【队列 高并发】java web瞬间高并发的解决方法
1、任何的高并发，请求总是会有一个顺序的
2、java的队列的数据结构是先进先出的取值顺序
3、BlockingQueue类(线程安全)（使用方法可以百度）
一般使用LinkedBlockingQueue
利用以上几点，我们可以把高并发时候的请求放入一个队列，队列的大小可以自己定义，比如队列容量为1000个数据，那么可以利用过滤器或者拦截器把当前的请求放入队列，如果队列的容量满了，其余的请求可以丢掉或者作出相应回复
具体实施：
利用生产者、消费者模型：
将队列的请求一一处理完。
上代码：
/**
* @author fuguangli
* @description 前沿消费者类
* @Create date: 2017/3/7
* @using EXAMPLE
*/
public class Customer implements Runnable{
/**
* 抛出异常 特殊值 阻塞 超时
插入 add(e) offer(e) put(e) offer(e, time, unit)
移除 remove() poll() take() poll(time, unit)
检查 element() peek() 不可用 不可用
*/
private BlockingQueue blockingQueue;
private AtomicInteger count = new AtomicInteger();
public Customer(BlockingQueue blockingQueue) {
this.blockingQueue = blockingQueue;
}
/**
* When an object implementing interface Runnable is used
* to create a thread, starting the thread causes the object's
* run method to be called in that separately executing
* thread.
*
* The general contract of the method run is that it may
* take any action whatsoever.
*
* @see Thread#run()
*/
@Override
public void run() {
System.out.println("消费者线程启动...");
LockFlag.setCustomerRunningFlag(true);
try {
while (LockFlag.getProducerRunningFlag()){
System.out.println(Thread.currentThread().getId()+"I'm Customer.Queue current size="+blockingQueue.size());
String data = (String) blockingQueue.poll(10, TimeUnit.SECONDS);
if(data!=null){
System.out.println(Thread.currentThread().getId()+"*************正在消费数据 data="+data);
}else{
//表示超过取值时间，视为生产者不再生产数据
System.out.println(Thread.currentThread().getId()+"队列为空无数据，请检查生产者是否阻塞");
}
Thread.sleep(50);
}
System.err.println("消费者程序执行完毕");
} catch (InterruptedException e) {
e.printStackTrace();
System.err.println("消费者程序退出");
LockFlag.setCustomerRunningFlag(false);//异常退出线程
Thread.currentThread().interrupt();
}
}
}
package com.qysxy.framework.queue;
import java.util.concurrent.BlockingQueue;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicInteger;
/**
* @author fuguangli
* @description 队列生产者类
* @Create date: 2017/3/7
* @using EXAMPLE
*/
public class Producer implements Runnable{
/**
* 抛出异常 特殊值 阻塞 超时
插入 add(e) offer(e) put(e) offer(e, time, unit)
移除 remove() poll() take() poll(time, unit)
检查 element() peek() 不可用 不可用
*/
private BlockingQueue blockingQueue;
private AtomicInteger count = new AtomicInteger();
public Producer(BlockingQueue blockingQueue) {
this.blockingQueue = blockingQueue;
}
/**
* When an object implementing interface Runnable is used
* to create a thread, starting the thread causes the object's
* run method to be called in that separately executing
* thread.
*
* The general contract of the method run is that it may
* take any action whatsoever.
*
* @see Thread#run()
*/
@Override
public void run() {
System.out.println("生产者线程启动...");
LockFlag.setProducerRunningFlag(true);
try {
while (LockFlag.getProducerRunningFlag()){
String data = "data:"+count.incrementAndGet();
if(blockingQueue.offer(data,10, TimeUnit.SECONDS)){
//返回true表示生产数据正确
System.out.println("^^^^^^^^^^^^^^正在生产数据 data="+data);
}else {
//表示阻塞时间内还没有生产者生产数据
System.out.println("生产者异常，无法生产数据");
}
Thread.sleep(50);
}
} catch (InterruptedException e) {
e.printStackTrace();
System.err.println("生产者程序退出");
LockFlag.setProducerRunningFlag(false);//异常退出线程
Thread.currentThread().interrupt();
}
}
}
package com.qysxy.framework.queue;
/**
* @author fuguangli
* @description 前沿生产者消费者模型的锁类
* @Create date: 2017/3/7
*/
public class LockFlag {
/**
* 生产者互斥锁
*/
private static Boolean producerRunningFlag = false;
/**
* 消费者互斥锁
*/
private static Boolean customerRunningFlag = false;
public static Boolean getProducerRunningFlag() {
return producerRunningFlag;
}
public static void setProducerRunningFlag(Boolean producerRunningFlag) {
LockFlag.producerRunningFlag = producerRunningFlag;
}
public static Boolean getCustomerRunningFlag() {
return customerRunningFlag;
}
public static void setCustomerRunningFlag(Boolean customerRunningFlag) {
LockFlag.customerRunningFlag = customerRunningFlag;
}
}
package com.qysxy.framework.queue;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import java.util.Queue;
import java.util.concurrent.*;
/**
* @author fuguangli
* @description 前沿队列实用类，用于大量并发用户
* @Create date: 2017/3/7
*/
public class BlockingQueueHelper {
private static final Integer maxQueueSize = 1000;
private static BlockingQueue blockingQueue = new LinkedBlockingQueue(maxQueueSize);
private static ExecutorService threadPool = Executors.newCachedThreadPool();
public static BlockingQueue getBlockingQueue() {
if (blockingQueue == null) {
blockingQueue = new LinkedBlockingQueue(maxQueueSize);
}
return blockingQueue;
}
/**
* @param o 队列处理对象（包含request,response,data）
*/
public static void requestQueue(Object o) {
//检测当前的队列大小
if (blockingQueue != null && blockingQueue.size() < maxQueueSize) {
//可以正常进入队列
if (blockingQueue.offer(o)) {
//添加成功，检测数据处理线程是否正常
if (LockFlag.getCustomerRunningFlag()) {
//说明处理线程类正常运行
} else {
//说明处理线程类停止，此时，应重新启动线程进行数据处理
LockFlag.setCustomerRunningFlag(true);
//example:run
Customer customer = new Customer(blockingQueue);
threadPool.execute(customer);
}
} else {
//进入队列失败，做出相应的处理，或者尝试重新进入队列
}
} else {
//队列不正常，或队列大小已达上限，做出相应处理
}
}
}
好了，这时候，利用过滤器或者拦截器将每个请求封装成队列元素进行处理就行。
当然了，对于多应用服务器的部署架构来说，数据库也需要加锁，数据库隔离级别另说。