ShardingSphere构建读写分离的奥秘：策略、代码与指南

2024-02-14 12:58:11

当系统存储的数据量逐渐庞大，单一数据库往往无法满足海量数据的存储与处理需求，这时我们就需要借助分库分表技术来对数据进行拆分，从而提升系统的并发能力和数据处理效率。

ShardingSphere是一款优秀的开源数据库中间件，它为我们提供了丰富的分库分表解决方案，帮助我们轻松应对大数据场景下的挑战。在本文中，我们将深入剖析ShardingSphere读写分离方案的设计原理，并通过代码演示和操作指南，帮助您快速掌握这一方案的实现。

策略解析

ShardingSphere读写分离方案主要包括读写分离策略和数据同步策略两个部分。

读写分离策略

读写分离策略用于决定读写操作应该路由到哪个数据库。ShardingSphere提供了多种读写分离策略，包括：

主库优先策略：所有读写操作都路由到主库。
从库优先策略：所有读操作路由到从库，写操作路由到主库。
随机策略：读写操作随机路由到主库或从库。
一致性哈希策略：根据数据分片键将读写操作路由到主库或从库。

数据同步策略

数据同步策略用于保证主库与从库的数据一致性。ShardingSphere提供了多种数据同步策略，包括：

同步复制策略：数据变更实时同步到从库。
半同步复制策略：数据变更先同步到一个从库，然后从库再同步到其他从库。
异步复制策略：数据变更异步同步到从库。

代码演示

接下来，我们将通过一个代码示例来演示如何使用ShardingSphere构建读写分离方案。

首先，我们需要在pom文件中添加ShardingSphere的依赖：

<dependency>
    <groupId>org.apache.shardingsphere</groupId>
    <artifactId>shardingsphere-jdbc</artifactId>
    <version>5.2.0</version>
</dependency>

接着，我们需要在application.yml中进行相关配置：

spring:
  shardingsphere:
    datasource:
      master:
        url: jdbc:mysql://127.0.0.1:3306/sharding_db
        username: root
        password: root
      slave:
        url: jdbc:mysql://127.0.0.1:3306/sharding_db_replica
        username: root
        password: root
    rules:
      - sharding:
          tables:
            t_order:
              actual-data-nodes: master.t_order_${0..2}
              database-strategy:
                inline:
                  sharding-column: user_id
                  algorithm-expression: user_id % 3
              table-strategy:
                inline:
                  sharding-column: order_id
                  algorithm-expression: order_id % 3
          binding-tables:
            - t_order
            - t_order_item
      - readwrite-splitting:
          data-sources:
            readwrite-splitting-ds:
              masterDataSourceName: master
              slaveDataSourceNames: slave
          tables:
            t_order:
              strategy: readwrite-splitting-ds

最后，我们需要在MybatisPlusConfig中配置相关的Interceptor：

@Configuration
public class MybatisPlusConfig {

    @Bean
    public ShardingSphereInterceptor shardingSphereInterceptor() {
        ShardingSphereInterceptor shardingSphereInterceptor = new ShardingSphereInterceptor();
        shardingSphereInterceptor.setShardingSphereConfig(shardingSphereConfig());
        return shardingSphereInterceptor;
    }

    private ShardingSphereConfig shardingSphereConfig() {
        ShardingSphereConfig shardingSphereConfig = new ShardingSphereConfig();
        shardingSphereConfig.setShardingRules(shardingRules());
        shardingSphereConfig.setReadWriteSplittingRules(readWriteSplittingRules());
        return shardingSphereConfig;
    }

    private List<ShardingRule> shardingRules() {
        List<ShardingRule> shardingRules = new ArrayList<>();
        shardingRules.add(shardingRule());
        return shardingRules;
    }

    private ShardingRule shardingRule() {
        ShardingRule shardingRule = new ShardingRule();
        shardingRule.setTables(tables());
        shardingRule.setBindingTables(bindingTables());
        shardingRule.setShardingStrategyConfig(shardingStrategyConfig());
        return shardingRule;
    }

    private List<String> tables() {
        List<String> tables = new ArrayList<>();
        tables.add("t_order");
        tables.add("t_order_item");
        return tables;
    }

    private List<BindingTableRule> bindingTables() {
        List<BindingTableRule> bindingTableRules = new ArrayList<>();
        BindingTableRule bindingTableRule = new BindingTableRule();
        bindingTableRule.setLogicTable("t_order");
        bindingTableRule.setActualDataNodes("master.t_order_${0..2}");
        bindingTableRules.add(bindingTableRule);
        return bindingTableRules;
    }

    private ShardingStrategyConfig shardingStrategyConfig() {
        ShardingStrategyConfig shardingStrategyConfig = new ShardingStrategyConfig();
        shardingStrategyConfig.setShardingAlgorithm(shardingAlgorithm());
        return shardingStrategyConfig;
    }

    private StandardShardingAlgorithm shardingAlgorithm() {
        StandardShardingAlgorithm shardingAlgorithm = new StandardShardingAlgorithm();
        shardingAlgorithm.setShardingColumn("user_id");
        shardingAlgorithm.setShardingAlgorithm(new ModuloShardingAlgorithm());
        return shardingAlgorithm;
    }

    private List<ReadWriteSplittingRule> readWriteSplittingRules() {
        List<ReadWriteSplittingRule> readWriteSplittingRules = new ArrayList<>();
        readWriteSplittingRules.add(readWriteSplittingRule());
        return readWriteSplittingRules;
    }

    private ReadWriteSplittingRule readWriteSplittingRule() {
        ReadWriteSplittingRule readWriteSplittingRule = new ReadWriteSplittingRule();
        readWriteSplittingRule.setName("readwrite-splitting-ds");
        readWriteSplittingRule.setDataSources(dataSources());
        readWriteSplittingRule.setLoadBalancer(roundRobin());
        readWriteSplittingRule.setTables(tables());
        return readWriteSplittingRule;
    }

    private Map<String, DataSource> dataSources() {
        Map<String, DataSource> dataSources = new HashMap<>();
        dataSources.put("master", masterDataSource());
        dataSources.put("slave", slaveDataSource());
        return dataSources;
    }

    private DataSource masterDataSource() {
        DruidDataSource dataSource = new DruidDataSource();
        dataSource.setDriverClassName("com.mysql.jdbc.Driver");
        dataSource.setUrl("jdbc:mysql://127.0.0.1:3306/sharding_db");
        dataSource.setUsername("root");
        dataSource.setPassword("root");
        return dataSource;
    }

    private DataSource slaveDataSource() {
        DruidDataSource dataSource = new DruidDataSource();
        dataSource.setDriverClassName("com.mysql.jdbc.Driver");
        dataSource.setUrl("jdbc:mysql://127.0.0.1:3306/sharding_db_replica");
        dataSource.setUsername("root");
        dataSource.setPassword("root");
        return dataSource;
    }

    private LoadBalancer roundRobin() {
        return new RoundRobin();
    }
}