sharding-jdbc垂直分库分表实战

• 资料
  分库分表的概念及应用场景详解
  分库分表带来的一些问题
  sharding-jdbc水平垂直分库分表环境搭建
  sharding-jdbc水平分库分表实战
  sharding-jdbc垂直分库分表实战

• 垂直分库分表目的
  1.主从表结构拆分,也在一定程度缓解索引性能,同时可以使主从表可以并发操作,不被行锁限制(垂直分表)
  2.微服务架构情况下,为了业务更好的区分,采用多schema模式,不同模块使用不同的schema(伪垂直分库)
  3.微服务架构情况下,由于某些模块业务量非常大,导致单库性能下降,影响其它模块,一般会单独拆到另外一个库中(真垂直分库)

• 垂直分表实现
  垂直分表就不做实验了,我们每天都在做垂直分表,比如主从表的结构

• 垂直分库实现

  public class springJdbcTest {
        
        
      public static void main(String[] args) throws SQLException {
        
        
  
          //获取数据源
          DataSource dataSource = getDataSource();
  
          //获取jdbctemplate
          JdbcTemplate jdbcTemplate = getJdbcTemplate(dataSource);
  
  
          //执行插入语句
          for(int i=1;i<=10;i++) {
        
        
              //执行插入用户语句
              jdbcTemplate.update("insert into t_user(user_name,user_age,user_type) values (?,?,?)",i,i,i);
              //执行插入订单语句
              jdbcTemplate.update("insert into t_order(user_id,order_price) values (?,?)",i,i);
          }
  
      }
  
  
      public static JdbcTemplate getJdbcTemplate( DataSource dataSource){
        
        
          JdbcTemplate jdbcTemplate = new JdbcTemplate();
          jdbcTemplate.setDataSource(dataSource);
          return jdbcTemplate;
      }
  
      
  
      public static DataSource getDataSource() throws SQLException {
        
        
          // 配置真实数据源
          Map<String, DataSource> dataSourceMap = new HashMap<>();
  
          // 配置第 1 个数据源
          DruidDataSource dataSource1 = new DruidDataSource();
          dataSource1.setDriverClassName("com.mysql.jdbc.Driver");
          dataSource1.setUrl("jdbc:mysql://localhost:3306/ds0?characterEncoding=utf-8&useSSL=false");
          dataSource1.setUsername("root");
          dataSource1.setPassword("123456");
          dataSourceMap.put("ds0", dataSource1);
  
          // 配置第 2 个数据源
          DruidDataSource dataSource2 = new DruidDataSource();
          dataSource2.setDriverClassName("com.mysql.jdbc.Driver");
          dataSource2.setUrl("jdbc:mysql://localhost:3307/ds0?characterEncoding=utf-8&useSSL=false");
          dataSource2.setUsername("root");
          dataSource2.setPassword("123456");
          dataSourceMap.put("ds1", dataSource2);
  
          // 配置表规则
          ShardingRuleConfiguration shardingRuleConfiguration=new ShardingRuleConfiguration();
  
          //用户表配置
          //配置逻辑表和实际表分布情况，配置用户表分布情况
          TableRuleConfiguration tableRuleConfiguration1 = new TableRuleConfiguration("t_user","ds0.t_user");
          //生成主键策略
          KeyGeneratorConfiguration keyGeneratorConfiguration1 = new KeyGeneratorConfiguration("snowflake","user_id");
          //用户表的表和库路由配置，都是单库单表情况，相当于多数据源情况，库和表都是固定
          ShardingStrategyConfiguration shardingStrategyConfiguration1 = new InlineShardingStrategyConfiguration("user_id","t_user");
          ShardingStrategyConfiguration shardingStrategyConfiguration2 = new InlineShardingStrategyConfiguration("user_id","ds0");
          tableRuleConfiguration1.setKeyGeneratorConfig(keyGeneratorConfiguration1);
          tableRuleConfiguration1.setTableShardingStrategyConfig(shardingStrategyConfiguration1);
          tableRuleConfiguration1.setDatabaseShardingStrategyConfig(shardingStrategyConfiguration2);
  
  
          //订单表配置
          //配置逻辑表和实际表分布情况，配置订单表分布情况
          TableRuleConfiguration tableRuleConfiguration2 = new TableRuleConfiguration("t_order","ds1.t_order");
          //生成主键策略
          KeyGeneratorConfiguration keyGeneratorConfiguration2 = new KeyGeneratorConfiguration("snowflake","order_id");
          //订单表的表和库路由配置，都是单库单表情况，相当于多数据源情况，库和表都是固定
          ShardingStrategyConfiguration shardingStrategyConfiguration3 = new InlineShardingStrategyConfiguration("order_id","t_order");
          ShardingStrategyConfiguration shardingStrategyConfiguration4 = new InlineShardingStrategyConfiguration("order_id","ds1");
          tableRuleConfiguration2.setKeyGeneratorConfig(keyGeneratorConfiguration2);
          tableRuleConfiguration2.setTableShardingStrategyConfig(shardingStrategyConfiguration3);
          tableRuleConfiguration2.setDatabaseShardingStrategyConfig(shardingStrategyConfiguration4);
  
          //实际表生成主键策略
          shardingRuleConfiguration.setTableRuleConfigs(Arrays.asList(tableRuleConfiguration1,tableRuleConfiguration2));
  
          return ShardingDataSourceFactory.createDataSource(dataSourceMap, shardingRuleConfiguration, new Properties());
      }
  }
  
  

• 垂直分库效果