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利用redis实现分布式锁,快速解决高并发时的线程安全问题

实际工作中,经常会遇到多线程并发时的类似抢购的功能,本篇描述一个简单的redis分布式锁实现的多线程抢票功能。

直接上代码。首先按照慣例,给出一个错误的示范:

我们可以看看,当20个线程一起来抢10张票的时候,会发生什么事。

package com.tiger.utils; 
public class TestMutilThread {
 
	// 总票量
	public static int count = 10; 
	public static void main(String[] args) {
		statrtMulti();
	}
 
	public static void statrtMulti() {
		for (int i = 1; i <= 20; i++) {
			TicketRunnable tickrunner = new TicketRunnable();
			Thread thread = new Thread(tickrunner, "Thread No: " + i);
			thread.start();
		} 
	}
 
	public static class TicketRunnable implements Runnable {
 
		@Override
		public void run() {
			System.out.println(Thread.currentThread().getName() + " start "
					+ count);
			// TODO Auto-generated method stub
			// logger.info(Thread.currentThread().getName()
			// + " really start" + count);
			if (count <= 0) {
				System.out.println(Thread.currentThread().getName()
						+ " ticket sold out ! No tickets remained!" + count);
				return;
			} else {
				count = count - 1;
				System.out.println(Thread.currentThread().getName()
						+ " bought a ticket,now remaining :" + (count));
			}
		}
	}
}

测试结果,从结果可以看到,票数在不同的线程中已经出现混乱。

Thread No: 2 start 10
Thread No: 6 start 10
Thread No: 4 start 10
Thread No: 5 start 10
Thread No: 3 start 10
Thread No: 9 start 6
Thread No: 1 start 10
Thread No: 1 bought a ticket,now remaining :3
Thread No: 9 bought a ticket,now remaining :4
Thread No: 3 bought a ticket,now remaining :5
Thread No: 12 start 3
Thread No: 5 bought a ticket,now remaining :6
Thread No: 4 bought a ticket,now remaining :7
Thread No: 8 start 7
Thread No: 7 start 8
Thread No: 12 bought a ticket,now remaining :1
Thread No: 14 start 0
Thread No: 6 bought a ticket,now remaining :8
Thread No: 16 start 0
Thread No: 2 bought a ticket,now remaining :9
Thread No: 16 ticket sold out ! No tickets remained!0
Thread No: 14 ticket sold out ! No tickets remained!0
Thread No: 18 start 0
Thread No: 18 ticket sold out ! No tickets remained!0
Thread No: 7 bought a ticket,now remaining :0
Thread No: 15 start 0
Thread No: 8 bought a ticket,now remaining :1
Thread No: 13 start 2
Thread No: 19 start 0
Thread No: 11 start 3
Thread No: 11 ticket sold out ! No tickets remained!0
Thread No: 10 start 3
Thread No: 10 ticket sold out ! No tickets remained!0
Thread No: 19 ticket sold out ! No tickets remained!0
Thread No: 13 ticket sold out ! No tickets remained!0
Thread No: 20 start 0
Thread No: 20 ticket sold out ! No tickets remained!0
Thread No: 15 ticket sold out ! No tickets remained!0
Thread No: 17 start 0
Thread No: 17 ticket sold out ! No tickets remained!0

为了解决多线程时出现的混乱问题,这里給出真正的测试类!!!

真正的测试类,这里启动20个线程,来抢10张票。

RedisTemplate 是用来实现redis操作的,由spring进行集成。这里是使用到了RedisTemplate,所以我以构造器的形式在外部将RedisTemplate传入到测试类中。

MultiTestLock 是用来实现加锁的工具类。

总票数使用volatile关键字,实现多线程时变量在系统内存中的可见性,这点可以去了解下volatile关键字的作用。

TicketRunnable用于模拟抢票功能。

其中由于lock与unlock之间存在if判断,为保证线程安全,这里使用synchronized来保证。

测试类:

package com.tiger.utils; 
import java.io.Serializable; 
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.data.redis.core.RedisTemplate; 
public class MultiConsumer {
	Logger logger=LoggerFactory.getLogger(MultiTestLock.class);	
	private RedisTemplate<Serializable, Serializable> redisTemplate;	
	public MultiTestLock lock;
	//总票量
	public volatile static int count = 10;
 
	public void statrtMulti() {
		lock = new MultiTestLock(redisTemplate);
		for (int i = 1; i <= 20; i++) {
			TicketRunnable tickrunner = new TicketRunnable();
			Thread thread = new Thread(tickrunner, "Thread No: " + i);
			thread.start();
			} 
	}
 
	public class TicketRunnable implements Runnable {
 
		@Override
		public void run() {
			logger.info(Thread.currentThread().getName() + " start "
					+ count);
			// TODO Auto-generated method stub
			if (count > 0) {
//				logger.info(Thread.currentThread().getName()
//						+ " really start" + count);
				lock.lock();
				synchronized (this) {
					if(count<=0){
						logger.info(Thread.currentThread().getName()
								+ " ticket sold out ! No tickets remained!" + count);
						lock.unlock();
						return;
					}else{
						count=count-1;
						logger.info(Thread.currentThread().getName()
								+ " bought a ticket,now remaining :" + (count));
					}
				}
				lock.unlock();
			}else{
				logger.info(Thread.currentThread().getName()
						+ " ticket sold out !" + count);
			}
		}
	}
 
	public RedisTemplate<Serializable, Serializable> getRedisTemplate() {
		return redisTemplate;
	}
 
	public void setRedisTemplate(
			RedisTemplate<Serializable, Serializable> redisTemplate) {
		this.redisTemplate = redisTemplate;
	}
 
	public MultiConsumer(RedisTemplate<Serializable, Serializable> redisTemplate) {
		super();
		this.redisTemplate = redisTemplate;
	}
}

Lock工具类:

我们知道为保证线程安全,程序中执行的操作必须时原子的。redis后续的版本中可以使用set key同时设置expire超时时间。

想起上次去 电信翼支付 面试时,面试官问过一个问题:分布式锁如何防止死锁,问题关键在于我们在分布式中进行加锁操作时成功了,但是后续业务操作完毕执行解锁时出现失败。导致分布式锁无法释放。出现死锁,后续的加锁无法正常进行。所以这里设置expire超时时间的目的就是防止出现解锁失败的情况,这样,即使解锁失败了,分布式锁依然会在超时时间过了之后自动释放。

具体在代码中也有注释,也可以作为参考。

package com.tiger.utils; 
import java.io.Serializable;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Random;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.Lock; 
import javax.sound.midi.MidiDevice.Info; 
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.dao.DataAccessException;
import org.springframework.data.redis.core.RedisOperations;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.SessionCallback;
import org.springframework.data.redis.core.script.RedisScript; 
 
public class MultiTestLock implements Lock {	
	Logger logger=LoggerFactory.getLogger(MultiTestLock.class);	
	private RedisTemplate<Serializable, Serializable> redisTemplate;	
	public MultiTestLock(RedisTemplate<Serializable, Serializable> redisTemplate) {
		super();
		this.redisTemplate = redisTemplate;
	}
 
	@Override
	public void lock() {
		//这里使用while循环强制线程进来之后先进行抢锁操作。只有抢到锁才能进行后续操作
		while(true){
			if(tryLock()){
				try {
					//这里让线程睡500毫秒的目的是为了模拟业务耗时,确保业务结束时之前设置的值正好打到超时时间,
					//实际生产中可能有偏差,这里需要经验
					Thread.sleep(500l);
//					logger.info(Thread.currentThread().getName()+" time to awake");
					return;
				} catch (InterruptedException e) {
					// TODO Auto-generated catch block
					e.printStackTrace();
				}
			}else{
				try {
					//这里设置一个随机毫秒的sleep目的时降低while循环的频率 
					Thread.sleep(new Random().nextInt(200)+100);
				} catch (InterruptedException e) {
					// TODO Auto-generated catch block
					e.printStackTrace();
				}
			}
		}
	}
 
	@Override
	public boolean tryLock() {
		//这里也可以选用transactionSupport支持事务操作
		SessionCallback<Object> sessionCallback=new SessionCallback<Object>() {
			@Override
			public Object execute(RedisOperations operations)
					throws DataAccessException {
				operations.multi();
				operations.opsForValue().setIfAbsent("secret", "answer");
				//设置超时时间要根据业务实际的可能处理时间来,是一个经验值
				operations.expire("secret", 500l, TimeUnit.MILLISECONDS);
				Object object=operations.exec();
				return object;
			}
		};
		//执行两部操作,这里会拿到一个数组值 [true,true],分别对应上述两部操作的结果,如果中途出现第一次为false则表明第一步set值出错
		List<Boolean> result=(List) redisTemplate.execute(sessionCallback);
//		logger.info(Thread.currentThread().getName()+" try lock "+ result);
		if(true==result.get(0)||"true".equals(result.get(0)+"")){
			logger.info(Thread.currentThread().getName()+" try lock success");
			return true;
		}else{
			return false;
		}
	}
 
	@Override
	public boolean tryLock(long arg0, TimeUnit arg1)
			throws InterruptedException {
		// TODO Auto-generated method stub
		return false;
	}
 
	@Override
	public void unlock() {
		//unlock操作直接删除锁,如果执行完还没有达到超时时间则直接删除,让后续的线程进行继续操作。起到补刀的作用,确保锁已经超时或被删除
		SessionCallback<Object> sessionCallback=new SessionCallback<Object>() {
			@Override
			public Object execute(RedisOperations operations)
					throws DataAccessException {
				operations.multi();
				operations.delete("secret");
				Object object=operations.exec();
				return object;
			}
		};
		Object result=redisTemplate.execute(sessionCallback);
	} 
 
	@Override
	public void lockInterruptibly() throws InterruptedException {
		// TODO Auto-generated method stub
	}
 
	@Override
	public Condition newCondition() {
		// TODO Auto-generated method stub
		return null;
	}
	
	public RedisTemplate<Serializable, Serializable> getRedisTemplate() {
		return redisTemplate;
	}
 
	public void setRedisTemplate(
			RedisTemplate<Serializable, Serializable> redisTemplate) {
		this.redisTemplate = redisTemplate;
	}
}

执行结果

利用redis实现分布式锁,快速解决高并发时的线程安全问题

可以看到,票数稳步减少,后续没有抢到锁的线程余票为0,无票可抢。

tips:

这其中也出现了一个问题,redis进行多部封装操作时,系统报错:ERR EXEC without MULTI

后经过查阅发现问题出在:

在spring中,多次执行MULTI命令不会报错,因为第一次执行时,会将其内部的一个isInMulti变量设为true,后续每次执行命令是都会检查这个变量,如果为true,则不执行命令。

而多次执行EXEC命令则会报开头说的"ERR EXEC without MULTI"错误。

利用redis实现分布式锁,快速解决高并发时的线程安全问题

以上为个人经验,希望能给大家一个参考,也希望大家多多支持。如有错误或未考虑完全的地方,望不吝赐教。