167 lines
7.0 KiB
Markdown
167 lines
7.0 KiB
Markdown
HashMap 源码中主要了解其核心源码及实现逻辑。ConcurrentHashMap 就不再重复那些数据结构相关的内容咯，这里重点看一下它的并发安全实现。源码如下。
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```java
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public class ConcurrentHashMap<K,V> extends AbstractMap<K,V> implements ConcurrentMap<K,V>,
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Serializable {
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/* --------- 常量及成员变量的设计 几乎与HashMap相差无几 -------- */
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/**
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* 最大容量
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*/
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private static final int MAXIMUM_CAPACITY = 1 << 30;
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/**
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* 默认初始容量
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*/
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private static final int DEFAULT_CAPACITY = 16;
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/**
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* 单个数组最大容量
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*/
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static final int MAX_ARRAY_SIZE = Integer.MAX_VALUE - 8;
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/**
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* 默认并发等级，也就分成多少个单独上锁的区域
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*/
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private static final int DEFAULT_CONCURRENCY_LEVEL = 16;
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/**
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* 扩容因子
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*/
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private static final float LOAD_FACTOR = 0.75f;
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/**
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*
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*/
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transient volatile Node<K,V>[] table;
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/**
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*
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*/
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private transient volatile Node<K,V>[] nextTable;
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/* --------- 系列构造方法，依然推荐在初始化时根据实际情况设置好初始容量 -------- */
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public ConcurrentHashMap() {
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}
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public ConcurrentHashMap(int initialCapacity) {
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if (initialCapacity < 0)
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throw new IllegalArgumentException();
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int cap = ((initialCapacity >= (MAXIMUM_CAPACITY >>> 1)) ?
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MAXIMUM_CAPACITY :
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tableSizeFor(initialCapacity + (initialCapacity >>> 1) + 1));
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this.sizeCtl = cap;
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}
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public ConcurrentHashMap(Map<? extends K, ? extends V> m) {
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this.sizeCtl = DEFAULT_CAPACITY;
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putAll(m);
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}
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public ConcurrentHashMap(int initialCapacity, float loadFactor) {
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this(initialCapacity, loadFactor, 1);
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}
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public ConcurrentHashMap(int initialCapacity,
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float loadFactor, int concurrencyLevel) {
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if (!(loadFactor > 0.0f) || initialCapacity < 0 || concurrencyLevel <= 0)
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throw new IllegalArgumentException();
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if (initialCapacity < concurrencyLevel) // Use at least as many bins
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initialCapacity = concurrencyLevel; // as estimated threads
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long size = (long)(1.0 + (long)initialCapacity / loadFactor);
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int cap = (size >= (long)MAXIMUM_CAPACITY) ?
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MAXIMUM_CAPACITY : tableSizeFor((int)size);
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this.sizeCtl = cap;
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}
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/**
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* ConcurrentHashMap 的核心就在于其put元素时 利用synchronized局部锁 和
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* CAS乐观锁机制 大大提升了本集合的并发能力，比JDK7的分段锁性能更强
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*/
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public V put(K key, V value) {
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return putVal(key, value, false);
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}
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/**
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* 当前指定数组位置无元素时，使用CAS操作 将 Node键值对 放入对应的数组下标。
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* 出现hash冲突，则用synchronized局部锁锁住，若当前hash对应的节点是链表的头节点，遍历链表，
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* 若找到对应的node节点，则修改node节点的val，否则在链表末尾添加node节点；倘若当前节点是
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* 红黑树的根节点，在树结构上遍历元素，更新或增加节点
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*/
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final V putVal(K key, V value, boolean onlyIfAbsent) {
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if (key == null || value == null) throw new NullPointerException();
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int hash = spread(key.hashCode());
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int binCount = 0;
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for (Node<K,V>[] tab = table;;) {
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Node<K,V> f; int n, i, fh;
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if (tab == null || (n = tab.length) == 0)
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tab = initTable();
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else if ((f = tabAt(tab, i = (n - 1) & hash)) == null) {
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// 注意！这是一个CAS的方法，将新节点放入指定位置，不用加锁阻塞线程
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// 也能保证并发安全
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if (casTabAt(tab, i, null, new Node<K,V>(hash, key, value, null)))
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break; // no lock when adding to empty bin
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}
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// 当前Map在扩容，先协助扩容，在更新值
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else if ((fh = f.hash) == MOVED)
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tab = helpTransfer(tab, f);
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else { // hash冲突
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V oldVal = null;
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// 局部锁，有效减少锁竞争的发生
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synchronized (f) { // f 是 链表头节点/红黑树根节点
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if (tabAt(tab, i) == f) {
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if (fh >= 0) {
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binCount = 1;
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for (Node<K,V> e = f;; ++binCount) {
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K ek;
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// 若节点已经存在，修改该节点的值
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if (e.hash == hash && ((ek = e.key) == key ||
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(ek != null && key.equals(ek)))) {
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oldVal = e.val;
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if (!onlyIfAbsent)
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e.val = value;
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break;
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}
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Node<K,V> pred = e;
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// 节点不存在，添加到链表末尾
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if ((e = e.next) == null) {
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pred.next = new Node<K,V>(hash, key,
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value, null);
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break;
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}
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}
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}
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// 如果该节点是 红黑树节点
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else if (f instanceof TreeBin) {
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Node<K,V> p;
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binCount = 2;
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if ((p = ((TreeBin<K,V>)f).putTreeVal(hash, key,
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value)) != null) {
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oldVal = p.val;
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if (!onlyIfAbsent)
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p.val = value;
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}
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}
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}
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}
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// 链表节点超过了8，链表转为红黑树
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if (binCount != 0) {
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if (binCount >= TREEIFY_THRESHOLD)
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treeifyBin(tab, i);
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if (oldVal != null)
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return oldVal;
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break;
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}
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}
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}
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// 统计节点个数，检查是否需要resize
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addCount(1L, binCount);
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return null;
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}
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}
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```
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**与 JDK1.7 在同步机制上的区别** 总结如下：
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JDK1.7 使用的是分段锁机制，其内部类 Segment 继承了 ReentrantLock，将 容器内的数组划分成多段区域，每个区域对应一把锁，相比于 HashTable 确实提升了不少并发能力，但在数据量庞大的情况下，性能依然不容乐观，只能通过不断的增加锁来维持并发性能。而 JDK1.8 则使用了 CAS 乐观锁 + synchronized 局部锁 处理并发问题，锁粒度更细，即使数据量很大也能保证良好的并发性。
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