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ConcurrentHashMap

2017-07-17 17:52 169 查看
ConcurrentHashMap继承了AbstractMap,实现了AbstractMap和Serializable接口。

ConcurrentHashMap是支持高并发的hashMap。

//节点信息保存了对应的hash值、key、value,及下一节点信息,但是value和下一节点信息用volatile 修饰,保证可见性。
static class Node<K,V> implements Map.Entry<K,V> {
final int hash;
final K key;
volatile V val;              //volatile修饰,保证可见性
volatile Node<K,V> next;     //volatile修饰,保证可见性

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; }

//不允许直接修改value值,但是增加了一个find帮助类。
public final V setValue(V value) {
throw new UnsupportedOperationException();
}

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();
*/
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;
}
}


另外一个重要的存储结构是ForwardingNode,ForwardingNode继承Node,内部有一个final类型的数组,及节点信息,重写了find方法,方便在内部数组查找信息。

static final class ForwardingNode<K,V> extends Node<K,V> {
final Node<K,V>[] nextTable;   //不可修改的数组,保存节点信息
ForwardingNode(Node<K,V>[] tab) {
super(MOVED, null, null, null);
this.nextTable = tab;
}

Node<K,V> find(int h, Object k) {

outer: for (Node<K,V>[] tab = nextTable;;) {
Node<K,V> e; int n;

if (k == null || tab == null || (n = tab.length) == 0 ||(e = tabAt(tab, (n - 1) & h)) == null)
return null;
for (;;) {
int eh; K ek;
if ((eh = e.hash) == h &&((ek = e.key) == k || (ek != null && k.equals(ek))))
return e;
if (eh < 0) {
if (e instanceof ForwardingNode) {
tab = ((ForwardingNode<K,V>)e).nextTable;
continue outer;
}
else
return e.find(h, k);
}
if ((e = e.next) == null)
return null;
}
}
}
}


几个重要的值

/*
*判断当前节点的下一节点指向的类型
*/
static final int MOVED     = -1; //指向的是ForwardingNode节点
static final int TREEBIN   = -2; //指向的是tree节点

transient volatile Node<K,V>[] table;   //hash桶,volatile修饰,保证可见性

private transient volatile Node<K,V>[] nextTable; //指向的下一个hash桶,volatile修饰,保证可见性

/*
*表示当前表的状态,为负数的时候表示当前表正在初始化或扩容
*-1表示正在初始化,其他负数表示 -1+数值正在扩容的线程数
*/
private transient volatile int sizeCtl
4000
;

//反向链表,不为空的时候总是2的幂数
private transient volatile CounterCell[] counterCells;


下面根据常用的流程来梳理其内部结构。首先是最常用的put(K key, V value)方法。put方法会调用putVal(key, value, false)方法。

final V putVal(K key, V value, boolean onlyIfAbsent) {
//不允许key=null和value=null
if (key == null || value == null) throw new NullPointerException();
//对hash值重新计算,以减少冲突
int hash = spread(key.hashCode());
int binCount = 0;

//对当前表进行遍历
for (Node<K,V>[] tab = table;;) {
Node<K,V> f; int n, i, fh;
if (tab == null || (n = tab.length) == 0)
//当前表为空,对表初始化
tab = initTable();
else if ((f = tabAt(tab, i = (n - 1) & hash)) == null) {
if (casTabAt(tab, i, null,
new Node<K,V>(hash, key, value, null)))
break;
}
//当前节点正在扩容,线程帮助扩容
else if ((fh = f.hash) == MOVED)
tab = helpTransfer(tab, f);
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;
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;
if ((e = e.next) == null) {
pred.next = new Node<K,V>(hash, key,
value, null);
break;
}
}
}
else if (f instanceof TreeBin) {
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)
treeifyBin(tab, i);
if (oldVal != null)
return oldVal;
break;
}
}
}
addCount(1L, binCount);
return null;
}


initTable()

private final Node<K,V>[] initTable() {
Node<K,V>[] tab; int sc;
//当表为空的时候进行循环
while ((tab = table) == null || tab.length == 0) {
//当sizeCtl为负数时,表示当前表正在初始化或扩容,当前线程进行等待
if ((sc = sizeCtl) < 0)
Thread.yield(); // lost initialization race; just spin
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<?,?>
;
table = tab = nt;
sc = n - (n >>> 2);
}
} finally {
sizeCtl = sc;
}
break;
}
}
return tab;
}


helpTransfer
(Node<K,V>[] tab, Node<K,V> f)


final Node<K,V>[] helpTransfer(Node<K,V>[] tab, Node<K,V> f) {
Node<K,V>[] nextTab; int sc;
if (tab != null && (f instanceof ForwardingNode) &&
(nextTab = ((ForwardingNode<K,V>)f).nextTable) != null) {
//生成一个数字戳,防止ABA问题
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)) {
transfer(tab, nextTab);
break;
}
}
return nextTab;
}
return table;
}


到这里,关于put的所有方法已经完成。

* get(Object key)*

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) {
if ((eh = e.hash) == h) {
//在数组中
if ((ek = e.key) == key || (ek != null && key.equals(ek)))
return e.val;
}
else if (eh < 0)
//在小数组中
return (p = e.find(h, key)) != null ? p.val : null;
while ((e = e.next) != null) {
if (e.hash == h &&
//在链表中
((ek = e.key) == key || (ek != null && key.equals(ek))))
return e.val;
}
}
return null;
}


ConcurrentHashMap是一个比较难的类,看过之后还是一知半解,还需要不断学习。
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