-
原理
-
TransferQueue
-
LinkedTransferQueue结构-Node
-
Node节点
-
Node节点源码
-
LinkedTransferQueue结构源码
-
核心方法
-
put-offer-add
-
untimed poll-tryTransfer
-
transfer-take
-
超时的poll-tryTransfer
-
核心xfer
-
其他辅助方法
-
Example
前端妹子推荐Markdown排版,尝试下看看效果如何。
JUC集合队列的最后一个,LinkedTransferQueue是个好东西,利用链表FIFO实现无界队列,看到有说法说是ConcurrentLinkedQueue、SynchronousQueue (公平模式下)、无界的LinkedBlockingQueues等的超集,看完源码,感觉是有点这个意思。
BlockingQueue的是队列满了以后你再入队会阻塞,take的时候队列空也会阻塞;SynchronousQueue是一个取必须对应着一个入;而ConcurrentLinkedQueue则使用的wait-free算法解决并发问题。
原理
个人感觉先记得原理再去看这个queue更好,要不然累死。LinkedTransferQueue采用的一种预占模式。意思就是消费者线程取元素时,如果队列为空,那就生成一个节点(节点元素为null)入队,然后消费者线程park住,后面生产者线程入队时发现有一个元素为null的节点,生产者线程就不入队了,直接就将元素填充到该节点,唤醒该节点上park住线程,被唤醒的消费者线程拿货走人。这就是预占的意思:有就拿货走人,没有就占个位置等着,等到或超时。
TransferQueue
LinkedTransferQueue实现了TransferQueue接口,这个接口继承了BlockingQueue。之前BlockingQueue是队列满时再入队会阻塞,而这个接口实现的功能是队列不满时也可以阻塞,实现一种有阻塞的入队功能。而这个接口在之前SynChronousQueue内种也有体现,作为内部抽象类Transferer,然后公平非公平2中实现,可以体会下。看下TransferQueue接口的代码:
public interface TransferQueue<E> extends BlockingQueue<E> {
/**
* 立即转交一个元素给消费者,如果此时队列没有消费者,那就false
*/
boolean tryTransfer(E e);
/**
* 转交一个元素给消费者,如果此时队列没有消费者,那就阻塞
*/
void transfer(E e) throws InterruptedException;
/**
* 带超时的tryTransfer
*/
boolean tryTransfer(E e, long timeout, TimeUnit unit)
throws InterruptedException;
/**
* 是否有消费者等待接收数据,瞬时状态,不一定准
*/
boolean hasWaitingConsumer();
/**
* 返回还有多少个等待的消费者,跟上面那个一样,都是一种瞬时状态,不一定准
*/
int getWaitingConsumerCount();
}
LinkedTransferQueue结构-Node
Node节点
先看下大概样子:
isData | item | next | waiter |
---|
isData:表示该节点是存放数据还是获取数据;
item:存放数据,isData为false时,该节点为null,为true时,匹配后,该节点会置为null;
next:指向下一个节点;
waiter:上面原理部分说的会park住消费者线程,线程就放在这里。
Node节点源码
static final class Node {
final boolean isData; // 如果是请求时是为false
volatile Object item; // isData为true时,item存放数据,后面匹配后置为null
volatile Node next;
volatile Thread waiter; // 请求时的park住的消费者线程
// CAS methods for fields
final boolean casNext(Node cmp, Node val) {
return UNSAFE.compareAndSwapObject(this, nextOffset, cmp, val);
}
final boolean casItem(Object cmp, Object val) {
// assert cmp == null || cmp.getClass() != Node.class;
return UNSAFE.compareAndSwapObject(this, itemOffset, cmp, val);
}
/**
* Constructs a new node. Uses relaxed write because item can
* only be seen after publication via casNext.
*/
Node(Object item, boolean isData) {
UNSAFE.putObject(this, itemOffset, item); // relaxed write
this.isData = isData;
}
/**
* 更新头节点后会将原来head节点的next指向自己for gc
*/
final void forgetNext() {
UNSAFE.putObject(this, nextOffset, this);
}
/**
* 匹配过或节点被取消的时候会调用
*/
final void forgetContents() {
UNSAFE.putObject(this, itemOffset, this);
UNSAFE.putObject(this, waiterOffset, null);
}
/**
* 节点是否匹配过了,如果匹配或者取消,item会有变化,也会调用上面那个forgetContents(),item会指向自己
*/
final boolean isMatched() {
Object x = item;
return (x == this) || ((x == null) == isData);
}
/**
* 是否是一个未匹配的请求节点,如果是的话,那么isData为false,item为null,如果匹配,item会有值的
*/
final boolean isUnmatchedRequest() {
return !isData && item == null;
}
/**
* 如给定节点类型不能挂在当前节点后返回true
* 满足节点类型不同且当前节点还未匹配,未匹配参考下上面的isMatched()方法
*/
final boolean cannotPrecede(boolean haveData) {
boolean d = isData;
Object x;
return d != haveData && (x = item) != this && (x != null) == d;
}
/**
* 匹配一个数据节点 -- used by remove.
*/
final boolean tryMatchData() {
// assert isData;
Object x = item;
if (x != null && x != this && casItem(x, null)) {
LockSupport.unpark(waiter);
return true;
}
return false;
}
private static final long serialVersionUID = -3375979862319811754L;
// Unsafe mechanics
private static final sun.misc.Unsafe UNSAFE;
private static final long itemOffset;
private static final long nextOffset;
private static final long waiterOffset;
static {
try {
UNSAFE = sun.misc.Unsafe.getUnsafe();
Class k = Node.class;
itemOffset = UNSAFE.objectFieldOffset
(k.getDeclaredField("item"));
nextOffset = UNSAFE.objectFieldOffset
(k.getDeclaredField("next"));
waiterOffset = UNSAFE.objectFieldOffset
(k.getDeclaredField("waiter"));
} catch (Exception e) {
throw new Error(e);
}
}
}
Node节点需要注意的是:匹配后节点的item的变化,以及搭配isData来综合判断是否匹配过isMatched()
。
Node | node1(isData-item) | node2(isData-item) |
---|---|---|
匹配前 | true-item | false-null |
匹配后 | true-null | false-this |
LinkedTransferQueue结构源码
/** 判断多核 */
private static final boolean MP =
Runtime.getRuntime().availableProcessors() > 1;
/**
* 作为第一个等待节点在阻塞park前自旋次数
*/
private static final int FRONT_SPINS = 1 << 7;
/**
* 前驱节点正在处理,当前节点需要自旋的次数
*/
private static final int CHAINED_SPINS = FRONT_SPINS >>> 1;
/**
* The maximum number of estimated removal failures (sweepVotes)
* to tolerate before sweeping through the queue unlinking
* cancelled nodes that were not unlinked upon initial
* removal. See above for explanation. The value must be at least
* two to avoid useless sweeps when removing trailing nodes.
*/
static final int SWEEP_THRESHOLD = 32;
/** head of the queue; null until first enqueue */
transient volatile Node head;
/** tail of the queue; null until first append */
private transient volatile Node tail;
/** The number of apparent failures to unsplice removed nodes */
private transient volatile int sweepVotes;
// CAS methods for fields
private boolean casTail(Node cmp, Node val) {
return UNSAFE.compareAndSwapObject(this, tailOffset, cmp, val);
}
private boolean casHead(Node cmp, Node val) {
return UNSAFE.compareAndSwapObject(this, headOffset, cmp, val);
}
private boolean casSweepVotes(int cmp, int val) {
return UNSAFE.compareAndSwapInt(this, sweepVotesOffset, cmp, val);
}
/*
* 调用xfer时候需要传入,区分不同处理
*/
private static final int NOW = 0; // for untimed poll, tryTransfer
private static final int ASYNC = 1; // for offer, put, add
private static final int SYNC = 2; // for transfer, take
private static final int TIMED = 3; // for timed poll, tryTransfer
public LinkedTransferQueue() {
}
结构就是一个head一个tail,构造为空,最重要的是:
private static final int NOW = 0; // for untimed poll, tryTransfer
private static final int ASYNC = 1; // for offer, put, add
private static final int SYNC = 2; // for transfer, take
private static final int TIMED = 3; // for timed poll, tryTransfer
调用核心方法xfer(E e, boolean haveData, int how, long nanos)
方法时传入参数(how),用于区分不同操作。
核心方法
put-offer-add
public void put(E e) {
xfer(e, true, ASYNC, 0);
}
public boolean offer(E e, long timeout, TimeUnit unit) {
xfer(e, true, ASYNC, 0);
return true;
}
public boolean offer(E e) {
xfer(e, true, ASYNC, 0);
return true;
}
public boolean add(E e) {
xfer(e, true, ASYNC, 0);
return true;
}
这几个BlockingQueue的实现方法,因为LinkedTransferQueue队列是无界的,不会阻塞,所以在调用xfer()
的时候传入的都是ASYNC,直接返回true。
untimed poll-tryTransfer
public boolean tryTransfer(E e) {
return xfer(e, true, NOW, 0) == null;
}
public E poll() {
return xfer(null, false, NOW, 0);
}
2者都是尝试下,也不会阻塞,传入xfer()
的是now,tryTransfer将元素转交给消费者线程,不会入队,poll是出队。
transfer-take
public void transfer(E e) throws InterruptedException {
if (xfer(e, true, SYNC, 0) != null) {
Thread.interrupted(); // failure possible only due to interrupt
throw new InterruptedException();
}
}
public E take() throws InterruptedException {
E e = xfer(null, false, SYNC, 0);
if (e != null)
return e;
Thread.interrupted();
throw new InterruptedException();
}
这2个方法需要阻塞。
超时的poll-tryTransfer
public boolean tryTransfer(E e, long timeout, TimeUnit unit)
throws InterruptedException {
if (xfer(e, true, TIMED, unit.toNanos(timeout)) == null)
return true;
if (!Thread.interrupted())
return false;
throw new InterruptedException();
}
public E poll(long timeout, TimeUnit unit) throws InterruptedException {
E e = xfer(null, false, TIMED, unit.toNanos(timeout));
if (e != null || !Thread.interrupted())
return e;
throw new InterruptedException();
}
这2个超时的也需要阻塞,使用TIMED区分SYNC。
核心xfer()
/**
* 所有入队出队都调用该方法
* @param e the item or null for take
* @param haveData true if this is a put, else a take
* @param how NOW, ASYNC, SYNC, or TIMED
* @param nanos timeout in nanosecs, used only if mode is TIMED
* @return an item if matched, else e
* @throws NullPointerException if haveData mode but e is null
*/
private E xfer(E e, boolean haveData, int how, long nanos) {
if (haveData && (e == null)) //put时非空校验
throw new NullPointerException();
Node s = null; // the node to append, if needed
retry:
for (;;) { // restart on append race
for (Node h = head, p = h; p != null;) { // 从head开始查找匹配的节点,p为null队列为空
boolean isData = p.isData;
Object item = p.item;
if (item != p && (item != null) == isData) { // 如果找到的节点没有匹配过
if (isData == haveData) // 节点类型跟待处理的类型一样,那肯定不行,例如找到的是一个data节点,匹配的肯定是一个false的reservation,你给一个data节点来匹配肯定不行
break;
if (p.casItem(item, e)) { // 可以匹配,那就casItem,2中情况,如果p的item原来是data,那么匹配后item为null,原来为null,现在有值了
for (Node q = p; q != h;) { //这里是帮助推进head节点,跟之前的SynchronousQueue类似效果
Node n = q.next; // update by 2 unless singleton
if (head == h && casHead(h, n == null ? q : n)) {
h.forgetNext();
break;
} // advance and retry
if ((h = head) == null ||
(q = h.next) == null || !q.isMatched())
break; // unless slack < 2
}
LockSupport.unpark(p.waiter); //匹配后将p上park的线程unpark,还是2种情况
return this.<E>cast(item); //返回item
}
}
Node n = p.next; //如果上面找到的节点已经匹配过了,那就往后再找
p = (p != n) ? n : (h = head); // 如果p的next指向p本身,说明p节点已经有其他线程处理过了,只能从head重新开始
}
if (how != NOW) { // 如果上面没有找到匹配的,对不同how进来的处理不同,NOW为untimed poll, tryTransfer,不需要入队
if (s == null)
s = new Node(e, haveData);
Node pred = tryAppend(s, haveData); //append节点,返回前驱节点
if (pred == null)
continue retry; // 返回的前驱节点为null,那就是有race,被其他的抢了,那就continue 整个for
if (how != ASYNC) //这里就是SYNC = 2; transfer, take 和TIMED = 3; timed poll, tryTransfer需要阻塞等待匹配
return awaitMatch(s, pred, e, (how == TIMED), nanos);
}
return e; // Now 和 ASYNC = 1; for offer, put, add,无界队列返回就是
}
}
我觉得大体流程还算清晰,总结下:
1、 findmatch,主要是判断匹配条件,节点本身还未匹配,且isData类型和待匹配的不一样就行,匹配后就是casItem,unpark匹配节点waiter,返回就是;
2、 unmatched,如果没找到,那就根据不同方法入参how处理了,now的就直接返回,其他的3种先入队,然后ASYNC入队后返回,SYNC和TIMED阻塞等待匹配;
其他辅助方法
/** append一个节点到tail */
private Node tryAppend(Node s, boolean haveData) {
for (Node t = tail, p = t;;) { // 从tail节点开始
Node n, u; // temps for reads of next & tail
if (p == null && (p = head) == null) { //队列空
if (casHead(null, s)) //将节点设置成head
return s; // initialize
}
else if (p.cannotPrecede(haveData))
return null; // lost race vs opposite mode
else if ((n = p.next) != null) // not last; keep traversing
p = p != t && t != (u = tail) ? (t = u) : // stale tail
(p != n) ? n : null; // restart if off list
else if (!p.casNext(null, s))
p = p.next; // re-read on CAS failure
else {
if (p != t) { // update if slack now >= 2
while ((tail != t || !casTail(t, s)) &&
(t = tail) != null &&
(s = t.next) != null && // advance and retry
(s = s.next) != null && s != t);
}
return p;
}
}
}
/** 等待匹配或者超时时间到,大体流程跟SynchronousQueue的那个awaitFulfill类似 */
private E awaitMatch(Node s, Node pred, E e, boolean timed, long nanos) {
long lastTime = timed ? System.nanoTime() : 0L;
Thread w = Thread.currentThread();
int spins = -1; // initialized after first item and cancel checks
ThreadLocalRandom randomYields = null; // bound if needed
for (;;) {
Object item = s.item;
if (item != e) { // 匹配后,xfer会有个casItem操作,这里park被唤醒后检查是否有变化
// assert item != s;
s.forgetContents(); // avoid garbage
return this.<E>cast(item);
}
if ((w.isInterrupted() || (timed && nanos <= 0)) &&
s.casItem(e, s)) { // 超时了
unsplice(pred, s); //将节点unlink
return e;
}
if (spins < 0) { // 自旋 establish spins at/near front
if ((spins = spinsFor(pred, s.isData)) > 0) //自旋次数
randomYields = ThreadLocalRandom.current();
}
else if (spins > 0) { // spin
--spins;
if (randomYields.nextInt(CHAINED_SPINS) == 0) //这里没太明白为什么要yield
Thread.yield(); // occasionally yield
}
else if (s.waiter == null) {
s.waiter = w; // park前肯定会调用一次
}
else if (timed) { //超时的park
long now = System.nanoTime();
if ((nanos -= now - lastTime) > 0)
LockSupport.parkNanos(this, nanos);
lastTime = now;
}
else {
LockSupport.park(this); //没有超时的park
}
}
}
/** 将节点s从队列断开 */
final void unsplice(Node pred, Node s) {
s.forgetContents(); // forget unneeded fields
/*
* See above for rationale. Briefly: if pred still points to
* s, try to unlink s. If s cannot be unlinked, because it is
* trailing node or pred might be unlinked, and neither pred
* nor s are head or offlist, add to sweepVotes, and if enough
* votes have accumulated, sweep.
*/
if (pred != null && pred != s && pred.next == s) {
Node n = s.next;
if (n == null ||
(n != s && pred.casNext(s, n) && pred.isMatched())) {
for (;;) { // check if at, or could be, head
Node h = head;
if (h == pred || h == s || h == null)
return; // at head or list empty
if (!h.isMatched())
break;
Node hn = h.next;
if (hn == null)
return; // now empty
if (hn != h && casHead(h, hn)) //推进head节点
h.forgetNext(); // advance head
}
if (pred.next != pred && s.next != s) { // recheck if offlist
for (;;) { // 通过sweepVotes变量控制到达足够次数后清除matched节点
int v = sweepVotes;
if (v < SWEEP_THRESHOLD) {
if (casSweepVotes(v, v + 1))
break;
}
else if (casSweepVotes(v, 0)) {
sweep();
break;
}
}
}
}
}
}
/** 通过pre节点计算自旋次数 */
private static int spinsFor(Node pred, boolean haveData) {
if (MP && pred != null) { //必须多核
if (pred.isData != haveData) // phase change
return FRONT_SPINS + CHAINED_SPINS;
if (pred.isMatched()) // pre已经匹配了,那就可以少自旋一些 probably at front
return FRONT_SPINS;
if (pred.waiter == null) // pre节点在匹配中了,那可以再少自旋一点 pred apparently spinning
return CHAINED_SPINS;
}
return 0;
}
主流程看完,其他不看了,unsplice()
方法的细节有些不清楚,还需要再看看深挖下。
Example
这里的东西是从参考1那个哥们的文章里面看到的,感觉放在最后,看完源码后,看这个能加深对LinkedTransferQueue的理解,感谢那位哥们!
1:Head->Data Input->Data
Match: 根据他们的属性 发现 cannot match ,因为是同类的
处理节点: 所以把新的data放在原来的data后面,然后head往后移一位,Reservation同理
HEAD=DATA->DATA
2:Head->Data Input->Reservation (取数据)
Match: 成功match,就把Data的item变为reservation的值(null,有主了),并且返回数据。
处理节点: 没动,head还在原地
HEAD=DATA(用过)
3:Head->Reservation Input->Data(放数据)
Match: 成功match,就把Reservation的item变为Data的值(有主了),并且叫waiter来取
处理节点: 没动
HEAD=RESERVATION(用过)