We all know that distributed locks must be used in a distributed environment. So what characteristics do distributed locks need? How to lock stand-alone redis? What are the pitfalls of redis cluster locking? Don't worry, let's unravel the veil of Redis distributed lock step by step.
No matter what the circumstances Only one thread can hold the lock.
The redis cluster environment cannot fail to acquire or release locks because a node is down. [Related recommendations: Redis Video Tutorial]
must have a timeout control mechanism or cancellation operate.
Lock it yourself and release it yourself. Locks added by others cannot be released.
The same thread can be locked multiple times.
Generally, it is implemented using the setnx lua script.
Post the code directly
package com.fandf.test.redis;
import cn.hutool.core.util.IdUtil;
import cn.hutool.core.util.RandomUtil;
import lombok.extern.slf4j.Slf4j;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.script.DefaultRedisScript;
import org.springframework.stereotype.Service;
import javax.annotation.Resource;
import java.util.Collections;
import java.util.concurrent.TimeUnit;
/**
* redis 单机锁
*
* @author fandongfeng
* @date 2023/3/29 06:52
*/
@Slf4j
@Service
public class RedisLock {
@Resource
RedisTemplate<String, Object> redisTemplate;
private static final String SELL_LOCK = "kill:";
/**
* 模拟秒杀
*
* @return 是否成功
*/
public String kill() {
String productId = "123";
String key = SELL_LOCK + productId;
//锁value,解锁时 用来判断当前锁是否是自己加的
String value = IdUtil.fastSimpleUUID();
//加锁 十秒钟过期 防死锁
Boolean flag = redisTemplate.opsForValue().setIfAbsent(key, value, 10, TimeUnit.SECONDS);
if (!flag) {
return "加锁失败";
}
try {
String productKey = "good123";
//获取商品库存
Integer stock = (Integer) redisTemplate.opsForValue().get(productKey);
if (stock == null) {
//模拟录入数据， 实际应该加载时从数据库读取
redisTemplate.opsForValue().set(productKey, 100);
stock = 100;
}
if (stock <= 0) {
return "卖完了，下次早点来吧";
}
//扣减库存, 模拟随机卖出数量
int randomInt = RandomUtil.randomInt(1, 10);
redisTemplate.opsForValue().decrement(productKey, randomInt);
// 修改db,可以丢到队列里慢慢处理
return "成功卖出" + randomInt + "个，库存剩余" + redisTemplate.opsForValue().get(productKey) + "个";
} finally {
// //这种方法会存在删除别人加的锁的可能
// redisTemplate.delete(key);
// if(value.equals(redisTemplate.opsForValue().get(key))){
// //因为if条件的判断和 delete不是原子性的，
// //if条件判断成功后，恰好锁到期自己解锁
// //此时别的线程如果持有锁了，就会把别人的锁删除掉
// redisTemplate.delete(key);
// }
//使用lua脚本保证判断和删除的原子性
String luaScript =
"if (redis.call('get',KEYS[1]) == ARGV[1]) then " +
"return redis.call('del',KEYS[1]) " +
"else " +
"return 0 " +
"end";
redisTemplate.execute(new DefaultRedisScript<>(luaScript, Boolean.class), Collections.singletonList(key), value);
}
}
}Conduct unit testing and simulate a hundred threads to perform flash kills at the same time
package com.fandf.test.redis;
import org.junit.jupiter.api.DisplayName;
import org.junit.jupiter.api.RepeatedTest;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.parallel.Execution;
import org.springframework.boot.test.context.SpringBootTest;
import javax.annotation.Resource;
import static org.junit.jupiter.api.parallel.ExecutionMode.CONCURRENT;
/**
* @Description:
* @author: fandongfeng
* @date: 2023-3-24 16:45
*/
@SpringBootTest
class SignServiceTest {
@Resource
RedisLock redisLock;
@RepeatedTest(100)
@Execution(CONCURRENT)
public void redisLock() {
String result = redisLock.kill();
if("加锁失败".equals(result)) {
}else {
System.out.println(result);
}
}
}Only three threads grabbed the lock
成功卖出5个，库存剩余95个 成功卖出8个，库存剩余87个 成功卖出7个，库存剩余80个
In general, there are two:
So is there any way to solve these two problems? Yes, let’s talk about Redisson
Redisson is a Java in-memory data grid (In-Memory Data Grid) implemented on the basis of Redis. It not only provides a series of distributed common Java objects, but also provides many distributed services. These include (BitSet, Set, Multimap, SortedSet, Map, List , Queue, BlockingQueue, Deque, BlockingDeque, Semaphore, Lock, AtomicLong, CountDownLatch, Publish / Subscribe, Bloom filter, Remote service, Spring cache, Executor service, Live Object service, Scheduler service) Redisson provides the simplest and most convenient way to use Redis. The purpose of Redisson is to promote users' separation of concerns (Separation of Concern) from Redis, so that users can focus more on processing business logic.
Integration is very simple, just two steps
<dependency>
<groupId>org.redisson</groupId>
<artifactId>redisson-spring-boot-starter</artifactId>
</dependency>spring:
application:
name: test
redis:
host: 127.0.0.1
port: 6379It is also very simple to use, just inject RedissonClient
package com.fandf.test.redis;
import lombok.extern.slf4j.Slf4j;
import org.redisson.api.RLock;
import org.redisson.api.RedissonClient;
import org.springframework.stereotype.Component;
import javax.annotation.Resource;
/**
* @author fandongfeng
*/
@Component
@Slf4j
public class RedissonTest {
@Resource
RedissonClient redissonClient;
public void test() {
RLock rLock = redissonClient.getLock("anyKey");
//rLock.lock(10, TimeUnit.SECONDS);
rLock.lock();
try {
// do something
} catch (Exception e) {
log.error("业务异常", e);
} finally {
rLock.unlock();
}
}
}Friends who may not understand redisson can't help but ask questions.
What? Don’t you need to add an expiration time when locking? Will this cause a deadlock? Isn’t it necessary to judge whether you own it to unlock it?
Haha, don’t worry, we will unveil redisson step by step.
Let’s follow the lock() method step by step to look at the source code (the local redisson version is 3.20.0)
//RedissonLock.class
@Override
public void lock() {
try {
lock(-1, null, false);
} catch (InterruptedException e) {
throw new IllegalStateException();
}
}View lock(- 1, null, false);Method
private void lock(long leaseTime, TimeUnit unit, boolean interruptibly) throws InterruptedException {
//获取当前线程id
long threadId = Thread.currentThread().getId();
//加锁代码块， 返回锁的失效时间
Long ttl = tryAcquire(-1, leaseTime, unit, threadId);
// lock acquired
if (ttl == null) {
return;
}
CompletableFuture<RedissonLockEntry> future = subscribe(threadId);
pubSub.timeout(future);
RedissonLockEntry entry;
if (interruptibly) {
entry = commandExecutor.getInterrupted(future);
} else {
entry = commandExecutor.get(future);
}
try {
while (true) {
ttl = tryAcquire(-1, leaseTime, unit, threadId);
// lock acquired
if (ttl == null) {
break;
}
// waiting for message
if (ttl >= 0) {
try {
entry.getLatch().tryAcquire(ttl, TimeUnit.MILLISECONDS);
} catch (InterruptedException e) {
if (interruptibly) {
throw e;
}
entry.getLatch().tryAcquire(ttl, TimeUnit.MILLISECONDS);
}
} else {
if (interruptibly) {
entry.getLatch().acquire();
} else {
entry.getLatch().acquireUninterruptibly();
}
}
}
} finally {
unsubscribe(entry, threadId);
}
// get(lockAsync(leaseTime, unit));
}Let’s see how it is locked, that is, tryAcquire method
private Long tryAcquire(long waitTime, long leaseTime, TimeUnit unit, long threadId) {
//真假加锁方法 tryAcquireAsync
return get(tryAcquireAsync(waitTime, leaseTime, unit, threadId));
}public RedissonLock(CommandAsyncExecutor commandExecutor, String name) {
super(commandExecutor, name);
this.commandExecutor = commandExecutor;
this.internalLockLeaseTime = commandExecutor.getServiceManager().getCfg().getLockWatchdogTimeout();
this.pubSub = commandExecutor.getConnectionManager().getSubscribeService().getLockPubSub();
}
private <T> RFuture<Long> tryAcquireAsync(long waitTime, long leaseTime, TimeUnit unit, long threadId) {
RFuture<Long> ttlRemainingFuture;
if (leaseTime > 0) {
ttlRemainingFuture = tryLockInnerAsync(waitTime, leaseTime, unit, threadId, RedisCommands.EVAL_LONG);
} else {
//waitTime和leaseTime都是-1，所以走这里
//过期时间internalLockLeaseTime初始化的时候赋值commandExecutor.getServiceManager().getCfg().getLockWatchdogTimeout();
//跟进去源码发现默认值是30秒， private long lockWatchdogTimeout = 30 * 1000;
ttlRemainingFuture = tryLockInnerAsync(waitTime, internalLockLeaseTime,
TimeUnit.MILLISECONDS, threadId, RedisCommands.EVAL_LONG);
}
CompletionStage<Long> s = handleNoSync(threadId, ttlRemainingFuture);
ttlRemainingFuture = new CompletableFutureWrapper<>(s);
//加锁成功，开启子线程进行续约
CompletionStage<Long> f = ttlRemainingFuture.thenApply(ttlRemaining -> {
// lock acquired
if (ttlRemaining == null) {
if (leaseTime > 0) {
//如果指定了过期时间，则不续约
internalLockLeaseTime = unit.toMillis(leaseTime);
} else {
//没指定过期时间，或者小于0，在这里实现锁自动续约
scheduleExpirationRenewal(threadId);
}
}
return ttlRemaining;
});
return new CompletableFutureWrapper<>(f);
}The above code contains the logic of locking and lock renewal. We Let’s take a look at the locking code first
<T> RFuture<T> tryLockInnerAsync(long waitTime, long leaseTime, TimeUnit unit, long threadId, RedisStrictCommand<T> command) {
return evalWriteAsync(getRawName(), LongCodec.INSTANCE, command,
"if ((redis.call('exists', KEYS[1]) == 0) " +
"or (redis.call('hexists', KEYS[1], ARGV[2]) == 1)) then " +
"redis.call('hincrby', KEYS[1], ARGV[2], 1); " +
"redis.call('pexpire', KEYS[1], ARGV[1]); " +
"return nil; " +
"end; " +
"return redis.call('pttl', KEYS[1]);",
Collections.singletonList(getRawName()), unit.toMillis(leaseTime), getLockName(threadId));
} It’s very clear here. Redisson uses a Lua script to ensure the atomicity of the command.
redis.call('hexists', KEYS[1], ARGV[2]) Check whether the key value exists.
The Redis Hexists command is used to check whether the specified field of the hash table exists.
If the hash table contains the given field, return 1. If the hash table does not contain the given field, or key does not exist, 0 is returned.
127.0.0.1:6379> hexists 123 uuid (integer) 0 127.0.0.1:6379> hincrby 123 uuid 1 (integer) 1 127.0.0.1:6379> hincrby 123 uuid 1 (integer) 2 127.0.0.1:6379> hincrby 123 uuid 1 (integer) 3 127.0.0.1:6379> hexists 123 uuid (integer) 1 127.0.0.1:6379> hgetall 123 1) "uuid" 2) "3" 127.0.0.1:6379>
When the key does not exist, or already contains the given field (that is, it has been locked, here is to achieve reentrancy), directly compare the value of the field 1
The value of this field, That is ARGV[2], obtained by the getLockName(threadId) method, let's take a look at the value of this field
protected String getLockName(long threadId) {
return id + ":" + threadId;
}
public RedissonBaseLock(CommandAsyncExecutor commandExecutor, String name) {
super(commandExecutor, name);
this.commandExecutor = commandExecutor;
this.id = commandExecutor.getServiceManager().getId();
this.internalLockLeaseTime = commandExecutor.getServiceManager().getCfg().getLockWatchdogTimeout();
this.entryName = id + ":" + name;
}
//commandExecutor.getServiceManager() 的id默认值
private final String id = UUID.randomUUID().toString();We will understand here, the field name is uuid: threadId
Connect Let's take a look at the lock renewal code scheduleExpirationRenewal(threadId);
protected void scheduleExpirationRenewal(long threadId) {
ExpirationEntry entry = new ExpirationEntry();
//判断该实例是否加过锁
ExpirationEntry oldEntry = EXPIRATION_RENEWAL_MAP.putIfAbsent(getEntryName(), entry);
if (oldEntry != null) {
//重入次数+1
oldEntry.addThreadId(threadId);
} else {
//第一次加锁
entry.addThreadId(threadId);
try {
//锁续约核心代码
renewExpiration();
} finally {
if (Thread.currentThread().isInterrupted()) {
//如果线程异常终止，则关闭锁续约线程
cancelExpirationRenewal(threadId);
}
}
}
}Let's take a look at the renewExpiration() method
private void renewExpiration() {
ExpirationEntry ee = EXPIRATION_RENEWAL_MAP.get(getEntryName());
if (ee == null) {
return;
}
//新建一个线程执行
Timeout task = commandExecutor.getServiceManager().newTimeout(new TimerTask() {
@Override
public void run(Timeout timeout) throws Exception {
ExpirationEntry ent = EXPIRATION_RENEWAL_MAP.get(getEntryName());
if (ent == null) {
return;
}
Long threadId = ent.getFirstThreadId();
if (threadId == null) {
return;
}
//设置锁过期时间为30秒
CompletionStage<Boolean> future = renewExpirationAsync(threadId);
future.whenComplete((res, e) -> {
if (e != null) {
log.error("Can't update lock {} expiration", getRawName(), e);
EXPIRATION_RENEWAL_MAP.remove(getEntryName());
return;
}
//检查锁是还否存在
if (res) {
// reschedule itself 10后调用自己
renewExpiration();
} else {
//关闭续约
cancelExpirationRenewal(null);
}
});
}
}, internalLockLeaseTime / 3, TimeUnit.MILLISECONDS);
//注意上行代码internalLockLeaseTime / 3，
//internalLockLeaseTime默认30s，那么也就是10s检查一次
ee.setTimeout(task);
}
//设置锁过期时间为internalLockLeaseTime 也就是30s lua脚本保证原子性
protected CompletionStage<Boolean> renewExpirationAsync(long threadId) {
return evalWriteAsync(getRawName(), LongCodec.INSTANCE, RedisCommands.EVAL_BOOLEAN,
"if (redis.call('hexists', KEYS[1], ARGV[2]) == 1) then " +
"redis.call('pexpire', KEYS[1], ARGV[1]); " +
"return 1; " +
"end; " +
"return 0;",
Collections.singletonList(getRawName()),
internalLockLeaseTime, getLockName(threadId));
}OK，分析到这里我们已经知道了，lock()，方法会默认加30秒过期时间，并且开启一个新线程，每隔10秒检查一下，锁是否释放，如果没释放，就将锁过期时间设置为30秒，如果锁已经释放，那么就将这个新线程也关掉。
我们写个测试类看看
package com.fandf.test.redis;
import org.junit.jupiter.api.Test;
import org.redisson.api.RLock;
import org.redisson.api.RedissonClient;
import org.springframework.boot.test.context.SpringBootTest;
import javax.annotation.Resource;
/**
* @Description:
* @author: fandongfeng
* @date: 2023-3-2416:45
*/
@SpringBootTest
class RedissonTest {
@Resource
private RedissonClient redisson;
@Test
public void watchDog() throws InterruptedException {
RLock lock = redisson.getLock("123");
lock.lock();
Thread.sleep(1000000);
}
}查看锁的过期时间，及是否续约
127.0.0.1:6379> keys * 1) "123" 127.0.0.1:6379> ttl 123 (integer) 30 127.0.0.1:6379> ttl 123 (integer) 26 127.0.0.1:6379> ttl 123 (integer) 24 127.0.0.1:6379> ttl 123 (integer) 22 127.0.0.1:6379> ttl 123 (integer) 21 127.0.0.1:6379> ttl 123 (integer) 20 127.0.0.1:6379> ttl 123 (integer) 30 127.0.0.1:6379> ttl 123 (integer) 28 127.0.0.1:6379>
我们再改改代码，看看是否可重入和字段名称是否和我们预期一致
package com.fandf.test.redis;
import org.junit.jupiter.api.Test;
import org.redisson.api.RLock;
import org.redisson.api.RedissonClient;
import org.springframework.boot.test.context.SpringBootTest;
import javax.annotation.Resource;
/**
* @Description:
* @author: fandongfeng
* @date: 2023-3-24 16:45
*/
@SpringBootTest
class RedissonTest {
@Resource
private RedissonClient redisson;
@Test
public void watchDog() throws InterruptedException {
RLock lock = redisson.getLock("123");
lock.lock();
lock.lock();
lock.lock();
//加了三次锁，此时重入次数为3
Thread.sleep(3000);
//解锁一次，此时重入次数变为3
lock.unlock();
Thread.sleep(1000000);
}
}127.0.0.1:6379> keys * 1) "123" 127.0.0.1:6379> 127.0.0.1:6379> ttl 123 (integer) 24 127.0.0.1:6379> hgetall 123 1) "df7f4c71-b57b-455f-acee-936ad8475e01:12" 2) "3" 127.0.0.1:6379> 127.0.0.1:6379> hgetall 123 1) "df7f4c71-b57b-455f-acee-936ad8475e01:12" 2) "2" 127.0.0.1:6379>
我们加锁了三次，重入次数是3，字段值也是 uuid+:+threadId,和我们预期结果是一致的。
redisson是基于Redlock算法实现的，那么什么是Redlock算法呢？
假设当前集群有5个节点，那么运行redlock算法的客户端会一次执行下面步骤
- 1.客户端记录当前系统时间，以毫秒为单位
- 2.依次尝试从5个redis实例中，使用相同key获取锁
当redis请求获取锁时，客户端会设置一个网络连接和响应超时时间，避免因为网络故障等原因导致阻塞。- 3.客户端使用当前时间减去开始获取锁时间（步骤1的时间），得到获取锁消耗的时间
只有当半数以上redis节点加锁成功，并且加锁消耗的时间要小于锁失效时间，才算锁获取成功- 4.如果获取到了锁，key的真正有效时间等于锁失效时间 减去 获取锁消耗的时间
- 5.如果获取锁失败，所有的redis实例都会进行解锁
防止因为服务端响应消息丢失，但是实际数据又添加成功导致数据不一致问题
这里有下面几个点需要注意：
更多编程相关知识，请访问：编程视频！！
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