基本使用
案例 :单词计数
public class TestWordCount { public static void main(String[] args) { demo( // 创建 map 集合 // 创建 ConcurrentHashMap 对不对？ () -> new ConcurrentHashMap<String, LongAdder>(8,0.75f,8), (map, words) -> { for (String word : words) { // 如果缺少一个 key，则计算生成一个 value , 然后将 key value 放入 map // a 0 LongAdder value = map.computeIfAbsent(word, (key) -> new LongAdder()); // 执行累加 value.increment(); // 2 /*// 检查 key 有没有 Integer counter = map.get(word); int newValue = counter == null ? 1 : counter + 1; // 没有 则 put map.put(word, newValue);*/ } } ); } private static void demo2() { Map<String, Integer> collect = IntStream.range(1, 27).parallel() .mapToObj(idx -> readFromFile(idx)) .flatMap(list -> list.stream()) .collect(Collectors.groupingBy(Function.identity(), Collectors.summingInt(w -> 1))); System.out.println(collect); } private static <V> void demo(Supplier<Map<String, V>> supplier, BiConsumer<Map<String, V>, List<String>> consumer) { Map<String, V> counterMap = supplier.get(); // key value // a 200 // b 200 List<Thread> ts = new ArrayList<>(); for (int i = 1; i <= 26; i++) { int idx = i; Thread thread = new Thread(() -> { List<String> words = readFromFile(idx); consumer.accept(counterMap, words); }); ts.add(thread); } ts.forEach(t -> t.start()); ts.forEach(t -> { try { t.join(); } catch (InterruptedException e) { e.printStackTrace(); } }); System.out.println(counterMap); } public static List<String> readFromFile(int i) { ArrayList<String> words = new ArrayList<>(); try (BufferedReader in = new BufferedReader(new InputStreamReader(new FileInputStream("tmp/" + i + ".txt")))) { while (true) { String word = in.readLine(); if (word == null) { break; } words.add(word); } return words; } catch (IOException e) { throw new RuntimeException(e); } } }
重要成员变量
// 默认为 0 // 当初始化时, 为 -1 // 当扩容时, 为 -(1 + 扩容线程数) // 当初始化或扩容完成后，为 下一次的扩容的阈值大小 private transient volatile int sizeCtl; // 整个 ConcurrentHashMap 就是一个 Node[] static class Node<K,V> implements Map.Entry<K,V> {} // hash 表 transient volatile Node<K,V>[] table; // 扩容时的 新 hash 表 private transient volatile Node<K,V>[] nextTable; // 扩容时如果某个 bin 迁移完毕, 用 ForwardingNode 作为旧 table bin 的头结点 static final class ForwardingNode<K,V> extends Node<K,V> {} // 用在 compute 以及 computeIfAbsent 时, 用来占位, 计算完成后替换为普通 Node static final class ReservationNode<K,V> extends Node<K,V> {} // 作为 treebin 的头节点, 存储 root 和 first static final class TreeBin<K,V> extends Node<K,V> {} // 作为 treebin 的节点, 存储 parent, left, right static final class TreeNode<K,V> extends Node<K,V> {}
方法
// 获取 Node[] 中第 i 个 Node static final <K,V> Node<K,V> tabAt(Node<K,V>[] tab, int i) // cas 修改 Node[] 中第 i 个 Node 的值, c 为旧值, v 为新值 static final <K,V> boolean casTabAt(Node<K,V>[] tab, int i, Node<K,V> c, Node<K,V> v) // 直接修改 Node[] 中第 i 个 Node 的值, v 为新值 static final <K,V> void setTabAt(Node<K,V>[] tab, int i, Node<K,V> v)
JDK8版本
构造器分析
可以看到实现了懒惰初始化，在构造方法中仅仅计算了 table 的大小，以后在第一次使用时才会真正创建
public ConcurrentHashMap(int initialCapacity, float loadFactor, int concurrencyLevel) { if (!(loadFactor > 0.0f) || initialCapacity < 0 || concurrencyLevel <= 0) throw new IllegalArgumentException(); if (initialCapacity < concurrencyLevel) // Use at least as many bins initialCapacity = concurrencyLevel; // as estimated threads long size = (long)(1.0 + (long)initialCapacity / loadFactor); // tableSizeFor 仍然是保证计算的大小是 2^n, 即 16,32,64 ... int cap = (size >= (long)MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : tableSizeFor((int)size); this.sizeCtl = cap; }
get 流程
public V get(Object key) { Node<K,V>[] tab; Node<K,V> e, p; int n, eh; K ek; // spread 方法能确保返回结果是正数 int h = spread(key.hashCode()); if ((tab = table) != null && (n = tab.length) > 0 && (e = tabAt(tab, (n - 1) & h)) != null) { // 如果头结点已经是要查找的 key if ((eh = e.hash) == h) { if ((ek = e.key) == key || (ek != null && key.equals(ek))) return e.val; } // hash 为负数表示该 bin 在扩容中或是 treebin, 这时调用 find 方法来查找 else if (eh < 0) return (p = e.find(h, key)) != null ? p.val : null; // 正常遍历链表, 用 equals 比较 while ((e = e.next) != null) { if (e.hash == h && ((ek = e.key) == key || (ek != null && key.equals(ek)))) return e.val; } } return null; }
put 流程
以下数组简称（table），链表简称（bin）
public V put(K key, V value) { return putVal(key, value, false); } /** Implementation for put and putIfAbsent */ final V putVal(K key, V value, boolean onlyIfAbsent) { if (key == null || value == null) throw new NullPointerException(); // 其中 spread 方法会综合高位低位, 具有更好的 hash 性 int hash = spread(key.hashCode()); int binCount = 0; for (Node<K,V>[] tab = table;;) { // f 是链表头节点 // fh 是链表头结点的 hash // i 是链表在 table 中的下标 Node<K,V> f; int n, i, fh; // 要创建 table if (tab == null || (n = tab.length) == 0) // 初始化 table 使用了 cas, 无需 synchronized 创建成功, 进入下一轮循环 tab = initTable(); // 要创建链表头节点 else if ((f = tabAt(tab, i = (n - 1) & hash)) == null) { // 添加链表头使用了 cas, 无需 synchronized if (casTabAt(tab, i, null, new Node<K,V>(hash, key, value, null))) break; // no lock when adding to empty bin } // 帮忙扩容 else if ((fh = f.hash) == MOVED) // 帮忙之后, 进入下一轮循环 tab = helpTransfer(tab, f); else { V oldVal = null; // 锁住链表头节点 synchronized (f) { // 再次确认链表头节点没有被移动 if (tabAt(tab, i) == f) { // 链表 if (fh >= 0) { binCount = 1; // 遍历链表 for (Node<K,V> e = f;; ++binCount) { K ek; // 找到相同的 key if (e.hash == hash && ((ek = e.key) == key || (ek != null && key.equals(ek)))) { oldVal = e.val; // 更新 if (!onlyIfAbsent) e.val = value; break; } Node<K,V> pred = e; // 已经是最后的节点了, 新增 Node, 追加至链表尾 if ((e = e.next) == null) { pred.next = new Node<K,V>(hash, key, value, null); break; } } } // 红黑树 else if (f instanceof TreeBin) { Node<K,V> p; binCount = 2; // putTreeVal 会看 key 是否已经在树中, 是, 则返回对应的 TreeNode if ((p = ((TreeBin<K,V>)f).putTreeVal(hash, key, value)) != null) { oldVal = p.val; if (!onlyIfAbsent) p.val = value; } } } // 释放链表头节点的锁 } if (binCount != 0) { if (binCount >= TREEIFY_THRESHOLD) // 如果链表长度 >= 树化阈值(8), 进行链表转为红黑树 treeifyBin(tab, i); if (oldVal != null) return oldVal; break; } } } // 增加 size 计数 addCount(1L, binCount); return null; }
/** * 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) { if ((sc = sizeCtl) < 0) Thread.yield(); // lost initialization race; just spin // 尝试将 sizeCtl 设置为 -1（表示初始化 table） else if (U.compareAndSwapInt(this, SIZECTL, sc, -1)) { try { // 获得锁, 创建 table, 这时其它线程会在 while() 循环中 yield 直至 table 创建 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 = n - (n >>> 2); } } finally { sizeCtl = sc; } break; } } return tab; }
// check 是之前 binCount 的个数 private final void addCount(long x, int check) { CounterCell[] as; long b, s; if ( // 已经有了 counterCells, 向 cell 累加 (as = counterCells) != null || // 还没有, 向 baseCount 累加 !U.compareAndSwapLong(this, BASECOUNT, b = baseCount, s = b + x)) { CounterCell a; long v; int m; boolean uncontended = true; if ( // 还没有 counterCells as == null || (m = as.length - 1) < 0 || // 还没有 cell (a = as[ThreadLocalRandom.getProbe() & m]) == null || // cell cas 增加计数失败 !(uncontended = U.compareAndSwapLong(a, CELLVALUE, v = a.value, v + x))) { // 创建累加单元数组和cell, 累加重试 fullAddCount(x, uncontended); return; } if (check <= 1) return; // 获取元素个数 s = sumCount(); } if (check >= 0) { Node<K,V>[] tab, nt; int n, sc; while (s >= (long)(sc = sizeCtl) && (tab = table) != null && (n = tab.length) < MAXIMUM_CAPACITY) { int rs = resizeStamp(n); if (sc < 0) { if ((sc >>> RESIZE_STAMP_SHIFT) != rs || sc == rs + 1 || sc == rs + MAX_RESIZERS || (nt = nextTable) == null || transferIndex <= 0) break; // newtable 已经创建了，帮忙扩容 if (U.compareAndSwapInt(this, SIZECTL, sc, sc + 1)) transfer(tab, nt); } // 需要扩容，这时 newtable 未创建 else if (U.compareAndSwapInt(this, SIZECTL, sc, (rs << RESIZE_STAMP_SHIFT) + 2)) transfer(tab, null); s = sumCount(); } } }
size 计算流程
size 计算实际发生在 put，remove 改变集合元素的操作之中 没
- 有竞争发生，向 baseCount 累加计数
- 有竞争发生，新建 counterCells，向其中的一个 cell 累加计数
- counterCells 初始有两个 cell
- 如果计数竞争比较激烈，会创建新的 cell 来累加计数
public int size() { long n = sumCount(); return ((n < 0L) ? 0 : (n > (long)Integer.MAX_VALUE) ? Integer.MAX_VALUE : (int)n); } final long sumCount() { CounterCell[] as = counterCells; CounterCell a; long sum = baseCount; if (as != null) { for (int i = 0; i < as.length; ++i) { if ((a = as[i]) != null) sum += a.value; } } return sum; }
1.8改进方案的总结
Java 8 数组（Node） +（ 链表 Node | 红黑树 TreeNode ） 以下数组简称（table），链表简称（bin）
- 初始化，使用 cas 来保证并发安全，懒惰初始化 table
- 树化，当 table.length < 64 时，先尝试扩容，超过 64 时，并且 bin.length > 8 时，会将链表树化，树化过程会用
synchronized锁住链表头
- put，如果该 bin 尚未创建，只需要使用 cas 创建 bin；如果已经有了，锁住链表头进行后续 put 操作，元素添加至 bin 的尾部
- get，无锁操作仅需要保证可见性，扩容过程中 get 操作拿到的是
ForwardingNode它会让 get 操作在新table 进行搜索
- 扩容，扩容时以 bin 为单位进行，需要对 bin 进行
synchronized，但这时妙的是其它竞争线程也不是无事可做，它们会帮助把其它 bin 进行扩容，扩容时平均只有 1/6 的节点会把复制到新 table 中
- size，元素个数保存在 baseCount 中，并发时的个数变动保存在 CounterCell[] 当中。最后统计数量时累加即可
JDK7实现
它维护了一个 segment 数组，每个 segment 对应一把锁
优点：如果多个线程访问不同的 segment，实际是没有冲突的，这与 jdk8 中是类似的
缺点：Segments 数组默认大小为16，这个容量初始化指定后就不能改变了，并且不是懒惰初始化
构造器分析
public ConcurrentHashMap(int initialCapacity, float loadFactor, int concurrencyLevel) { if (!(loadFactor > 0) || initialCapacity < 0 || concurrencyLevel <= 0) throw new IllegalArgumentException(); if (concurrencyLevel > MAX_SEGMENTS) concurrencyLevel = MAX_SEGMENTS; // Find power-of-two sizes best matching arguments // ssize 必须是 2^n, 即 2, 4, 8, 16 ... 表示了 segments 数组的大小 int sshift = 0; int ssize = 1; while (ssize < concurrencyLevel) { ++sshift; ssize <<= 1; } // segmentShift 默认是 32 - 4 = 28 this.segmentShift = 32 - sshift; // segmentMask 默认是 15 即 0000 0000 0000 1111 this.segmentMask = ssize - 1; if (initialCapacity > MAXIMUM_CAPACITY) initialCapacity = MAXIMUM_CAPACITY; int c = initialCapacity / ssize; if (c * ssize < initialCapacity) ++c; int cap = MIN_SEGMENT_TABLE_CAPACITY; while (cap < c) cap <<= 1; // create segments and segments[0] // 创建 segments and segments[0] Segment<K,V> s0 = new Segment<K,V>(loadFactor, (int)(cap * loadFactor), (HashEntry<K,V>[])new HashEntry[cap]); Segment<K,V>[] ss = (Segment<K,V>[])new Segment[ssize]; UNSAFE.putOrderedObject(ss, SBASE, s0); // ordered write of segments[0] this.segments = ss; }
构造完成，如下图所示
可以看到 ConcurrentHashMap 没有实现懒惰初始化，空间占用不友好，其中 this.segmentShift 和 this.segmentMask 的作用是决定将 key 的 hash 结果匹配到哪个 segment
例如，根据某一 hash 值求 segment 位置，先将高位向低位移动
this.segmentShift 位
结果再与 this.segmentMask 做位于运算，最终得到 1010 即下标为 10 的 segment
put
public V put(K key, V value) { Segment<K,V> s; if (value == null) throw new NullPointerException(); int hash = hash(key); // 计算出 segment 下标 int j = (hash >>> segmentShift) & segmentMask; // 获得 segment 对象, 判断是否为 null, 是则创建该 segment if ((s = (Segment<K,V>)UNSAFE.getObject // nonvolatile; recheck (segments, (j << SSHIFT) + SBASE)) == null) // in ensureSegment // 这时不能确定是否真的为 null, 因为其它线程也发现该 segment 为 null, // 因此在 ensureSegment 里用 cas 方式保证该 segment 安全性 s = ensureSegment(j); // 进入 segment 的put 流程 return s.put(key, hash, value, false); }
final V put(K key, int hash, V value, boolean onlyIfAbsent) { // 尝试加锁 HashEntry<K,V> node = tryLock() ? null : // 如果不成功, 进入 scanAndLockForPut 流程 // 如果是多核 cpu 最多 tryLock 64 次, 进入 lock 流程 // 在尝试期间, 还可以顺便看该节点在链表中有没有, 如果没有顺便创建出来 scanAndLockForPut(key, hash, value); // 执行到这里 segment 已经被成功加锁, 可以安全执行 V oldValue; try { HashEntry<K,V>[] tab = table; int index = (tab.length - 1) & hash; HashEntry<K,V> first = entryAt(tab, index); for (HashEntry<K,V> e = first;;) { if (e != null) { // 更新 K k; if ((k = e.key) == key || (e.hash == hash && key.equals(k))) { oldValue = e.value; if (!onlyIfAbsent) { e.value = value; ++modCount; } break; } e = e.next; } else { // 新增 // 1) 之前等待锁时, node 已经被创建, next 指向链表头 if (node != null) node.setNext(first); else // 2) 创建新 node node = new HashEntry<K,V>(hash, key, value, first); // 3) 扩容 int c = count + 1; if (c > threshold && tab.length < MAXIMUM_CAPACITY) rehash(node); else // 将 node 作为链表头 setEntryAt(tab, index, node); ++modCount; count = c; oldValue = null; break; } } } finally { unlock(); } return oldValue; }
rehash
发生在 put 中，因为此时已经获得了锁，因此 rehash 时不需要考虑线程安全
private void rehash(HashEntry<K,V> node) { /* * Reclassify nodes in each list to new table. Because we * are using power-of-two expansion, the elements from * each bin must either stay at same index, or move with a * power of two offset. We eliminate unnecessary node * creation by catching cases where old nodes can be * reused because their next fields won't change. * Statistically, at the default threshold, only about * one-sixth of them need cloning when a table * doubles. The nodes they replace will be garbage * collectable as soon as they are no longer referenced by * any reader thread that may be in the midst of * concurrently traversing table. Entry accesses use plain * array indexing because they are followed by volatile * table write. */ HashEntry<K,V>[] oldTable = table; int oldCapacity = oldTable.length; int newCapacity = oldCapacity << 1; threshold = (int)(newCapacity * loadFactor); HashEntry<K,V>[] newTable = (HashEntry<K,V>[]) new HashEntry[newCapacity]; int sizeMask = newCapacity - 1; for (int i = 0; i < oldCapacity ; i++) { HashEntry<K,V> e = oldTable[i]; if (e != null) { HashEntry<K,V> next = e.next; int idx = e.hash & sizeMask; if (next == null) // Single node on list newTable[idx] = e; else { // Reuse consecutive sequence at same slot HashEntry<K,V> lastRun = e; int lastIdx = idx; // 过一遍链表, 尽可能把 rehash 后 idx 不变的节点重用 for (HashEntry<K,V> last = next; last != null; last = last.next) { int k = last.hash & sizeMask; if (k != lastIdx) { lastIdx = k; lastRun = last; } } newTable[lastIdx] = lastRun; // Clone remaining nodes // 剩余节点需要新建 for (HashEntry<K,V> p = e; p != lastRun; p = p.next) { V v = p.value; int h = p.hash; int k = h & sizeMask; HashEntry<K,V> n = newTable[k]; newTable[k] = new HashEntry<K,V>(h, p.key, v, n); } } } } // 扩容完成, 才加入新的节点 int nodeIndex = node.hash & sizeMask; // add the new node node.setNext(newTable[nodeIndex]); newTable[nodeIndex] = node; // 替换为新的 HashEntry table table = newTable; }
验证
public static void main(String[] args) { ConcurrentHashMap<Integer, String> map = new ConcurrentHashMap<>(); for (int i = 0; i < 1000; i++) { int hash = hash(i); int segmentIndex = (hash >>> 28) & 15; if (segmentIndex == 4 && hash % 8 == 2) { System.out.println(i + "\t" + segmentIndex + "\t" + hash % 2 + "\t" + hash % 4 +"\t" + hash % 8); } } map.put(1, "value"); map.put(15, "value"); // 2 扩容为 4 15 的 hash%8 与其他不同 map.put(169, "value"); map.put(197, "value"); // 4 扩容为 8 map.put(341, "value"); map.put(484, "value"); map.put(545, "value"); // 8 扩容为 16 map.put(912, "value"); map.put(941, "value"); System.out.println("ok"); } private static int hash(Object k) { int h = 0; if ((0 != h) && (k instanceof String)) { return sun.misc.Hashing.stringHash32((String) k); } h ^= k.hashCode(); // Spread bits to regularize both segment and index locations, // using variant of single-word Wang/Jenkins hash. h += (h << 15) ^ 0xffffcd7d; h ^= (h >>> 10); h += (h << 3); h ^= (h >>> 6); h += (h << 2) + (h << 14); int v = h ^ (h >>> 16); return v; }
get 流程
get 时并未加锁，用了 UNSAFE 方法保证了可见性，扩容过程中，get 先发生就从旧表取内容，get 后发生就从新表取内容
public V get(Object key) { Segment<K,V> s; // manually integrate access methods to reduce overhead HashEntry<K,V>[] tab; int h = hash(key); // u 为 segment 对象在数组中的偏移量 long u = (((h >>> segmentShift) & segmentMask) << SSHIFT) + SBASE; if ((s = (Segment<K,V>)UNSAFE.getObjectVolatile(segments, u)) != null && (tab = s.table) != null) { for (HashEntry<K,V> e = (HashEntry<K,V>) UNSAFE.getObjectVolatile (tab, ((long)(((tab.length - 1) & h)) << TSHIFT) + TBASE); e != null; e = e.next) { K k; if ((k = e.key) == key || (e.hash == h && key.equals(k))) return e.value; } } return null; }
size 计算流程
- 计算元素个数前，先不加锁计算两次，如果前后两次结果如一样，认为个数正确返回
- 如果不一样，进行重试，重试次数超过 3，将所有 segment 锁住，重新计算个数返回
public int size() { // Try a few times to get accurate count. On failure due to // continuous async changes in table, resort to locking. final Segment<K,V>[] segments = this.segments; int size; boolean overflow; // true if size overflows 32 bits long sum; // sum of modCounts long last = 0L; // previous sum int retries = -1; // first iteration isn't retry try { for (;;) { if (retries++ == RETRIES_BEFORE_LOCK) { for (int j = 0; j < segments.length; ++j) // 超过重试次数, 需要创建所有 segment 并加锁 ensureSegment(j).lock(); // force creation } sum = 0L; size = 0; overflow = false; for (int j = 0; j < segments.length; ++j) { Segment<K,V> seg = segmentAt(segments, j); if (seg != null) { sum += seg.modCount; int c = seg.count; if (c < 0 || (size += c) < 0) overflow = true; } } if (sum == last) break; last = sum; } } finally { if (retries > RETRIES_BEFORE_LOCK) { for (int j = 0; j < segments.length; ++j) segmentAt(segments, j).unlock(); } } return overflow ? Integer.MAX_VALUE : size; }