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读写分离

背景信息

Java API 形式配置的读写分离可以方便的适用于各种场景,不依赖额外的 jar 包,用户只需要通过 java 代码构造读写分离数据源便可以使用读写分离功能。

参数解释

配置入口

类名称:org.apache.shardingsphere.readwritesplitting.config.ReadwriteSplittingRuleConfiguration

可配置属性:

名称 数据类型 说明
dataSources (+) Collection<ReadwriteSplittingDataSourceRuleConfiguration> 读写数据源配置
loadBalancers (*) Map<String, AlgorithmConfiguration> 从库负载均衡算法配置

主从数据源配置

类名称:org.apache.shardingsphere.readwritesplitting.config.rule.ReadwriteSplittingDataSourceGroupRuleConfiguration

可配置属性:

名称 数据类型 说明 默认值
name String 读写分离数据源名称 -
writeDataSourceName String 写库数据源名称 -
readDataSourceNames List<String> 读库数据源名称 -
transactionalReadQueryStrategy (?) TransactionalReadQueryStrategy 事务内读请求的路由策略,可选值:PRIMARY(路由至主库)、FIXED(同一事务内路由至固定数据源)、DYNAMIC(同一事务内路由至非固定数据源) DYNAMIC
loadBalancerName (?) String 读库负载均衡算法名称 轮询负载均衡算法

算法类型的详情,请参见内置负载均衡算法列表

操作步骤

  1. 添加读写分离数据源
  2. 设置负载均衡算法
  3. 使用读写分离数据源

配置示例

public DataSource getDataSource() throws SQLException {
        ReadwriteSplittingDataSourceRuleConfiguration dataSourceConfig = new ReadwriteSplittingDataSourceRuleConfiguration(
                "demo_read_query_ds", "demo_write_ds", Arrays.asList("demo_read_ds_0", "demo_read_ds_1"), "demo_weight_lb");
        Properties algorithmProps = new Properties();
        algorithmProps.setProperty("demo_read_ds_0", "2");
        algorithmProps.setProperty("demo_read_ds_1", "1");
        Map<String, AlgorithmConfiguration> algorithmConfigMap = new HashMap<>(1);
        algorithmConfigMap.put("demo_weight_lb", new AlgorithmConfiguration("WEIGHT", algorithmProps));
        ReadwriteSplittingRuleConfiguration ruleConfig = new ReadwriteSplittingRuleConfiguration(Collections.singleton(dataSourceConfig), algorithmConfigMap);
        Properties props = new Properties();
        props.setProperty("sql-show", Boolean.TRUE.toString());
        return ShardingSphereDataSourceFactory.createDataSource(createDataSourceMap(), Collections.singleton(ruleConfig), props);
    }
    
    private Map<String, DataSource> createDataSourceMap() {
        Map<String, DataSource> result = new HashMap<>(3, 1);
        result.put("demo_write_ds", DataSourceUtil.createDataSource("demo_write_ds"));
        result.put("demo_read_ds_0", DataSourceUtil.createDataSource("demo_read_ds_0"));
        result.put("demo_read_ds_1", DataSourceUtil.createDataSource("demo_read_ds_1"));
        return result;
    }

相关参考