若是key不碰撞都是0, int binCount = 0; //常见的自旋结构 for (Node<K,V>[] tab = table;;) { Node<K,V> f; int n, i, fh; //延迟加载tab,用来放Node的数组 if (tab == null || (n = tab.length) == 0) tab = initTable(); //i的位置没有值 else if ((f = tabAt(tab, i = (n - 1) & hash)) == null) { //经过cas将i位置设定为新node if (casTabAt(tab, i, null, new Node<K,V>(hash, key, value, null))) break; // no lock when adding to empty bin } //正在扩容的移动阶段 else if ((fh = f.hash) == MOVED) tab = helpTransfer(tab, f); //i位置已经有值了 else { V oldVal = null; synchronized (f) { if (tabAt(tab, i) == f) { if (fh >= 0) { binCount = 1; for (Node<K,V> e = f;; ++binCount) { K ek; //hash和key都相同才认为是相同的key,而后根据onlyIfAbsent的值来决定是否覆盖值 if (e.hash == hash && ((ek = e.key) == key || (ek != null && key.equals(ek)))) { oldVal = e.val; if (!onlyIfAbsent) e.val = value; break; } Node<K,V> pred = e; //链表尾部添加新node if ((e = e.next) == null) { pred.next = new Node<K,V>(hash, key, value, null); break; } } } //红黑树结构 else if (f instanceof TreeBin) { Node<K,V> p; binCount = 2; //将k,v添加到树中 if ((p = ((TreeBin<K,V>)f).putTreeVal(hash, key, value)) != null) { oldVal = p.val; if (!onlyIfAbsent) p.val = value; } } } } if (binCount != 0) { //链表长度大于等于8,就将其转为红黑树结构 if (binCount >= TREEIFY_THRESHOLD) treeifyBin(tab, i); if (oldVal != null) return oldVal; break; } } } //计数及扩容的代码 addCount(1L, binCount); return null; }
private final Node<K,V>[] initTable() { Node<K,V>[] tab; int sc; while ((tab = table) == null || tab.length == 0) { //sizeCtl 是tab扩容和初始化的控制器,默认是0,能够进行操做,负的话就表明正在初始化或扩容,由于能够多个线程扩容,-N 就表明n个线程正在扩容 if ((sc = sizeCtl) < 0) Thread.yield(); // lost initialization race; just spin //CAS 设置 sizectl 设为-1,失败会跳过 else if (U.compareAndSwapInt(this, SIZECTL, sc, -1)) { try { if ((tab = table) == null || tab.length == 0) { int n = (sc > 0) ? sc : DEFAULT_CAPACITY; @SuppressWarnings("unchecked") Node<K,V>[] nt = (Node<K,V>[])new Node<?,?>[n]; table = tab = nt; //sc 为tab长度的 3/4 sc = n - (n >>> 2); } } finally { //此时sizeCtl 做为长度的3/4 ,后面做为是否须要扩容的一个判断条件 sizeCtl = sc; } break; } } return tab; }
final Node<K,V>[] helpTransfer(Node<K,V>[] tab, Node<K,V> f) { Node<K,V>[] nextTab; int sc; //ForwardingNode 是一个空的节点,没有val,是当transfer时插入到头那作标识的,因此这里表明f 正处于transfer 状态。 if (tab != null && (f instanceof ForwardingNode) && (nextTab = ((ForwardingNode<K,V>)f).nextTable) != null) { //根据tab的长度生成个印记戳 int rs = resizeStamp(tab.length); while (nextTab == nextTable && table == tab && (sc = sizeCtl) < 0) { if ((sc >>> RESIZE_STAMP_SHIFT) != rs || sc == rs + 1 || sc == rs + MAX_RESIZERS || transferIndex <= 0) break; if (U.compareAndSwapInt(this, SIZECTL, sc, sc + 1)) { //具体转移的代码,transfer的入口主要是在addCount里面,该方法是协助transfer的入口。 transfer(tab, nextTab); break; } } return nextTab; } return table; }
private final void addCount(long x, int check) { CounterCell[] as; long b, s; if ((as = counterCells) != null || //计数器增长x,s为最终长度 !U.compareAndSwapLong(this, BASECOUNT, b = baseCount, s = b + x)) { CounterCell a; long v; int m; boolean uncontended = true; if (as == null || (m = as.length - 1) < 0 || (a = as[ThreadLocalRandom.getProbe() & m]) == null || !(uncontended = U.compareAndSwapLong(a, CELLVALUE, v = a.value, v + x))) { fullAddCount(x, uncontended); return; } if (check <= 1) return; s = sumCount(); } //须要检查是否要扩容,默认check为0 ,每次都检查 if (check >= 0) { Node<K,V>[] tab, nt; int n, sc; //长度大于sizeCtl,前面说了是长度的是四分之三,而且小于最大容量2^30 //n 为数组长度 while (s >= (long)(sc = sizeCtl) && (tab = table) != null && (n = tab.length) < MAXIMUM_CAPACITY) { //待扩容列表长度n的校验戳 int rs = resizeStamp(n); //正在扩容 if (sc < 0) { // 待扩容长度n的校验戳不一致 || 长度+1了,其余线程扩容完了 || 超过最大的resizers || 扩容完成(transfer里)||扩容完成(transfer里) if ((sc >>> RESIZE_STAMP_SHIFT) != rs || sc == rs + 1 || sc == rs + MAX_RESIZERS || (nt = nextTable) == null || transferIndex <= 0) break; //添加帮助扩容线程 if (U.compareAndSwapInt(this, SIZECTL, sc, sc + 1)) //扩容 transfer(tab, nt); } //将计算出来的校验戳变为sizectl的高位,2是低位,保证了上面 sc >>> RESIZE_STAMP_SHIFT) != rs 的能够校验长度不变化 else if (U.compareAndSwapInt(this, SIZECTL, sc, (rs << RESIZE_STAMP_SHIFT) + 2)) transfer(tab, null); s = sumCount(); } } }
//扩容方法,该方法也比较长 private final void transfer(Node<K,V>[] tab, Node<K,V>[] nextTab) { int n = tab.length, stride; //stride 是每一个线程可处理的桶的数量,后面决定了nextBound的值 if ((stride = (NCPU > 1) ? (n >>> 3) / NCPU : n) < MIN_TRANSFER_STRIDE) stride = MIN_TRANSFER_STRIDE; // subdivide range //初始化nextTab if (nextTab == null) { // initiating try { @SuppressWarnings("unchecked") Node<K,V>[] nt = (Node<K,V>[])new Node<?,?>[n << 1]; //扩容为2倍 nextTab = nt; //OOM } catch (Throwable ex) { // try to cope with OOME sizeCtl = Integer.MAX_VALUE; return; } nextTable = nextTab; //从后向前遍历,<=0时遍历扩容完成 transferIndex = n; } int nextn = nextTab.length; //table里面某个位置的首节点,表明移动了,会被看成判断条件 ForwardingNode<K,V> fwd = new ForwardingNode<K,V>(nextTab); boolean advance = true; boolean finishing = false; // to ensure sweep before committing nextTab //bound 是边界 for (int i = 0, bound = 0;;) { Node<K,V> f; int fh; //获取该线程处理的桶的边界 以及负责向前推动下标i //advance 是上面操做的控制器 while (advance) { int nextIndex, nextBound; // 向前推动下标 if (--i >= bound || finishing) advance = false; else if ((nextIndex = transferIndex) <= 0) { i = -1; advance = false; } //当前参与扩容的线程给nextindex赋值,成功的话,bound设置为nextBound i=transferIndex-1,跳出循环 else if (U.compareAndSwapInt (this, TRANSFERINDEX, nextIndex, nextBound = (nextIndex > stride ? nextIndex - stride : 0))) { bound = nextBound; i = nextIndex - 1; advance = false; } } // i=-1 是上面transferIndex<=0的条件,任务执行完毕 if (i < 0 || i >= n || i + n >= nextn) { int sc; if (finishing) { nextTable = null; table = nextTab; sizeCtl = (n << 1) - (n >>> 1); return; } if (U.compareAndSwapInt(this, SIZECTL, sc = sizeCtl, sc - 1)) { if ((sc - 2) != resizeStamp(n) << RESIZE_STAMP_SHIFT) return; finishing = advance = true; //配合上面的>=n 从新计算table和sizeCtl i = n; // recheck before commit } } //占位 else if ((f = tabAt(tab, i)) == null) advance = casTabAt(tab, i, null, fwd); else if ((fh = f.hash) == MOVED) //该位置已经处理过,从新计算i bound等,继续向前推动 advance = true; // already processed else { //f是当前i位置的节点 synchronized (f) { if (tabAt(tab, i) == f) { Node<K,V> ln, hn; //fh是f的hash值 //链表操做 if (fh >= 0) { int runBit = fh & n; Node<K,V> lastRun = f; //找到链表中最后一个hash 相同的节点,就是最后一个节点 for (Node<K,V> p = f.next; p != null; p = p.next) { int b = p.hash & n; if (b != runBit) { runBit = b; lastRun = p; } } //ln 猜想是low node hn认为是 high node ,由于会拆出来两个链表 // hash&n ==0 一个判断标准,符合这样的,就做为ln,不符合的做为hn if (runBit == 0) { ln = lastRun; hn = null; } else { hn = lastRun; ln = null; } //遍历全部节点,符合 hash & n == 0的 就放到ln的前面,不符合的就放到hn的前面 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); } //将ln 放到nexttab的i位置,high 放到i+n位置 setTabAt(nextTab, i, ln); setTabAt(nextTab, i + n, hn); //原tab 的i位置 放fwd占位 setTabAt(tab, i, fwd); //继续往下推动 advance = true; } //红黑树操做 else if (f instanceof TreeBin) { 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; } } } } } }