Distributed ID generation system based on go-zero

With the continuous development of Internet business, the ID generation system has become one of the indispensable components. The distributed ID generation system can provide unique ID generation services for distributed systems to ensure the correct operation of the business system. This article will introduce the implementation of a distributed ID generation system based on go-zero.

Why is a distributed ID generation system needed?

In a distributed system, different parts of services need to work together. Under normal circumstances, different services cannot communicate by referencing the object of another service. This requires the use of unique identifiers. for data transfer and access. The distributed ID generation system can provide a unique identifier for each service to realize communication and data transmission between services.

Normally, the ID generator in the system is a single point service. Due to a single point of failure or performance bottleneck, it will affect the normal operation of the entire system. As the system scale expands, the single-point ID generator is unable to cope with high concurrent requests, which requires splitting the ID generator to implement a distributed ID generation system.

Implementation of distributed ID generation system

Distributed ID generator system generally needs to include the following parts:

• Generator: generate a unique ID;
• Storage: stores generated IDs to prevent duplication;
• Distributed lock: ensures that multiple generators will not generate the same ID at the same time.

For these three parts, we use components in go-zero to build a simple distributed ID generation system.

Generator

In go-zero, you can use the snowflake algorithm to generate unique IDs. The snowflake algorithm was developed by Twitter and can generate a 64-bit unique ID, which consists of three parts: timestamp, node ID, and serial number.

In go-zero, use the following code to implement the snowflake algorithm:

package generate

import (
    "github.com/go-redis/redis"
    "github.com/tal-tech/go-zero/core/lock"
    "github.com/tal-tech/go-zero/core/stores/redis"
)

func GenerateId(nodeId int64, conn redis.Redis) (int64, error) {
    redisLock := lock.NewRedisLock(conn, "id_gen_lock")
    if err := redisLock.Lock(); err != nil {
        return 0, err
    }
    defer redisLock.Unlock()

    redisKey := "id_gen:" + strconv.Itoa(int(nodeId))
    id := snowflake.Generate(nodeId)
    _, err := conn.SetNX(redisKey, id, 0).Result()
    if err != nil {
        return 0, err
    }
    return id, nil
}

In this code, we use the redis component in go-zero to generate a unique ID and store it in redis.

Storage

We use redis as the storage of the distributed ID generator, and ensure that the generated IDs will not be repeated through the setnx instruction in redis. Each key stored in redis corresponds to a unique ID.

Distributed lock

In the lock component of go-zero, we can use redis lock to implement distributed lock. In the process of generating IDs, redis locks are used to ensure that only one generator can generate unique IDs at the same time to avoid duplicate IDs.

redisLock := lock.NewRedisLock(conn, "id_gen_lock")
if err := redisLock.Lock(); err != nil {
    return 0, err
}
defer redisLock.Unlock()

Using

With the above code, we can build a distributed ID generator system based on go-zero, simply use it as follows:

nodeId := 1
id, err := generate.GenerateId(nodeId, conn)
if err != nil {
    fmt.Println("generate id error:", err)
}
fmt.Println(id)

In this In the example, we pass in a nodeId, generate a unique ID, and store it in redis. In a distributed system, this function can be called separately using different nodeIds to obtain a unique ID.

Summary

Through the introduction of this article, we have learned about the design ideas and implementation details of the distributed ID generator. Through the components in go-zero, we can quickly build a distributed ID Generator system.

The distributed ID generation system plays an important role in the distributed system and can provide guarantee for the normal operation of the distributed system. In practice, we need to appropriately adjust the implementation of the ID generator according to specific business needs to ensure the correct operation of the system.

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