上文中结尾处，我们说到了现在很少用Hashtable，那么在需要线程安全的场景中，我们如何保持同步呢，这就是本文的重点：ConcurrentHashMap（JDK1.7）。ConcurrentHashMap比HashMap以及Hashtable复杂多了，其内部采用了锁分段技术用以提高并发存取效率。我们看一下测试代码：
代码清单1：
import java.util.HashMap;
import java.util.Hashtable;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
public class CurrentHashMapTest {
private static ConcurrentHashMap<String,String> concurrentHashMap=new ConcurrentHashMap<>();
private static Hashtable<String,String> hashtable=new Hashtable<>();
private static HashMap<String,String> hashMap=new HashMap<>();
public static void main(String[] args){
testConcurrentHashMapThreadSafe();
System.out.println(concurrentHashMap.size()+"last:"+concurrentHashMap.get("concurrentHashMap9999"));
testHashtableThreadSafe();
System.out.println(hashtable.size()+"last:"+hashtable.get("hashtable9999"));
testHashMapThreadSafe();
System.out.println(hashMap.size()+"last:"+hashMap.get("hashmap9999"));
System.out.println("test end");
}
public static void testConcurrentHashMapThreadSafe(){
long startTime=System.currentTimeMillis();
for (int i=0;i<100000;i++){
new ConcurrentThread(i,"concurrentHashMap",concurrentHashMap).start();
}
long endTime=System.currentTimeMillis();
System.out.println("ConcurrentHashMap take time:"+(endTime-startTime));
}
public static void testHashtableThreadSafe(){
long startTime=System.currentTimeMillis();
for (int i=0;i<100000;i++){
new ConcurrentHashTableThread(i,"hashtable",hashtable).start();
}
long endTime=System.currentTimeMillis();
System.out.println("Hashtable take time:"+(endTime-startTime));
}
public static void testHashMapThreadSafe(){System.out.println("enter test HashMap");
long startTime=System.currentTimeMillis();
for (int i=0;i<100000;i++){
new ConcurrentHashMapThread(i,"hashmap",hashMap).start();
}
long endTime=System.currentTimeMillis();
System.out.println(" HashMap take time:"+(endTime-startTime));
}
}
class ConcurrentThread extends Thread{
public int i;
public String name;
private ConcurrentHashMap<String,String> map;
public ConcurrentThread(int i,String name,ConcurrentHashMap<String,String> map){
this.i=i;
this.name=name;
this.map=map;
}
@Override
public void run() {
super.run();
map.put(name+i,i+"");
}
}
class ConcurrentHashTableThread extends Thread{
public int i;
public String name;
private Hashtable<String,String> map;
public ConcurrentHashTableThread(int i,String name,Hashtable<String,String> map){
this.i=i;
this.name=name;
this.map=map;
}
@Override
public void run() {
super.run();
map.put(name+i,i+"");
}
}
class ConcurrentHashMapThread extends Thread{
public int i;
public String name;
private HashMap<String,String> map;
public ConcurrentHashMapThread(int i,String name,HashMap<String,String> map){
this.i=i;
this.name=name;
this.map=map;
}
@Override
public void run() {
super.run();
map.put(name+i,i+"");
}
}上面的代码输出结果(代码运行环境:Ubuntu14.04+idea+jdk1.7)：
ConcurrentHashMap take time:3522
100000last:9999
Hashtable take time:3674
100000last:9999
enter test HashMap
HashMap take time:1105168
99945last:9999
test end
从代码输出结果上可以看出ConcurrentHashMap的效率明显要比Hashtable要高效，而HashMap是不安全的。
先说一下ConcurrentHashMap的内部结构，如下图所示：
按照以前的风格，我们看下ConcurrentHashMap的构造函数，如代码清单2：
static final int DEFAULT_INITIAL_CAPACITY = 16;//table数组的默认长度，这个和HashMap是一样的
static final float DEFAULT_LOAD_FACTOR = 0.75f;//加载因子
static final int DEFAULT_CONCURRENCY_LEVEL = 16;//并发级别
static final int MAXIMUM_CAPACITY = 1 << 30;//最大容量，这里可以看到DEFAULT_INITIAL_CAPACITY、DEFAULT_LOAD_FACTOR、MAXIMUM_CAPACITY，都是和HashMap相应字段的值是相同的。
static final int MIN_SEGMENT_TABLE_CAPACITY = 2;//段组的最小长度，这里最小值为2的原因是，如果小于2的话(即为1)，就没有锁分段的意义了，就和Hashtable一样了，不能两个线程同时并发存和取数据了。
static final int MAX_SEGMENTS = 1 << 16; //段组的最大长度
static final int RETRIES_BEFORE_LOCK = 2;//
final int segmentMask;//地位掩码
final int segmentShift;//段偏移量
final Segment<K,V>[] segments;//段组
transient Set<K> keySet;
transient Set<Map.Entry<K,V>> entrySet;
transient Collection<V> values;
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
int sshift = 0;//左移次数
int ssize = 1;//经过计算得到段组的长度
while (ssize < concurrencyLevel) {//我们在阅读源码时，碰到这类代码，我们可以假设输入值，以便更好的理解代码的含义。
++sshift;
ssize <<= 1;//sszie的值为2的sshift幂
}
this.segmentShift = 32 - sshift;//
this.segmentMask = ssize - 1;//低位掩码，sszie为2的指数，则segmentMask的低位全是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的值是2的指数，同时计算之后也是table数组的容量。
cap <<= 1;
// create 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];//创建段组
UNSAFE.putOrderedObject(ss, SBASE, s0); // 利用Unsafe将s0放在SBASE放入位置
this.segments = ss;
}
public ConcurrentHashMap(int initialCapacity, float loadFactor) {
this(initialCapacity, loadFactor, DEFAULT_CONCURRENCY_LEVEL);
}
public ConcurrentHashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR, DEFAULT_CONCURRENCY_LEVEL);
}
public ConcurrentHashMap() {
this(DEFAULT_INITIAL_CAPACITY, DEFAULT_LOAD_FACTOR, DEFAULT_CONCURRENCY_LEVEL);
}
public ConcurrentHashMap(Map<? extends K, ? extends V> m) {
this(Math.max((int) (m.size() / DEFAULT_LOAD_FACTOR) + 1,
DEFAULT_INITIAL_CAPACITY),
DEFAULT_LOAD_FACTOR, DEFAULT_CONCURRENCY_LEVEL);
putAll(m);
}代码清单2中的34~41行，主要是为了计算segmentShift与segmentMask的值，下面举个两个计算过程的例子：
看了上面的两组运行数据，我们可以知道segmentShift以及segmentMask的值是由concurrentLevel决定的，这几个变量意义在代码注释里都有说明，这里就不进行阐述了。
我们创建ConcurrentHashMap对象的目的就是为了使用，于是我们就来到了put方法这里，如代码清单3
代码清单3
public V put(K key, V value) {
Segment<K,V> s;
if (value == null)
throw new NullPointerException();//ConcurrentHashMap也不能接收null的键值对的，key和value都不能为Null
int hash = hash(key);//计算哈希值
int j = (hash >>> segmentShift) & segmentMask;//计算段组的索引，（hash>>>segmentShift）保留哈希值的高位将其结果与segmentMask与是为了求段组下标。
if ((s = (Segment<K,V>)UNSAFE.getObject // nonvolatile; recheck
(segments, (j << SSHIFT) + SBASE)) == null) //取出(j<<SSHIFT)+SBASE内存偏移处的对象，如果为空，则创建。
s = ensureSegment(j);
return s.put(key, hash, value, false);//具体的put数据的操作由segment对象来完成。
}
private int hash(Object k) {//这个hash函数的作用就是为了对key的hashcode的原始值进行再次处理，以减少碰撞。
int h = hashSeed;
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);
return h ^ (h >>> 16);
}
private Segment<K,V> ensureSegment(int k) {
final Segment<K,V>[] ss = this.segments;
long u = (k << SSHIFT) + SBASE; //内存地址
Segment<K,V> seg;
if ((seg = (Segment<K,V>)UNSAFE.getObjectVolatile(ss, u)) == null) {//如果内存偏移处没有值，使用ss[0]元素为原型。
Segment<K,V> proto = ss[0]; // use segment 0 as prototype
int cap = proto.table.length;//复制容量
float lf = proto.loadFactor;//复制加载因子
int threshold = (int)(cap * lf);//阀值
HashEntry<K,V>[] tab = (HashEntry<K,V>[])new HashEntry[cap];
if ((seg = (Segment<K,V>)UNSAFE.getObjectVolatile(ss, u))
== null) { // 再次检查是否为null
Segment<K,V> s = new Segment<K,V>(lf, threshold, tab);//创建Segment对象
while ((seg = (Segment<K,V>)UNSAFE.getObjectVolatile(ss, u))
== null) {//循环检查u地址偏移处的对象是否为null
if (UNSAFE.compareAndSwapObject(ss, u, null, seg = s))//如果赋值成功则跳出循环，
break;
}
}
}
return seg;//最终返回此次创建的Segment对象或者u处的Segment对象。
}
// Unsafe mechanics
private static final sun.misc.Unsafe UNSAFE;
private static final long SBASE;
private static final int SSHIFT;//有多少个1位
private static final long TBASE;
private static final int TSHIFT;//有多少个1位
private static final long HASHSEED_OFFSET;
private static final long SEGSHIFT_OFFSET;
private static final long SEGMASK_OFFSET;
private static final long SEGMENTS_OFFSET;
static {
int ss, ts;
try {
UNSAFE = sun.misc.Unsafe.getUnsafe();
Class tc = HashEntry[].class;
Class sc = Segment[].class;
TBASE = UNSAFE.arrayBaseOffset(tc);//table组的对象头的偏移量
SBASE = UNSAFE.arrayBaseOffset(sc);//段组的对象头的偏移量
ts = UNSAFE.arrayIndexScale(tc);//单个HashEntry的大小，
ss = UNSAFE.arrayIndexScale(sc);//单个Segment的大小
HASHSEED_OFFSET = UNSAFE.objectFieldOffset(
ConcurrentHashMap.class.getDeclaredField("hashSeed"));//hashSeed的内存地址
SEGSHIFT_OFFSET = UNSAFE.objectFieldOffset(
ConcurrentHashMap.class.getDeclaredField("segmentShift"));//segmentShift的内存地址
SEGMASK_OFFSET = UNSAFE.objectFieldOffset(
ConcurrentHashMap.class.getDeclaredField("segmentMask"));//segmentMask的内存地址
SEGMENTS_OFFSET = UNSAFE.objectFieldOffset(
ConcurrentHashMap.class.getDeclaredField("segments"));//segment的起始地址
} catch (Exception e) {
throw new Error(e);
}
if ((ss & (ss-1)) != 0 || (ts & (ts-1)) != 0)//这里可以看到对于ss以及ts的要求也是2的指数值。
throw new Error("data type scale not a power of two");
SSHIFT = 31 - Integer.numberOfLeadingZeros(ss);//numberOfLeadingZeros是代表一个int型的二进制值代表数值的最高位为1的之前有多少个0位。也就是说SSHIFT与TSHIFT代表数据的有效信息占用多少位。
TSHIFT = 31 - Integer.numberOfLeadingZeros(ts);
}通过代码清单3我们知道了ConcurrentHashMap的put操作是由Segment来完成的，下面我们继续往下挖，看代码清单4
代码清单4
static final class Segment<K,V> extends ReentrantLock implements Serializable {//继承ReetrantLock可重入锁
private static final long serialVersionUID = 2249069246763182397L;
static final int MAX_SCAN_RETRIES =
Runtime.getRuntime().availableProcessors() > 1 ? 64 : 1;
transient volatile HashEntry<K,V>[] table;//表组
transient int count;//表的长度
transient int modCount;//修改次数
transient int threshold;//阀值
final float loadFactor;//负载因子
Segment(float lf, int threshold, HashEntry<K,V>[] tab) {
this.loadFactor = lf;
this.threshold = threshold;
this.table = tab;
}
final V put(K key, int hash, V value, boolean onlyIfAbsent) {//put操作
HashEntry<K,V> node = tryLock() ? null :
scanAndLockForPut(key, hash, value);//保证能够获取到段锁，只有key不在该段内，node才不为null，其余情况node为null
V oldValue;
try {
HashEntry<K,V>[] tab = table;
int index = (tab.length - 1) & hash;//计算table数组的索引
HashEntry<K,V> first = entryAt(tab, index);
for (HashEntry<K,V> e = first;;) {
if (e != null) {//循环遍历链表，如果没有找到e=null然后跳转至else的分支代码中。
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 {
if (node != null)
node.setNext(first);//头插法
else
node = new HashEntry<K,V>(hash, key, value, first);//头插法
int c = count + 1;
if (c > threshold && tab.length < MAXIMUM_CAPACITY)//扩容处理
rehash(node);
else
setEntryAt(tab, index, node);
++modCount;
count = c;
oldValue = null;
break;
}
}
} finally {
unlock();
}
return oldValue;
}
@SuppressWarnings("unchecked")
private void rehash(HashEntry<K,V> node) {//这个函数的理解还是不容易的。
HashEntry<K,V>[] oldTable = table;
int oldCapacity = oldTable.length;
int newCapacity = oldCapacity << 1;//扩容方式为old*2.
threshold = (int)(newCapacity * loadFactor);//新的阀值
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];//遍历table数组，进而遍历单链表
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;
for (HashEntry<K,V> last = next;last != null;last = last.next) {//遍历单链表
int k = last.hash & sizeMask;
if (k != lastIdx) {
lastIdx = k;
lastRun = last;
}
}
newTable[lastIdx] = lastRun;
// Clone remaining nodes
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);
}
}
}
}
int nodeIndex = node.hash & sizeMask; // add the new node
node.setNext(newTable[nodeIndex]);
newTable[nodeIndex] = node;
table = newTable;
}
private HashEntry<K,V> scanAndLockForPut(K key, int hash, V value) {
HashEntry<K,V> first = entryForHash(this, hash);//根据hash值找到table的数组元素
HashEntry<K,V> e = first;
HashEntry<K,V> node = null;
int retries = -1; // 用来定位节点，如果为0则定位到包含key的节点
while (!tryLock()) {//循环检测锁，如果当前线程已经获取到锁，则跳出循环。
HashEntry<K,V> f; // to recheck first below
if (retries < 0) {//检索key的节点
if (e == null) {
if (node == null) // speculatively create node
node = new HashEntry<K,V>(hash, key, value, null);
retries = 0;
}
else if (key.equals(e.key))
retries = 0;
else
e = e.next;
}
else if (++retries > MAX_SCAN_RETRIES) {
lock();
break;
}
else if ((retries & 1) == 0 &&
(f = entryForHash(this, hash)) != first) {
e = first = f; // re-traverse if entry changed
retries = -1;
}
}
return node;
}
private void scanAndLock(Object key, int hash) {
// similar to but simpler than scanAndLockForPut
HashEntry<K,V> first = entryForHash(this, hash);
HashEntry<K,V> e = first;
int retries = -1;
while (!tryLock()) {
HashEntry<K,V> f;
if (retries < 0) {
if (e == null || key.equals(e.key))
retries = 0;
else
e = e.next;
}
else if (++retries > MAX_SCAN_RETRIES) {
lock();
break;
}
else if ((retries & 1) == 0 &&
(f = entryForHash(this, hash)) != first) {
e = first = f;
retries = -1;
}
}
}
final V remove(Object key, int hash, Object value) {
if (!tryLock())
scanAndLock(key, hash);
V oldValue = null;
try {
HashEntry<K,V>[] tab = table;
int index = (tab.length - 1) & hash;
HashEntry<K,V> e = entryAt(tab, index);
HashEntry<K,V> pred = null;
while (e != null) {
K k;
HashEntry<K,V> next = e.next;
if ((k = e.key) == key ||
(e.hash == hash && key.equals(k))) {
V v = e.value;
if (value == null || value == v || value.equals(v)) {
if (pred == null)
setEntryAt(tab, index, next);
else
pred.setNext(next);
++modCount;
--count;
oldValue = v;
}
break;
}
pred = e;
e = next;
}
} finally {
unlock();
}
return oldValue;
}
final boolean replace(K key, int hash, V oldValue, V newValue) {
if (!tryLock())
scanAndLock(key, hash);
boolean replaced = false;
try {
HashEntry<K,V> e;
for (e = entryForHash(this, hash); e != null; e = e.next) {
K k;
if ((k = e.key) == key ||
(e.hash == hash && key.equals(k))) {
if (oldValue.equals(e.value)) {
e.value = newValue;
++modCount;
replaced = true;
}
break;
}
}
} finally {
unlock();
}
return replaced;
}
final V replace(K key, int hash, V value) {
if (!tryLock())
scanAndLock(key, hash);
V oldValue = null;
try {
HashEntry<K,V> e;
for (e = entryForHash(this, hash); e != null; e = e.next) {
K k;
if ((k = e.key) == key ||
(e.hash == hash && key.equals(k))) {
oldValue = e.value;
e.value = value;
++modCount;
break;
}
}
} finally {
unlock();
}
return oldValue;
}
final void clear() {
lock();
try {
HashEntry<K,V>[] tab = table;
for (int i = 0; i < tab.length ; i++)
setEntryAt(tab, i, null);
++modCount;
count = 0;
} finally {
unlock();
}
}
}上面的代码清单4其实就是Segment类的代码，之前我们说过ConcurrentHashMap的put操作是由Segment的put来执行的。细心的读者可以看到Segment继承了ReentrantLock，也就是其内部是可以直接使用lock与unlock来进行同步操作的。从代码中我们可以看到其put操作是线程安全的，而且Segment的其他成员函数也是线程安全的。这里如果认真看了代码清单2，3，4的同学会发现segments数组的长度取决于构造函数指定的concurrencyLevel的值，在存储数据时并不会扩容segments的数组长度，在进行存储数据时，扩容的是segment的成员变量table数组的长度。
存储数据的姿势搞清楚之后，我们就看看怎么取我们的数据，请看代码清单5:
代码清单5
public V get(Object key) {
Segment<K,V> s; // manually integrate access methods to reduce overhead
HashEntry<K,V>[] tab;
int h = hash(key);
long u = (((h >>> segmentShift) & segmentMask) << SSHIFT) + SBASE;//计算索引
if ((s = (Segment<K,V>)UNSAFE.getObjectVolatile(segments, u)) != null &&
(tab = s.table) != null) {//通过CAS获索引处Segment对象，并进一步获得table的引用
for (HashEntry<K,V> e = (HashEntry<K,V>) UNSAFE.getObjectVolatile
(tab, ((long)(((tab.length - 1) & h)) << TSHIFT) + TBASE);//找到table索引处的单链表，并循环遍历
e != null; e = e.next) {
K k;
if ((k = e.key) == key || (e.hash == h && key.equals(k)))
return e.value;
}
}
return null;
}代码清单5没有什么可以过多的说的，就是定位索引，遍历单链表，找到返回对应值，否则返回null.如果大家明白了put的过程，get操作是很好理解的。
接下来我们看下ConcurrentHashMap是怎么统计目前包含多少键值对的，请看代码清单6:
代码清单6
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; // 是否溢出
long sum; // 修改次数
long last = 0L; // 上遍历时的修改次数
int retries = -1;
try {
for (;;) {
if (retries++ == RETRIES_BEFORE_LOCK) {// 这里注意只有可重锁的次数大于最大值时，才会对segments数组元素依次上锁
for (int j = 0; j < segments.length; ++j)
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)//如果相加为负数，则说明已经超过最大值，溢出，即overflow为true
overflow = true;
}
}
if (sum == last)//如果为true则代表，没有在累积键值对时，没有其他线程改变数据结构，则退出循环。
break;
last = sum;
}
} finally {
if (retries > RETRIES_BEFORE_LOCK) {//解锁
for (int j = 0; j < segments.length; ++j)
segmentAt(segments, j).unlock();
}
}
return overflow ? Integer.MAX_VALUE : size;
}上面的size函数首先不加锁循环执行以下操作：遍历segments数组元素，获得count和modCount的值并相加。如果连续两次所有的modcount相加结果相等，即last==sum，则过程中没有发生其他线程修改ConcurrentHashMap的情况，返回获得的值。当循环次数超过可重入最大值时，这时需要对所有的段组元素进行加锁，获取返回值后再依次解锁。值得注意的是，加锁过程中要强制创建所有的Segment，否则容易出现其他线程创建Segment并进行put，remove等操作。
要说的内容就这么多，如果文中有不对的地方，麻烦指出，如果喜欢我的文章，可以动动手指关注一下，赞一下，我会有更大的动力写出更多的文章，转载请注明出处：blog.csdn.net/android_jia…
