HashMap并发问题
在多线程环境中，HashMap的put方法有可能会导致程序的死循环，这是因为多线程下可能会使HashMap形成环形链表，即链表的一个节点的next节点永不为null就会导致死循环，CPU100%。
HashMap死链的问题主要是在hashMap的扩容操作，也就是transfer()方法
void transfer(Entry[] newTable, boolean rehash) {
int newCapacity = newTable.length;
for (Entry<K,V> e : table) {
while(null != e) {
Entry<K,V> next = e.next;
//A
if (rehash) {
e.hash = null == e.key ? 0 : hash(e.key);
}
int i = indexFor(e.hash, newCapacity);
//将新元素加入 newTable[i], 原 newTable[i] 作为新元素的 next
e.next = newTable[i];
newTable[i] = e;
e = next;
}
}
}
- 在多线程情况下，假设该链表元素为：(1,35)->(35,16)->(16,null)
- 当我们线程一执行到A处被挂起此时局部变量e的值为 (1,35),next为： (35,16),
- 然后线程2开始执行，发生扩容，对链表的元素进行移动，扩容完成后，该链表元素为： (35,1)->(1,null)
- 然后切回线程1，此时变量e和next被恢复，引用没变但是内容发生改变，此时局部变量e的值变为(1,null),next为(35,1)，并链向(1,null)
- 然后将内容赋值给新链表，循环一次后，链表的内容为：(1,null)
- 第二次循环为后链表元素为：(35,1) -> (1,null)
- 因为线程2对链表进行了重组此时链表元素(35,1)指向(1,null),所以next = (1,null)
- 再次进行循环，e = (1,null),next = null 但是由于jdk7的头插法，e被放入了链表头，所有next变成了35 链表内容为(1,35)->(35,1)->(1,35),此时就发生了死链情况，也就是死循环
JDK1.8中将扩容算法做了调整，将头插法改为尾插法，避免了死链的问题，但仍不意味着能够在多线程环境下能够安全扩容，还会出现其它问题（如扩容丢数据）
解决方案
- 使用HashTable代替HashMap
- Collections.synchronizedMap将HashMap包装起来
- ConcurrentHashMap替换HashMap
HashTable虽然是线程安全的，但是效率低下，当一个线程访问HashTable的同步方法时其他线程如果也访问HashTable的同步方法，那么会进入阻塞或者轮询状态
ConcurrentHashMap 源码分析(1.8)
在JDK1.8中ConcurrentHashMap弃用了Segment分段锁机制，利用CAS+Synchronized来保证并发更新的安全，底层任然采用数组加链表的存储结构
1、属性
// 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 volatile+cas自旋锁
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> {}
//sizeCtl=0代表数组未初始化 >0 如果数组未初始化，那么其记录的是数组的初始容量，如果数组已经初始化，那么其记录的是数组的扩容阈值
// = -1 代表数组正在进行初始化
//<0 != -1 表示数组正在扩容， -(1+n)，表示此时有n个线程正在共同完成数组的扩容操作
private transient volatile int sizeCtl;
3、构造函数
/**
* 初始容量 负载因子(默认0.75) 并发级别
* 这里采用了懒汉式的方式，构造只初始化大小的属性，不真正创建
*/
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
//根据负载因子以及初始长度计算容量
long size = (long)(1.0 + (long)initialCapacity / loadFactor);
//tableSizeFor方法保证计算的值为2的n次方
int cap = (size >= (long)MAXIMUM_CAPACITY) ?
MAXIMUM_CAPACITY : tableSizeFor((int)size);
this.sizeCtl = cap;
}
get()
public V get(Object key) {
Node<K,V>[] tab; Node<K,V> e, p; int n, eh; K ek;
//spread保证计算的hash值不为负数
int h = spread(key.hashCode());
if ((tab = table) != null && (n = tab.length) > 0 &&
//根据hash找到元素所在的数组下标找到链表
(e = tabAt(tab, (n - 1) & h)) != null) {
//如果头节点就是要查找的key就直接返回
if ((eh = e.hash) == h) {
if ((ek = e.key) == key || (ek != null && key.equals(ek)))
return e.val;
}
//如果hash为负数则表示该bin在扩容或者为树形，这是调用find方法来查找
else if (eh < 0)
return (p = e.find(h, key)) != null ? p.val : null;
//循环遍历链表
while ((e = e.next) != null) {
if (e.hash == h &&
((ek = e.key) == key || (ek != null && key.equals(ek))))
return e.val;
}
}
return null;
}
put()添加元素
当添加元素时，会针对当前元素所对应的通位进行加锁操作，这样一方面保证元素添加时多线程的安全，提示对某个桶位加锁不会影响其他桶位的操作，进一步提升多线程的并发效率
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();
//计算hash值
int hash = spread(key.hashCode());
int binCount = 0;
for (Node<K,V>[] tab = table;;) {
//f是链表头节点，fh是链表头节点的hash i是链表在数组中的下标
Node<K,V> f; int n, i, fh;
//如果第一次添加就去初始化数组 使用cas 无需synchronized 创建成功 进入下一轮循环
if (tab == null || (n = tab.length) == 0)
tab = initTable();
//创建链表头节点
else if ((f = tabAt(tab, i = (n - 1) & hash)) == null) {
//使用cas自旋添加链表头
if (casTabAt(tab, i, null,
new Node<K,V>(hash, key, value, null)))
break; // no lock when adding to empty bin
}
//如果hash为-1则代表正在扩容，则当前线程会帮忙进行扩容
else if ((fh = f.hash) == MOVED)
tab = helpTransfer(tab, f);
else {
V oldVal = null;
//使用synchronized锁住当前链表头节点
synchronized (f) {
//确认头节点没有被移动
if (tabAt(tab, i) == f) {
//链表结构
if (fh >= 0) {
binCount = 1;
//遍历链表
for (Node<K,V> e = f;; ++binCount) {
K ek;
//找到相同的key就赋值然后跳出循环
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;
//遍历到最后节点还没有相同的key就增加node节点 至链表末尾
if ((e = e.next) == null) {
pred.next = new Node<K,V>(hash, key,
value, null);
break;
}
}
}
//红黑树结构
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;
}
}
}
//释放锁
}
if (binCount != 0) {
//如果链表长度 >= 树化阈值就将链表转为红黑树
if (binCount >= TREEIFY_THRESHOLD)
treeifyBin(tab, i);
if (oldVal != null)
return oldVal;
break;
}
}
}
// 增加 size 计数
addCount(1L, binCount);
return null;
}
initTable()：初始化方法
private final Node<K,V>[] initTable() {
Node<K,V>[] tab; int sc;
while ((tab = table) == null || tab.length == 0) {
//如果sizeCtl < 0代表有线程正在初始化数组，则当前线程就yield让出cpu资源
if ((sc = sizeCtl) < 0)
Thread.yield(); // lost initialization race; just spin
//尝试将sizectl设置为-1代表正在初始化数组
else if (U.compareAndSwapInt(this, SIZECTL, sc, -1)) {
//获得锁，去创建数组
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<?,?>[n];
table = tab = nt;
sc = n - (n >>> 2);
}
} finally {
sizeCtl = sc;
}
break;
}
}
return tab;
}
addCount(long x, int check)
// check 是之前 binCount 的个数
private final void addCount(long x, int check) {
CounterCell[] as; long b, s;
// 已经有了 counterCells, 向 cell 累加
if ((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;
// 还没有 counterCells
if (as == null || (m = as.length - 1) < 0 ||
(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 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
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;
// 将 baseCount 计数与所有 cell 计数累加
long sum = baseCount;
if (as != null) {
for (int i = 0; i < as.length; ++i) {
if ((a = as[i]) != null)
sum += a.value;
}
}
return sum;
}
扩容安全
transfer()源码
private final void transfer(Node<K,V>[] tab, Node<K,V>[] nextTab) {
int n = tab.length, stride;
//如果是多CPU，那么每个线程划分任务，最小任务量是16个桶位的迁移
if ((stride = (NCPU > 1) ? (n >>> 3) / NCPU : n) < MIN_TRANSFER_STRIDE)
stride = MIN_TRANSFER_STRIDE; // subdivide range
//扩容线程新数组为null
if (nextTab == null) { // initiating
try {
@SuppressWarnings("unchecked")
//两倍扩容创建新数组
Node<K,V>[] nt = (Node<K,V>[])new Node<?,?>[n << 1];
nextTab = nt;
} catch (Throwable ex) { // try to cope with OOME
sizeCtl = Integer.MAX_VALUE;
return;
}
nextTable = nextTab;
//记录线程开始迁移的桶位，从后往前迁移
transferIndex = n;
}
//记录新数组的长度
int nextn = nextTab.length;
//已经迁移的桶位会用forwardingNode节点占位
ForwardingNode<K,V> fwd = new ForwardingNode<K,V>(nextTab);
boolean advance = true;
boolean finishing = false; // to ensure sweep before committing nextTab
for (int i = 0, bound = 0;;) {
Node<K,V> f; int fh;
while (advance) {
int nextIndex, nextBound;
//i代表当前正在迁移的桶位的索引值 bound代表下一次任务迁移开始的桶位
//如果--i >= bound 则代表当前线程分配的迁移任务还没有完成
if (--i >= bound || finishing)
advance = false;
//没有元素需要迁移 后续会将扩容线程数-1 并哦按段扩容是否完成
else if ((nextIndex = transferIndex) <= 0) {
i = -1;
advance = false;
}
//计算下一次任务迁移的开始桶位，并复制诶transferIndex
else if (U.compareAndSwapInt
(this, TRANSFERINDEX, nextIndex,
nextBound = (nextIndex > stride ?
nextIndex - stride : 0))) {
bound = nextBound;
i = nextIndex - 1;
advance = false;
}
}
//没有其他需要迁移的桶
if (i < 0 || i >= n || i + n >= nextn) {
int sc;
//扩容结束后就保存新数组，并计算扩容阈值 赋值给sizeCtl
if (finishing) {
nextTable = null;
table = nextTab;
sizeCtl = (n << 1) - (n >>> 1);
return;
}
//扩容任务数-1
if (U.compareAndSwapInt(this, SIZECTL, sc = sizeCtl, sc - 1)) {
//判断当前所有客人任务线程是否都执行完成
if ((sc - 2) != resizeStamp(n) << RESIZE_STAMP_SHIFT)
return;
finishing = advance = true;
i = n; // recheck before commit
}
}
//如果当前迁移的桶位没有元素，则直接在该位置添加一个fwd节点
else if ((f = tabAt(tab, i)) == null)
advance = casTabAt(tab, i, null, fwd);
//当前节点已被迁移
else if ((fh = f.hash) == MOVED)
advance = true; // already processed
else {
//加锁迁移
synchronized (f) {
if (tabAt(tab, i) == f) {
Node<K,V> ln, hn;
if (fh >= 0) {
int runBit = fh & n;
Node<K,V> lastRun = f;
for (Node<K,V> p = f.next; p != null; p = p.next) {
int b = p.hash & n;
if (b != runBit) {
runBit = b;
lastRun = p;
}
}
if (runBit == 0) {
ln = lastRun;
hn = null;
}
else {
hn = lastRun;
ln = null;
}
for (Node<K,V> p = f; p != lastRun; p = p.next) {
int ph = p.hash; K pk = p.key; V pv = p.val;
if ((ph & n) == 0)
ln = new Node<K,V>(ph, pk, pv, ln);
else
hn = new Node<K,V>(ph, pk, pv, hn);
}
setTabAt(nextTab, i, ln);
setTabAt(nextTab, i + n, hn);
setTabAt(tab, i, fwd);
advance = true;
}
else if (f instanceof TreeBin) {
TreeBin<K,V> t = (TreeBin<K,V>)f;
TreeNode<K,V> lo = null, loTail = null;
TreeNode<K,V> hi = null, hiTail = null;
int lc = 0, hc = 0;
for (Node<K,V> e = t.first; e != null; e = e.next) {
int h = e.hash;
TreeNode<K,V> p = new TreeNode<K,V>
(h, e.key, e.val, null, null);
if ((h & n) == 0) {
if ((p.prev = loTail) == null)
lo = p;
else
loTail.next = p;
loTail = p;
++lc;
}
else {
if ((p.prev = hiTail) == null)
hi = p;
else
hiTail.next = p;
hiTail = p;
++hc;
}
}
ln = (lc <= UNTREEIFY_THRESHOLD) ? untreeify(lo) :
(hc != 0) ? new TreeBin<K,V>(lo) : t;
hn = (hc <= UNTREEIFY_THRESHOLD) ? untreeify(hi) :
(lc != 0) ? new TreeBin<K,V>(hi) : t;
setTabAt(nextTab, i, ln);
setTabAt(nextTab, i + n, hn);
setTabAt(tab, i, fwd);
advance = true;
}
}
}
}
}
}
jdk8 使用数组+链表+红黑树的结构
- 初始化，使用cas来保证并发安全，懒惰初始化table
- 树化，当数组长度 < 64 时，会先尝试扩容，如果扩容到64 并且链表长度依旧大于8，此时会将该链表树化，树化过程会有synchronized锁住链表头
- put，如果该链表尚未创建，只需要使用cas来创建bin，如果已经创建了，就锁住链表头进行put操作，使用尾插法插入链表尾部
- 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：扩容时以链表为单位进行，需要对链表进行synchronized，但是此时其他竞争线程并不是阻塞等待，而是会帮组其他链表进行扩容，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
ConturrentHashMap源码分析（JDK1.7）
ConcurrentHashMap在JDK1.7采用分段所的机制，实现并发的更新操作，底层由Segment数组和HashEntry数组组成。Segment继承自ReentrantLock来充当锁的角色，每个Segment对象守护每个散列映射表的若干个桶，HashEntry用来封装映射表的键值对，每个Segment元素中保存了一个默认长度为2的HashEntry[]
重要属性 HashEntry：HashEntry是ConcurrentHashMap中存储数据的对象
static final class HashEntry<K,V> {
//hash值
final int hash;
//键
final K key;
//值 使用volatile保证并发时数据获取的可见性
volatile V value;
//下一个元素
volatile HashEntry<K,V> next;
HashEntry(int hash, K key, V value, HashEntry<K,V> next) {
this.hash = hash;
this.key = key;
this.value = value;
this.next = next;
}
}
segment
构造方法
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;
//计算segment[]长度，确保为2的幂次方
while (ssize < concurrencyLevel) {
++sshift;
ssize <<= 1;
}
this.segmentShift = 32 - sshift;
this.segmentMask = ssize - 1;
if (initialCapacity > MAXIMUM_CAPACITY)
initialCapacity = MAXIMUM_CAPACITY;
//计算每个segment中的元素个数
int c = initialCapacity / ssize;
if (c * ssize < initialCapacity)
++c;
int cap = MIN_SEGMENT_TABLE_CAPACITY;
//矫正segment中存储元素的个数，保证时2的幂次方
while (cap < c)
cap <<= 1;
// create segments and segments[0]
//根据cap和负载因子等属性创建模板segment对象
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];
//使用unsafe类将创建的segment对象存入0角标位置
UNSAFE.putOrderedObject(ss, SBASE, s0); // ordered write of segments[0]
this.segments = ss;
}
put方法
public V put(K key, V value) {
Segment<K,V> s;
if (value == null)
throw new NullPointerException();
//计算Hash值
int hash = hash(key);
//根据hash值计算segment[]的索引
int j = (hash >>> segmentShift) & segmentMask;
//判断该索引位的segment对象是否创建，没有的话就去创建
if ((s = (Segment<K,V>)UNSAFE.getObject // nonvolatile; recheck
(segments, (j << SSHIFT) + SBASE)) == null) // in ensureSegment
s = ensureSegment(j);
//调用segment的put方法实现元素的添加
return s.put(key, hash, value, false);
}
ensureSegment方法 该方法的作用是创建当前索引位的Segment对象并返回
private Segment<K,V> ensureSegment(int k) {
final Segment<K,V>[] ss = this.segments;
long u = (k << SSHIFT) + SBASE; // raw offset
Segment<K,V> seg;
if ((seg = (Segment<K,V>)UNSAFE.getObjectVolatile(ss, u)) == null) {
//根据初始化时0角标的segment模板对象创建
Segment<K,V> proto = ss[0]; // use segment 0 as prototype
int cap = proto.table.length;
float lf = proto.loadFactor;
int threshold = (int)(cap * lf);
HashEntry<K,V>[] tab = (HashEntry<K,V>[])new HashEntry[cap];
//在创建前再判断是否为null
if ((seg = (Segment<K,V>)UNSAFE.getObjectVolatile(ss, u))
== null) { // recheck
//创建
Segment<K,V> s = new Segment<K,V>(lf, threshold, tab);
//通过cas紫炫方式将Segment对象放到sement[]中，确保线程的安全
while ((seg = (Segment<K,V>)UNSAFE.getObjectVolatile(ss, u))
== null) {
if (UNSAFE.compareAndSwapObject(ss, u, null, seg = s))
break;
}
}
}
return seg;
}
Segment的put方法
final V put(K key, int hash, V value, boolean onlyIfAbsent) {
//尝试获取lock锁，如果获取成功 node为null，如果由其他线程占据锁对象，那么去做别的事情，提升效率
HashEntry<K,V> node = tryLock() ? null :
scanAndLockForPut(key, hash, value);
V oldValue;
try {
HashEntry<K,V>[] tab = table;
//计算hashEntry的索引
int index = (tab.length - 1) & hash;
//获取所有位ide元素对象
HashEntry<K,V> first = entryAt(tab, index);
for (HashEntry<K,V> e = first;;) {
//如果获取的元素的不为空
if (e != null) {
K k;
//如果时重复的元素，则覆盖原值
if ((k = e.key) == key ||
(e.hash == hash && key.equals(k))) {
oldValue = e.value;
if (!onlyIfAbsent) {
e.value = value;
++modCount;
}
break;
}
//如果不是重复元素，则获取链表下一个元素，循环遍历链表
e = e.next;
}
else {
//如果当前获取到的元素为空，并且HashEntry对象已经创建，则使用头插法关联
if (node != null)
node.setNext(first);
else
//创建当前添加的键值对的HashEntry对象
node = new HashEntry<K,V>(hash, key, value, first);
//添加的元素数量+1
int c = count + 1;
//判断是否需要扩容
if (c > threshold && tab.length < MAXIMUM_CAPACITY)
rehash(node);
else
//将当前添加的元素对象存入数组角标位
setEntryAt(tab, index, node);
++modCount;
count = c;
oldValue = null;
break;
}
}
} finally {
unlock();
}
return oldValue;
}
Segment的scanAndLockForPut方法
该方法再没有获取到锁的情况下，去完成HashEntry对象的创建，提升效率
private HashEntry<K,V> scanAndLockForPut(K key, int hash, V value) {
//获取头部元素
HashEntry<K,V> first = entryForHash(this, hash);
HashEntry<K,V> e = first;
HashEntry<K,V> node = null;
int retries = -1; // negative while locating node
//尝试获取锁失败
while (!tryLock()) {
HashEntry<K,V> f; // to recheck first below
if (retries < 0) {
if (e == null) {
//如果没有下一个节点并且也不是重复元素，就直接去创建HashEntry对象
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扩容方法
private void rehash(HashEntry<K,V> node) {
HashEntry<K,V>[] oldTable = table;
int oldCapacity = oldTable.length;
//两倍扩容
int newCapacity = oldCapacity << 1;
threshold = (int)(newCapacity * loadFactor);
//基于新的容量创建HashEntry数组
HashEntry<K,V>[] newTable =
(HashEntry<K,V>[]) new HashEntry[newCapacity];
int sizeMask = newCapacity - 1;
//进行数据迁移
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;
}
