Using Redis to implement distributed locks in Beego

With the rapid development of the Internet, the application of distributed systems is becoming more and more widespread. In distributed systems, multiple nodes often operate on the same resource. In order to avoid problems with concurrent operations, a mechanism is needed to coordinate the order of operations on each node. This is a distributed lock.

Redis is an open source, high-performance cache database that has become one of the commonly used solutions in distributed systems. It provides a distributed lock implementation based on atomic operations. This article will introduce how to use Redis to implement distributed locks in the Beego framework.

1. How to implement distributed locks

There are many ways to implement distributed locks, such as database-based locks, Zookeeper-based locks, Redis-based locks, etc. In this article, we mainly introduce the lock implementation based on Redis.

The setnx (SET if Not eXists) command provided by Redis can realize that a key can only be set successfully if it does not exist, otherwise the setting fails. Taking advantage of this, we can implement distributed locks based on Redis. The specific process is as follows:

1. The client tries to acquire the lock, requests Redis to insert a Key, and sets the value to a unique random string token.
2. If the returned result is 1, it means that the lock acquisition is successful, otherwise the lock acquisition fails.
3. Before the lock is released, the client needs to refresh the expiration time of the Key regularly. This is because after a client acquires the lock, it may not have the opportunity to actively release the lock due to a program crash or other reasons during the execution of business logic.
4. After the business processing is completed, the client needs to actively release the lock and call the Redis del command to delete the Key.

2. Use Redis to implement distributed locks in the Beego framework

Beego is a Web framework for rapid development of Go applications. It is simple, easy to learn, efficient, flexible, and scalable. . It is also very convenient to use Redis to implement distributed locks in the Beego framework.

1. Using Redis in Beego

First of all, we need to use Redis in Beego. We can use the cache module built into the beego framework. The beego/cache package provides encapsulation of third-party cache services, including beegocache, filecache, memorycache, redis, memcache, ssdb, leveldb and other cache adapters.

First we need to configure the redis connection information and cache properties in the configuration file:

// 在conf/app.conf中加入如下配置信息

cache = redis 
adapter = redis
conn = 127.0.0.1:6379
dbnum = 0

Then when the application starts, we need to create a cache object to connect to redis, the code is as follows:

import(
    "github.com/astaxie/beego/cache"
    _ "github.com/astaxie/beego/cache/redis"
)

func main() {
    bm, err := cache.NewCache("redis", `{"conn":"127.0.0.1:6379","dbNum":"0"}`)
    if err != nil {
        fmt.Println("cache err:", err)
        return
    }
}

2. Implementation of distributed lock

After we have Redis and cache objects, we can start to implement distributed locks. In this example, we will implement a simple counter interface, which needs to implement a distributed lock.

First, define a redis lock structure:

type RedisLock struct {
    Key     string
    Token   string
    Timeout int64
}

Among them, Key is the name of the lock; Token is the value of the lock. When the Key already exists in Redis, the lock fails; Timeout Is the lock timeout, in seconds.

Then, implement the lock acquisition and release method:

func (l *RedisLock) Lock() error {
    ttl := strconv.FormatInt(l.Timeout, 10)
    for {
        ok, err := bm.Do("SET", l.Key, l.Token, "EX", ttl, "NX")
        if err != nil {
            return err
        }
        if ok == nil {
            time.Sleep(time.Millisecond * time.Duration(rand.Intn(100)))
            continue
        }
        return nil
    }
}

func (l *RedisLock) Unlock() error {
    _, err := bm.Do("DEL", l.Key)
    return err
}

The specific implementation process is as described above: Use the NX option of the set command to avoid lock competition problems. If the lock is successfully acquired, Then the Key locked within a certain period of time does not exist, and other clients cannot obtain the lock, thereby ensuring data consistency.

Finally, implement the distributed lock combined with the counter:

var counter int64

func Add() {
    l := RedisLock{
        Key:     "counter_lock",
        Token:   "token",
        Timeout: 3,
    }
    err := l.Lock()
    if err != nil {
        fmt.Println("acquire lock fail, err:", err)
        return
    }
    defer l.Unlock()

    counter = counter + 1
    fmt.Println("current counter number is", counter)
}

Get the lock object l in the Add function, and call the l.Lock() method to lock; after the lock is successful, Data operations, and call the l.Unlock() method to release the lock.

3. Summary

Through the introduction of this article, we have learned how to use Redis to implement distributed locks in Beego. The atomic operation setnx provided by Redis is very efficient for implementing distributed locks. In the Beego framework, the implementation of Redis distributed locks becomes simple and intuitive by using the cache package for Redis connection and operation.

Finally, it should be noted that although the implementation of distributed locks can effectively ensure data consistency, it cannot solve all concurrency problems in distributed systems. For example, the implementation of distributed locks needs to consider issues such as lock timeout and anti-deadlock. In addition, the key-value lock provided by distributed locks may cause lock failure due to network jitter, faults, etc. Developers also need to consider specific business scenarios. Make certain improvements and optimizations.

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