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Learn redis with you (11) -- redis distributed lock

2022-06-22 22:54:00 【Reviewing the old and learning the new Java】

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Preface

In monomer applications , If we do not lock the shared data , There will be data consistency issues , Our solution is usually to lock . In a distributed architecture , We will also encounter data sharing operation problems , here , We need distributed locks to solve the problem , Let's talk about using redis To implement distributed locking .

Use scenarios

  1. Inventory oversold such as 5 A notebook A see Ready to buy 3 individual B buy 2 individual C 4 individual One order 3+2+4 =9
  2. Prevent users from placing repeated orders
  3. MQ The news is heavy
  4. Order operation change

Why use distributed locks

Analyze from the business scenario , There's one thing in common , Competition for shared resources , For example, stock goods , user , news , Orders, etc , These resources can only be operated by one thread at the same time , And during operation , Prohibit other thread operations . To achieve this effect , It is necessary to realize mutual exclusion of shared resources , Shared resource serialization . Actually , This is the problem of locking shared resources . In single application （ Single process multithreading ） Using locks in , We can use synchronize、ReentrantLock Other key words , Lock shared resources . In distributed applications （ Multiprocess and multithreading ） in , Distributed lock is a way to control the synchronous access of shared resources between distributed systems .

How to use distributed locks

flow chart

image.png

Status of distributed locks

  1. The client can only operate on the shared resources by competing for the lock
  2. When the client holding the lock operates on the shared resource
  3. No other client can operate on this resource
  4. Until the client holding the lock completes the operation

Features of distributed locks

  • Mutual exclusivity

At any moment , Only one client can hold the lock （ exclusive ）

  • High availability , Fault tolerance

As long as most nodes in the lock service cluster are running normally , You can unlock the client

  • Avoid deadlock

Lock failure mechanism , The lock must be released after a period of time .（ Normal release or timeout release ）

  • Locking and unlocking are the same client

One client cannot release the lock added by other clients

The implementation of distributed locks （ With redis Take distributed lock implementation as an example ）

Simple version 

/** *  Simple version  * @author:liyajie * @createTime:2022/6/22 15:42 * @version:1.0 */
public class SimplyRedisLock {
    // Redis Distributed locked key
    public static final String REDIS_LOCK = "redis_lock";

    @Autowired
    StringRedisTemplate template;

    public String index(){

        //  Everyone needs to lock before they come in ,key The value is "redis_lock",value Random generation 
        String value = UUID.randomUUID().toString().replace("-","");
        try{
            //  Lock 
            Boolean flag = template.opsForValue().setIfAbsent(REDIS_LOCK, value);
            //  Locking failed 
            if(!flag){
                return " Lock snatch failed ！";
            }
            System.out.println( value+ "  Successful lock snatching ");
            //  Business logic 
            String result = template.opsForValue().get("001");
            int total = result == null ? 0 : Integer.parseInt(result);
            if (total > 0) {
                int realTotal = total - 1;
                template.opsForValue().set("001", String.valueOf(realTotal));
                //  If after grabbing the place , Before deleting a lock , Something is wrong , The lock cannot be released ,
                //  The lock release operation cannot be performed here , To be in finally Handle 
                // template.delete(REDIS_LOCK);
                System.out.println(" Successful purchase of goods , Stock left ：" + realTotal + " Pieces of ");
                return " Successful purchase of goods , Stock left ：" + realTotal + " Pieces of ";
            } else {
                System.out.println(" Failed to buy goods ");
            }
            return " Failed to buy goods ";
        }finally {
            //  Release the lock 
            template.delete(REDIS_LOCK);
        }
    }   
}

The implementation scheme is relatively simple , But there are some problems . If the service hangs up while it is running , The code completes the locking process , But there's no use walking finally part , That is, the lock is not released , In this case , The lock can never be released . So there was an improved version .

Advanced version 

/** *  Advanced version  * @author:liyajie * @createTime:2022/6/22 15:42 * @version:1.0 */
public class SimplyRedisLock2 {
    // Redis Distributed locked key
    public static final String REDIS_LOCK = "redis_lock";

    @Autowired
    StringRedisTemplate template;

    public String index(){

        //  Everyone needs to lock before they come in ,key The value is "redis_lock",value Random generation 
        String value = UUID.randomUUID().toString().replace("-","");
        try{
            //  Lock 
            Boolean flag = template.opsForValue().setIfAbsent(REDIS_LOCK, value,10L, TimeUnit.SECONDS);
            //  Locking failed 
            if(!flag){
                return " Lock snatch failed ！";
            }
            System.out.println( value+ "  Successful lock snatching ");
            //  Business logic 
            String result = template.opsForValue().get("001");
            int total = result == null ? 0 : Integer.parseInt(result);
            if (total > 0) {
                int realTotal = total - 1;
                template.opsForValue().set("001", String.valueOf(realTotal));
                //  If after grabbing the place , Before deleting a lock , Something is wrong , The lock cannot be released ,
                //  The lock release operation cannot be performed here , To be in finally Handle 
                // template.delete(REDIS_LOCK);
                System.out.println(" Successful purchase of goods , Stock left ：" + realTotal + " Pieces of ");
                return " Successful purchase of goods , Stock left ：" + realTotal + " Pieces of ";
            } else {
                System.out.println(" Failed to buy goods ");
            }
            return " Failed to buy goods ";
        }finally {
            //  Release the lock 
            template.delete(REDIS_LOCK);
        }
    }   
}

This implementation , Yes key Added an expiration time , In this way, even if the service fails , After the expiration time , The lock will release automatically . But think about it , There is still a problem . such as key The expiration time of the value is 10s, But the business processing logic needs 15s Time for , This will cause a thread to process the business logic , Releasing the lock , Delete immediately key When , Delete the key Not myself set Of , It is set by other threads , This will cause data inconsistency , Errors that cause data , And affect the business . It needs to be improved .

Advanced version 2- Who set the lock , Who released 

/** *  Advanced version 2- Who set the lock , Who released  * @author:liyajie * @createTime:2022/6/22 15:42 * @version:1.0 */
public class SimplyRedisLock3 {
    // Redis Distributed locked key
    public static final String REDIS_LOCK = "redis_lock";

    @Autowired
    StringRedisTemplate template;

    public String index(){

        //  Everyone needs to lock before they come in ,key The value is "redis_lock",value Random generation 
        String value = UUID.randomUUID().toString().replace("-","");
        try{
            //  Lock 
            Boolean flag = template.opsForValue().setIfAbsent(REDIS_LOCK, value,10L, TimeUnit.SECONDS);
            //  Locking failed 
            if(!flag){
                return " Lock snatch failed ！";
            }
            System.out.println( value+ "  Successful lock snatching ");
            //  Business logic 
            String result = template.opsForValue().get("001");
            int total = result == null ? 0 : Integer.parseInt(result);
            if (total > 0) {
                int realTotal = total - 1;
                template.opsForValue().set("001", String.valueOf(realTotal));
                //  If after grabbing the place , Before deleting a lock , Something is wrong , The lock cannot be released ,
                //  The lock release operation cannot be performed here , To be in finally Handle 
                // template.delete(REDIS_LOCK);
                System.out.println(" Successful purchase of goods , Stock left ：" + realTotal + " Pieces of ");
                return " Successful purchase of goods , Stock left ：" + realTotal + " Pieces of ";
            } else {
                System.out.println(" Failed to buy goods ");
            }
            return " Failed to buy goods ";
        }finally {
            //  Who added the lock , Who can delete ！！！！
            if(template.opsForValue().get(REDIS_LOCK).equals(value)){
                template.delete(REDIS_LOCK);
            }
        }
    }   
}

This method solves the problem of complex business , Processing time is too long , Past due date , And the problem of releasing other people's locks . Are there any other questions ？ In fact, there are still some ,finally Block judgment and del The delete operation is not atomic , There will also be problems during concurrency , Concurrency is to ensure data consistency , Ensure data consistency , It is best to ensure that the operation of data is atomic . So we still need to improve .

Advanced version 3-Lua edition 

/** *  Advanced version -Lua edition  * @author:liyajie * @createTime:2022/6/22 15:42 * @version:1.0 */
public class SimplyRedisLock3 {
    // Redis Distributed locked key
    public static final String REDIS_LOCK = "redis_lock";

    @Autowired
    StringRedisTemplate template;

    public String index(){

        //  Everyone needs to lock before they come in ,key The value is "redis_lock",value Random generation 
        String value = UUID.randomUUID().toString().replace("-","");
        try{
            //  Lock 
            Boolean flag = template.opsForValue().setIfAbsent(REDIS_LOCK, value,10L, TimeUnit.SECONDS);
            //  Locking failed 
            if(!flag){
                return " Lock snatch failed ！";
            }
            System.out.println( value+ "  Successful lock snatching ");
            //  Business logic 
            String result = template.opsForValue().get("001");
            int total = result == null ? 0 : Integer.parseInt(result);
            if (total > 0) {
                int realTotal = total - 1;
                template.opsForValue().set("001", String.valueOf(realTotal));
                //  If after grabbing the place , Before deleting a lock , Something is wrong , The lock cannot be released ,
                //  The lock release operation cannot be performed here , To be in finally Handle 
                // template.delete(REDIS_LOCK);
                System.out.println(" Successful purchase of goods , Stock left ：" + realTotal + " Pieces of ");
                return " Successful purchase of goods , Stock left ：" + realTotal + " Pieces of ";
            } else {
                System.out.println(" Failed to buy goods ");
            }
            return " Failed to buy goods ";
        }finally {
            //  Who added the lock , Who can delete , Use Lua Script , Delete the lock 
            Jedis jedis = null;
            try{
                jedis = RedisUtils.getJedis();
                String script = "if redis.call('get',KEYS[1]) == ARGV[1] " +
                        "then " +
                        "return redis.call('del',KEYS[1]) " +
                        "else " +
                        " return 0 " +
                        "end";

                Object eval = jedis.eval(script, Collections.singletonList(REDIS_LOCK), Collections.singletonList(value));
                if("1".equals(eval.toString())){
                    System.out.println("-----del redis lock ok....");
                }else{
                    System.out.println("-----del redis lock error ....");
                }
            }catch (Exception e){

            }finally {
                if(null != jedis){
                    jedis.close();
                }
            }
        }
    }   
}

This way, , Specifies who has the lock , Who can delete , It also solves the problem that the deletion operation has no atomicity . But cache has not been considered yet , as well as Redis Cluster deployment , Lock loss due to asynchronous replication ： The master node didn't have time to set Enter this data to the slave node , I hung up. . So we have to improve .

Ultimate evolution 

/** *  Ultimate evolution  * @author:liyajie * @createTime:2022/6/22 15:42 * @version:1.0 */
public class SimplyRedisLock5 {
    // Redis Distributed locked key
    public static final String REDIS_LOCK = "redis_lock";

    @Autowired
    StringRedisTemplate template;

    @Autowired
    Redisson redisson;

    public String index(){

        RLock lock = redisson.getLock(REDIS_LOCK);
        lock.lock();
        //  Everyone needs to lock before they come in ,key The value is "redis_lock"
        String value = UUID.randomUUID().toString().replace("-","");
        try {
            String result = template.opsForValue().get("001");
            int total = result == null ? 0 : Integer.parseInt(result);
            if (total > 0) {
                //  If you need to call other microservices here , Longer processing time ...
                int realTotal = total - 1;
                template.opsForValue().set("001", String.valueOf(realTotal));
                System.out.println(" Successful purchase of goods , Stock left ：" + realTotal + " Pieces of ");
                return " Successful purchase of goods , Stock left ：" + realTotal + " Pieces of ";
            } else {
                System.out.println(" Failed to buy goods ");
            }
            return " Failed to buy goods ";
        }finally {
            if(lock.isLocked() && lock.isHeldByCurrentThread()){
                lock.unlock();
            }
        }
    }   
}

This implementation , The bottom layer encapsulates multiple nodes redis Implementation of the distributed lock algorithm , Effectively prevent single point of failure , If you are interested, you can study it .

summary

The process of analyzing problems , It is also the process of solving problems , It can also exercise the way and angle of thinking when writing code . About redis That's all for the correlation analysis of distributed locks , You have new ideas , Welcome to exchange and analyze .

end

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