+++ title = “Use YAML” weight = 2 +++
<dependency> <groupId>org.apache.shardingsphere</groupId> <artifactId>shardingsphere-jdbc-orchestration</artifactId> <version>${shardingsphere.version}</version> </dependency> <!-- import if using ZooKeeper --> <dependency> <groupId>org.apache.shardingsphere</groupId> <artifactId>shardingsphere-orchestration-center-zookeeper-curator</artifactId> <version>${shardingsphere.version}</version> </dependency> <!-- import if using Etcd --> <dependency> <groupId>org.apache.shardingsphere</groupId> <artifactId>shardingsphere-orchestration-center-etcd</artifactId> <version>${shardingsphere.version}</version> </dependency>
Using ZooKeeper as config center and registry center for example.
orchestration: orchestration_ds: orchestrationType: registry_center,config_center,metadata_center instanceType: zookeeper serverLists: localhost:2181 namespace: orchestration props: overwrite: true
// Create OrchestrationShardingSphereDataSource DataSource dataSource = YamlOrchestrationShardingSphereDataSourceFactory.createDataSource(yamlFile);
The OrchestrationShardingSphereDataSource created by YamlOrchestrationShardingSphereDataSourceFactory implements the standard JDBC DataSource interface. Developer can choose to use native JDBC or ORM frameworks such as JPA or MyBatis through the DataSource.
Take native JDBC usage as an example:
DataSource dataSource = YamlOrchestrationShardingSphereDataSourceFactory.createDataSource(yamlFile); String sql = "SELECT i.* FROM t_order o JOIN t_order_item i ON o.order_id=i.order_id WHERE o.user_id=? AND o.order_id=?"; try ( Connection conn = dataSource.getConnection(); PreparedStatement ps = conn.prepareStatement(sql)) { ps.setInt(1, 10); ps.setInt(2, 1000); try (ResultSet rs = preparedStatement.executeQuery()) { while(rs.next()) { // ... } } }