ShardingJDBC

一个客户端数据库分片库

原理

简单使用

<dependency>
    <groupId>io.shardingjdbc</groupId>
    <artifactId>sharding-jdbc-core</artifactId>
    <version>2.0.3</version>
</dependency>

#shardingjdbc配置
sharding:
  jdbc:
    data-sources:
      ###配置第一个从数据库
      ds_slave_0:
        password: 123
        jdbc-url: jdbc:mysql://192.168.182.132:3306/test?useUnicode=true&characterEncoding=utf-8&useSSL=true
        driver-class-name: com.mysql.jdbc.Driver
        username: root

      ###主数据库配置
      ds_master:
        password: 123
        jdbc-url: jdbc:mysql://192.168.182.131:3306/test?useUnicode=true&characterEncoding=utf-8&useSSL=true
        driver-class-name: com.mysql.jdbc.Driver
        username: root
    ###配置读写分离
    master-slave-rule:
      ###配置从库选择策略，提供轮询与随机，这里选择用轮询
      load-balance-algorithm-type: round_robin
      ####指定从数据库
      slave-data-source-names: ds_slave_0
      name: ds_ms
      ####指定主数据库
      master-data-source-name: ds_master

@Configuration
@EnableConfigurationProperties(ShardingMasterSlaveConfig.class)
@Log4j2
// 读取ds_master主数据源和读写分离配置
@ConditionalOnProperty({ "sharding.jdbc.data-sources.ds_master.jdbc-url",
        "sharding.jdbc.master-slave-rule.master-data-source-name" })
public class ShardingDataSourceConfig {

    @Autowired
    private ShardingMasterSlaveConfig shardingMasterSlaveConfig;

    @Bean
    public DataSource masterSlaveDataSource() throws SQLException {
        final Map<String, DataSource> dataSourceMap = Maps.newHashMap();
        dataSourceMap.putAll(shardingMasterSlaveConfig.getDataSources());
        final Map<String, Object> newHashMap = Maps.newHashMap();
        // 创建 MasterSlave数据源
        DataSource dataSource = MasterSlaveDataSourceFactory.createDataSource(dataSourceMap,
                shardingMasterSlaveConfig.getMasterSlaveRule(), newHashMap);
        log.info("masterSlaveDataSource config complete");
        return dataSource;
    }

}
@Data
@ConfigurationProperties(prefix = "sharding.jdbc")
public class ShardingMasterSlaveConfig {

    // 存放本地多个数据源
    private Map<String, HikariDataSource> dataSources = new HashMap<>();

    private MasterSlaveRuleConfiguration masterSlaveRule;
}

分表

    private DataSource buildDataSource() {
        // 1.设置分库映射
        Map<String, DataSource> dataSourceMap = new HashMap<>(2);
        dataSourceMap.put("ds_0", createDataSource("ds_0"));
        // dataSourceMap.put("ds_1", createDataSource("ds_1"));
        // 设置默认db为ds_0，也就是为那些没有配置分库分表策略的指定的默认库
        // 如果只有一个库，也就是不需要分库的话，map里只放一个映射就行了，只有一个库时不需要指定默认库，
        // 但2个及以上时必须指定默认库，否则那些没有配置策略的表将无法操作数据
        DataSourceRule rule = new DataSourceRule(dataSourceMap, "ds_0");
        // 2.设置分表映射，将t_order_0和t_order_1两个实际的表映射到t_order逻辑表
        TableRule orderTableRule = TableRule.builder("t_order").actualTables(Arrays.asList("t_order_0", "t_order_1"))
                .dataSourceRule(rule).build();
        // 3.具体的分库分表策略
        ShardingRule shardingRule = ShardingRule.builder().dataSourceRule(rule)
                .tableRules(Arrays.asList(orderTableRule))
                // 根据userid分片字段
                .tableShardingStrategy(new TableShardingStrategy("user_id", new TableShardingAlgorithm())).build();
        // 创建数据源
        DataSource dataSource = ShardingDataSourceFactory.createDataSource(shardingRule);
        return dataSource;
    }

    private DataSource createDataSource(String dataSourceName) {
        // 使用druid连接数据库
        DruidDataSource druidDataSource = new DruidDataSource();
        druidDataSource.setDriverClassName(className);
        druidDataSource.setUrl(String.format(url, dataSourceName));
        druidDataSource.setUsername(username);
        druidDataSource.setPassword(password);
        return druidDataSource;
    }

public class TableShardingAlgorithm implements SingleKeyTableShardingAlgorithm<Long> {

    // sql 中关键字 匹配符为 =的时候，表的路由函数
    @Override
    public String doEqualSharding(Collection<String> availableTargetNames, ShardingValue<Long> shardingValue) {
        for (String tableName : availableTargetNames) {
            if (tableName.endsWith(shardingValue.getValue() % 2 + "")) {
                return tableName;
            }
        }
        throw new IllegalArgumentException();
    }
    ...
}

spring boot快速整合

<dependency>
    <groupId>io.shardingsphere</groupId>
    <artifactId>sharding-jdbc-spring-boot-starter</artifactId>
    <version>3.0.0.M3</version>
</dependency>

sharding:
  jdbc:
    ####ds1
    datasource:
      names: ds0
      ds0:
        password: 123
        type: com.alibaba.druid.pool.DruidDataSource
        driver-class-name: com.mysql.cj.jdbc.Driver
        url: jdbc:mysql://192.168.182.131:3306/ds_0
        username: root
    config:
      sharding:
        tables:
          t_order:
            table-strategy:
              inline:
                #### 根据userid 进行分片
                sharding-column: user_id
                algorithm-expression: ds_0.t_order_$->{user_id % 2}
            actual-data-nodes: ds0.t_order_$->{0..1}
        props:
          sql:
            ### 开启分片日志
            show: true