java 使用ShardingDataSourceFactory.createDataSource() 创建新数据源，并且重新初始化Sharding-JDBC的数据源，代码示例

以下是使用 ShardingDataSourceFactory.createDataSource() 创建新数据源并重新初始化 Sharding-JDBC 数据源的代码示例：

import org.apache.shardingsphere.api.config.ShardingRuleConfiguration;
import org.apache.shardingsphere.api.config.rule.TableRuleConfiguration;
import org.apache.shardingsphere.api.sharding.ShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.ShardingRule;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.RangeShardingAlgorithm;
import org.apache.shardingsphere.shardingjdbc.api.ShardingDataSourceFactory;
import org.apache.shardingsphere.shardingjdbc.jdbc.core.datasource.ShardingDataSource;

import javax.sql.DataSource;
import java.sql.SQLException;
import java.util.HashMap;
import java.util.Map;

public class ShardingJDBCExample {
    public static void main(String[] args) throws SQLException {
        // 创建数据源 Map
        Map<String, DataSource> dataSourceMap = new HashMap<>();
        dataSourceMap.put("ds0", createDataSource("ds0"));
        dataSourceMap.put("ds1", createDataSource("ds1"));
        // 配置分片规则
        ShardingRuleConfiguration shardingRuleConfig = new ShardingRuleConfiguration();
        TableRuleConfiguration tableRuleConfig = new TableRuleConfiguration("t_order", "ds${0..1}.t_order_${0..1}");
        shardingRuleConfig.getTableRuleConfigs().add(tableRuleConfig);
        // 配置分库算法
        PreciseShardingAlgorithm<Long> preciseShardingAlgorithm = (ShardingValue<Long> shardingValue) -> {
            // 根据订单 ID 取模 2，决定使用哪个库
            for (Long value : shardingValue.getValues()) {
                if (value % 2 == 0) {
                    return "ds0";
                } else {
                    return "ds1";
                }
            }
            throw new UnsupportedOperationException();
        };
        RangeShardingAlgorithm<Long> rangeShardingAlgorithm = (ShardingValue<Long> shardingValue) -> {
            // 省略逻辑，根据范围取模确定库
            return null;
        };
        shardingRuleConfig.setDefaultDatabaseShardingStrategyConfig(new StandardShardingStrategyConfiguration("order_id", preciseShardingAlgorithm, rangeShardingAlgorithm));
        // 配置分表算法
        PreciseShardingAlgorithm<Long> preciseTableShardingAlgorithm = (ShardingValue<Long> shardingValue) -> {
            // 根据订单 ID 取模 2，决定使用哪个表
            for (Long value : shardingValue.getValues()) {
                if (value % 2 == 0) {
                    return "t_order_0";
                } else {
                    return "t_order_1";
                }
            }
            throw new UnsupportedOperationException();
        };
        RangeShardingAlgorithm<Long> rangeTableShardingAlgorithm = (ShardingValue<Long> shardingValue) -> {
            // 省略逻辑，根据范围取模确定表
            return null;
        };
        tableRuleConfig.setDatabaseShardingStrategyConfig(new StandardShardingStrategyConfiguration("order_id", preciseTableShardingAlgorithm, rangeTableShardingAlgorithm));
        // 创建 Sharding 数据源
        DataSource dataSource = ShardingDataSourceFactory.createDataSource(dataSourceMap, shardingRuleConfig, new Properties());
        // 重新初始化 Sharding 数据源
        ShardingDataSource shardingDataSource = (ShardingDataSource) dataSource;
        shardingDataSource.initSharding();
    }

    private static DataSource createDataSource(String dataSourceName) {
        // 省略创建数据源的代码，根据 dataSourceName 创建对应的数据源
        return null;
    }
}

需要注意的是，创建新数据源后，必须重新初始化 Sharding 数据源，才能使新数据源生效。