How to use MySQL's distributed architecture to achieve horizontal expansion?

How to use MySQL's distributed architecture to achieve horizontal expansion?

With the rapid development of Internet applications, the storage and processing of large amounts of data has become an important issue in system design. In traditional stand-alone MySQL, as the amount of data increases, the storage and processing capabilities of the stand-alone machine can easily become a bottleneck. In order to solve this problem, we can use MySQL's distributed architecture to achieve horizontal expansion, thereby improving the storage and processing capabilities of the system.

MySQL’s distributed architecture mainly consists of two parts: data sharding and distributed transaction management.

First, shard the stored data. Sharding is dividing a database into multiple independent fragments, each fragment storing part of the data. During the sharding process, we need to implement a reasonable sharding strategy based on the characteristics of the data to ensure that the data is evenly distributed in different fragments, thereby improving the efficiency of data query. Commonly used sharding strategies include range-based sharding, hash-based sharding, and list-based sharding. The following uses range-based sharding as an example.

Suppose we have a user table that contains fields such as the user's ID, name, and age. We can shard based on the user's ID, storing users with user IDs ranging from 1 to 100 in one shard, users with user IDs ranging from 101 to 200 in another shard, and so on. In this way, when querying user data, we can query in the corresponding shards based on the range of user IDs to improve query efficiency.

Next, we need to synchronize data between different shards. In MySQL, you can use the replication mechanism to achieve data synchronization. The replication mechanism mainly includes two parts: the master node and the slave node. The master node is responsible for receiving write operations and recording the write operations into the binary log; the slave node achieves data synchronization by reading the binary log of the master node. When the master node receives a write operation, it will record the write operation into the binary log and send it to the slave node at the same time. After receiving the log, the slave node will replay the log operation to achieve data synchronization.

In a distributed architecture, we can set each shard as a master-slave node. When a write operation occurs, first determine which shard to operate, then use the master node of this shard as the master node, and the master nodes of other shards as slave nodes. In this way, when a write operation occurs, the master node is responsible for receiving the write operation and recording the operation to the binary log, and other slave nodes achieve data synchronization by reading the binary log of the master node. In this way, all shards will be updated synchronously to achieve data consistency.

The following will demonstrate how to implement a horizontally scalable distributed architecture in MySQL. First, we need to create several shards and configure their master-slave relationship. Taking range-based sharding as an example, we create three shards, representing the user ID ranges of 1-100, 101-200, and 201-300.

-- 创建分片数据库
CREATE DATABASE db_1;
CREATE DATABASE db_2;
CREATE DATABASE db_3;

-- 创建分片表
CREATE TABLE db_1.user (
  id INT PRIMARY KEY,
  name VARCHAR(20),
  age INT
);
CREATE TABLE db_2.user (
  id INT PRIMARY KEY,
  name VARCHAR(20),
  age INT
);
CREATE TABLE db_3.user (
  id INT PRIMARY KEY,
  name VARCHAR(20),
  age INT
);

-- 配置主从关系
ALTER TABLE db_1.user
  ADD COLUMN imaster INT DEFAULT 0;
ALTER TABLE db_2.user
  ADD COLUMN imaster INT DEFAULT 0;
ALTER TABLE db_3.user
  ADD COLUMN imaster INT DEFAULT 0;

-- 设置主节点
UPDATE db_1.user SET imaster = 1 WHERE id BETWEEN 1 AND 100;
UPDATE db_2.user SET imaster = 1 WHERE id BETWEEN 101 AND 200;
UPDATE db_3.user SET imaster = 1 WHERE id BETWEEN 201 AND 300;

-- 设置从节点
CREATE TABLE db_1.user_slave (
  id INT PRIMARY KEY,
  name VARCHAR(20),
  age INT,
  imaster INT DEFAULT 0
);
CREATE TABLE db_2.user_slave (
  id INT PRIMARY KEY,
  name VARCHAR(20),
  age INT,
  imaster INT DEFAULT 0
);
CREATE TABLE db_3.user_slave (
  id INT PRIMARY KEY,
  name VARCHAR(20),
  age INT,
  imaster INT DEFAULT 0
);

-- 插入数据
INSERT INTO db_1.user(id, name, age) VALUES (1, '张三', 20);
INSERT INTO db_2.user(id, name, age) VALUES (101, '李四', 25);

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