shardingjdbc批量插入例子

以下是使用ShardingJDBC进行批量插入的示例代码： ``` import java.sql.Connection; import java.sql.PreparedStatement; import java.sql.SQLException; import java.util.ArrayList; import java.util.List; import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm; import org.apache.shardingsphere.api.sharding.standard.RangeShardingAlgorithm; import org.apache.shardingsphere.api.sharding.standard.StandardShardingStrategyConfiguration; import org.apache.shardingsphere.driver.api.ShardingDataSourceFactory; import org.apache.shardingsphere.shardingjdbc.api.ShardingDataSource; import org.apache.shardingsphere.shardingjdbc.jdbc.core.datasource.ShardingDataSourceWrapper; import org.apache.shardingsphere.shardingjdbc.jdbc.core.statement.ShardingPreparedStatement; import org.apache.shardingsphere.shardingjdbc.jdbc.core.statement.ShardingStatement; import com.alibaba.druid.pool.DruidDataSource; public class ShardingJDBCBatchInsertExample { public static void main(String[] args) throws SQLException { // 配置分库 List<DruidDataSource> dataSourceList = new ArrayList<>(); for (int i = 0; i < 2; i++) { DruidDataSource dataSource = new DruidDataSource(); dataSource.setDriverClassName("com.mysql.jdbc.Driver"); dataSource.setUrl("jdbc:mysql://localhost:3306/db" + i + "?serverTimezone=UTC&useSSL=false"); dataSource.setUsername("root"); dataSource.setPassword("root"); dataSourceList.add(dataSource); } // 配置分表 PreciseShardingAlgorithm<Long> preciseShardingAlgorithm = (databaseNames, shardingValue) -> { for (String each : databaseNames) { if (each.endsWith(shardingValue.getValue() % 2 + "")) { return each; } } throw new UnsupportedOperationException(); }; RangeShardingAlgorithm<Long> rangeShardingAlgorithm = (databaseNames, shardingValue) -> { List<String> result = new ArrayList<>(); Long lowerValue = shardingValue.getValueRange().lowerEndpoint(); Long upperValue = shardingValue.getValueRange().upperEndpoint(); for (String each : databaseNames) { String value = each.substring(each.length() - 1); Long intValue = Long.parseLong(value); if (intValue >= lowerValue && intValue <= upperValue) { result.add(each); } } return result; }; StandardShardingStrategyConfiguration databaseShardingStrategyConfiguration = new StandardShardingStrategyConfiguration("id", preciseShardingAlgorithm, rangeShardingAlgorithm); ShardingDataSource shardingDataSource = ShardingDataSourceFactory.createDataSource(dataSourceList, Collections.singleton(databaseShardingStrategyConfiguration), new Properties()); // 执行批量插入 Connection conn = shardingDataSource.getConnection(); String sql = "insert into t_order (id, user_id, status) values (?, ?, ?)"; ShardingPreparedStatement pstmt = (ShardingPreparedStatement) conn.prepareStatement(sql); for (int i = 1; i <= 100; i++) { pstmt.setLong(1, i); pstmt.setLong(2, i % 10); pstmt.setString(3, "INIT"); pstmt.addBatch(); } pstmt.executeBatch(); conn.close(); } } ``` 该示例代码中，我们首先配置了两个Druid数据源，分别对应两个数据库db0和db1。然后，我们使用PreciseShardingAlgorithm和RangeShardingAlgorithm两种算法配置分库分表策略。具体而言，我们根据订单ID（id）的值来判断该订单属于哪个数据库和表，其中id % 2的值为0时，订单会被分配到db0数据库，否则分配到db1数据库；对于每个数据库，我们又根据id值的范围来判断该订单属于哪个表。 在执行批量插入时，我们首先通过shardingDataSource.getConnection()方法获取一个连接。然后，我们构造一个PreparedStatement对象，设置好参数，调用addBatch()方法将数据加入批处理队列中，最后调用executeBatch()方法执行批处理操作。由于使用了ShardingJDBC，ShardingPreparedStatement对象会在内部根据id值的分片规则自动将订单插入到对应的数据库和表中。