<dependency>
<groupId>org.apache.shardingsphere</groupId>
<artifactId>shardingsphere-jdbc-core</artifactId>
<version>${shardingsphere.version}</version>
</dependency>
<!-- import if using ZooKeeper -->
<dependency>
<groupId>org.apache.shardingsphere</groupId>
<artifactId>shardingsphere-cluster-mode-repository-zookeeper-curator</artifactId>
<version>${shardingsphere.version}</version>
</dependency>
<!-- import if using Etcd -->
<dependency>
<groupId>org.apache.shardingsphere</groupId>
<artifactId>shardingsphere-cluster-mode-repository-etcd</artifactId>
<version>${shardingsphere.version}</version>
</dependency>
Using ZooKeeper as config center and registry center for example.
mode:
type: Cluster
repository:
type: ZooKeeper
props:
namespace: governance_ds
server-lists: localhost:2181
overwrite: true
// Create ShardingSphereDataSource
DataSource dataSource = YamlShardingSphereDataSourceFactory.createDataSource(yamlFile);
The ShardingSphereDataSource created by YamlShardingSphereDataSourceFactory 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 = YamlShardingSphereDataSourceFactory.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()) {
// ...
}
}
}