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数据结构
JDK1.7 ConcurrentHashMap 基于数组 + 链表，包含一个 Segment 数组，每个 Segment 中是又是一个数组 + 链表的数据结构(相当于一个 HashMap)，数组和链表存储的是一个个 HashEntry 对象
static final class Segment<K,V> extends ReentrantLock implements Serializable {
private static final long serialVersionUID = 2249069246763182397L;
static final int MAX_SCAN_RETRIES =
Runtime.getRuntime().availableProcessors() > 1 ? 64 : 1;
transient volatile HashEntry<K,V>[] table;
transient int count;
transient int modCount;
transient int threshold;
final float loadFactor;
}
static final class HashEntry<K,V> {
final int hash;
final K key;
volatile V value;
volatile HashEntry<K,V> next;
}罕用办法
应用
源码剖析
次要属性
// 默认的容量大小，即 HashEntry 中数组的容量之和，初始化时会平均分配到每个 Segment 中的 HashEntry 数组
static final int DEFAULT_INITIAL_CAPACITY = 16;
// 默认加载因子
static final float DEFAULT_LOAD_FACTOR = 0.75f;
// 默认的并发级别，决定了 Segment 数组的长度
static final int DEFAULT_CONCURRENCY_LEVEL = 16;
// 最大容量
static final int MAXIMUM_CAPACITY = 1 << 30;
// 每个 Segment 中的 HashEntry 数组最小容量
static final int MIN_SEGMENT_TABLE_CAPACITY = 2;
//Segment 的最大数量 =65536
static final int MAX_SEGMENTS = 1 << 16;
// 重试次数
static final int RETRIES_BEFORE_LOCK = 2;构造方法
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);
}
@SuppressWarnings("unchecked")
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;
int ssize = 1;
//ssize 即为 Segment 数组的长度，默认 concurrencyLevel=16，即 ssize=Segment 数组的长度 =16
while (ssize < concurrencyLevel) {
++sshift;
ssize <<= 1; // 乘以 2
}
this.segmentShift = 32 - sshift;
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;
//cap 即每个 Segment 中的 HashEntry 数组的长度，即 cap= 每个 Segment 中的 HashEntry 数组的长度 =2
while (cap < c)
cap <<= 1;
// 将 Segment 数组初始化长度为 16 并且只填充第 0 个元素，默认大小为 2，负载因子 0.75，扩容阀值是 2*0.75=1.5，插入第二个值时才会进行扩容
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;
}put()办法
public V put(K key, V value) {
Segment<K,V> s;
if (value == null)
throw new NullPointerException();
// 1. 依据 key 值，通过 hash（）计算出对应的 hash 值
// 2. 依据 hash 值计算出对应的 segment 数组下标
int hash = hash(key);
int j = (hash >>> segmentShift) & segmentMask;
if ((s = (Segment<K,V>)UNSAFE.getObject // nonvolatile; recheck
(segments, (j << SSHIFT) + SBASE)) == null) // in ensureSegment
//3. 如果 segment[j]==null，初始化 segment[j]
s = ensureSegment(j);
//4. 往 segment[j]增加 key-value
return s.put(key, hash, value, false);
}
final V put(K key, int hash, V value, boolean onlyIfAbsent) {
//tryLock 尝试加锁，如果加锁胜利，返回 null，否则执行 scanAndLockForPut 尝试自旋加锁
HashEntry<K,V> node = tryLock() ? null :
scanAndLockForPut(key, hash, value);
V oldValue;
try {
// 1. 依据 key 值，通过 hash（）计算出对应的 hash 值
// 2. 依据 hash 值计算出对应的 HashEntry 数组下标
HashEntry<K,V>[] tab = table;
int index = (tab.length - 1) & hash;
HashEntry<K,V> first = entryAt(tab, index);
// 通过遍历以该数组元素为头结点的链表
for (HashEntry<K,V> e = first;;) {
// 若头结点存在，遍历链表，若该 key 已存在，则用新 value 替换旧 value
if (e != null) {
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;
}
// 若头节点不存在或曾经遍历到了链表尾部
else {
// 若 node 不为 null，将 node 增加到 HashEntry 数组中, 这里采纳头插法
if (node != null)
node.setNext(first);
// 若 node 为 null，将 node 初始化后增加到 HashEntry 数组中, 这里采纳头插法
else
node = new HashEntry<K,V>(hash, key, value, first);
int c = count + 1;
// 键值对数量 size > 最大容量 threshold
if (c > threshold && tab.length < MAXIMUM_CAPACITY)
// 扩容
rehash(node);
else
setEntryAt(tab, index, node);
++modCount;
count = c;
oldValue = null;
break;
}
}
} finally {
// 解锁
unlock();}
return oldValue;
}
// 一直用 tryLock()自旋进行加锁，若达到自旋次数则调用 lock()阻塞获取锁
private HashEntry<K,V> scanAndLockForPut(K key, int hash, V value) {HashEntry<K,V> first = entryForHash(this, hash);
HashEntry<K,V> e = first;
HashEntry<K,V> node = null;
int retries = -1; // negative while locating node
while (!tryLock()) {
HashEntry<K,V> f; // to recheck first below
if (retries < 0) {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;
}
rehash()办法
//HashEntry 数组扩容为原来的两倍。老数组里的数据挪动到新数组时，地位要么不变，要么变为 index+ oldSize，应用头插法插入到新数组
private void rehash(HashEntry<K,V> node) {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;
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
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;
}get()办法
// 因为 HashEntry 中的 value 属性是用 volatile 关键词润饰的，保障了内存可见性，所以每次获取时都是最新值。ConcurrentHashMap 的 get 办法是十分高效的，因为整个过程都不须要加锁。public V get(Object key) {
Segment<K,V> s; // manually integrate access methods to reduce overhead
HashEntry<K,V>[] tab;
// 1. 依据 key 值，通过 hash（）计算出对应的 hash 值
int h = hash(key);
// 2. 依据 hash 值计算出对应的 segment 数组下标，失去 segment 数组
long u = (((h >>> segmentShift) & segmentMask) << SSHIFT) + SBASE;
if ((s = (Segment<K,V>)UNSAFE.getObjectVolatile(segments, u)) != null &&
(tab = s.table) != null) {
3. 依据 hash 值计算出对应的 HashEntry 数组下标，失去 HashEntry 数组，遍历数组
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;
//4. 找到对应的 key，返回 value
if ((k = e.key) == key || (e.hash == h && key.equals(k)))
return e.value;
}
}
return null;
}size()办法
// 计算两次，如果不变则返回计算结果，若不统一，则锁住所有的 Segment 求和
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)
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;
}总结
1.JDK1.7 ConcurrentHashMap 基于数组 + 链表，包含一个 Segment 数组，每个 Segment 中是又是一个数组 + 链表的数据结构 (相当于一个 HashMap)，数组和链表存储的是一个个 HashEntry 对象
2.Segment 继承于 ReentrantLock，实践上 ConcurrentHashMap 反对 CurrencyLevel(Segment 数组数量) 的线程并发。每当一个线程占用锁拜访一个 Segment 时，不会影响到其余的 Segment。
3. 增加 key-value 时会依据 key 值计算，依据 hash 值计算出对应的 segment 数组下标，对这个 segment 应用 tryLock 尝试加锁，如果加锁失败，执行 scanAndLockForPut 尝试自旋加锁直到胜利；后续流程与 HashMap 雷同。
4. 因为 HashEntry 中的 value 属性是用 volatile 关键词润饰的，保障了内存可见性，所以每次获取时都是最新值。ConcurrentHashMap 的 get 办法是十分高效的，因为整个过程都不须要加锁。
正文完
