云数据库 ClickHouse：通过JDBC方式连接ClickHouse

操作步骤

1. 使用Eclipse或其他IDE工具创建Maven项目并引入ClickHouse驱动依赖包。

   <dependency>
       <groupId>org.lz4</groupId>
       <artifactId>lz4-java</artifactId>
       <version>1.8.0</version>
   </dependency>
   <dependency>
       <groupId>com.clickhouse</groupId>
       <artifactId>clickhouse-jdbc</artifactId>
       <version>0.4.6</version>
   </dependency>

2. 编写应用程序代码。

   以下代码演示了如何使用JDBC驱动连接集群和创建表以及写入数据。使用过程需修改集群连接串和端口参数。如果应用和ClickHouse实例在同一个VPC环境，请使用集群VPC地址，如果不在相同的VPC环境则需使用集群外网地址，如何获取外网地址，请参见申请和释放外网地址。

   import java.sql.Connection;
   import java.sql.DriverManager;
   import java.sql.ResultSet;
   import java.sql.SQLException;
   import java.sql.Statement;
   import java.sql.Timestamp;
   import java.text.ParseException;
   import java.text.SimpleDateFormat;
   import java.util.Date;
   
   public class Main4 {
     private static final String DATE_FORMAT = "yyyy-MM-dd HH:mm:ss";
     private static final SimpleDateFormat SIMPLE_DATE_FORMAT = new SimpleDateFormat(DATE_FORMAT);
   
     public static void main(String[] args) throws ClassNotFoundException, SQLException, InterruptedException, ParseException {
       String url = "your url";  //云数据库ClickHouse的VPC地址或外网地址
       String username = "your username";   //云数据库ClickHouse的账号
       String password = "your password";  //云数据库ClickHouse的密码
   
       String connectionStr = "jdbc:clickhouse://" + url + ":8123";
   
       try (Connection connection = DriverManager.getConnection(connectionStr, username, password);
            Statement stmt = connection.createStatement()) {
   
         {
           String createTableDDL = "create table test_table on cluster default " +
               "(id UInt32, " +
               "dt_str String, " +
               "dt_col DateTime) " +
               "engine=ReplicatedMergeTree('/clickhouse/tables/{database}/{table}/{shard}', '{replica}')" +
               "partition by toYYYYMM(dt_col)" +
               "order by (id)" +
               "primary key (id)" +
               "sample by (id)" +
               "settings index_granularity = 8192;";
           stmt.execute(createTableDDL);
           System.out.println("create local table done.");
         }
         {
           String createTableDDL = "create table test_dist on cluster default " +
               "as default.test_table " +
               "engine=Distributed(default, default, test_table, rand());";
           stmt.execute(createTableDDL);
           System.out.println("create distributed table done");
         }
   
         System.out.println("write 100000 rows...");
         long startTime = System.currentTimeMillis();
   
         // Write 10 batch
         for (int batch = 0; batch < 10; batch++) {
           StringBuilder sb = new StringBuilder();
   
           // Build one batch
           sb.append("insert into test_dist values(" + (batch * 10000) + ", '2020-02-19 16:00:00', '2020-02-19 16:00:00')");
           for (int row = 1; row < 10000; row++) {
             sb.append(", (" + (batch * 10000 + row) + ", '2020-02-19 16:00:00', '2020-02-19 16:00:00')");
           }
   
           // Write one batch: 10000 rows
           stmt.execute(sb.toString());
         }
   
         long endTime = System.currentTimeMillis();
         System.out.println("total time cost to write 10W rows: " + (endTime - startTime) + "ms");
   
         Thread.sleep(2 * 1000);
   
         System.out.println("Select count(id)...");
         try (ResultSet rs = stmt.executeQuery("select count(id) from test_dist");) {
           while (rs.next()) {
             int count = rs.getInt(1);
             System.out.println("id count: " + count);
           }
         }
   
         try (ResultSet rs = stmt.executeQuery("select id, dt_str, dt_col from test_dist limit 10");) {
           while (rs.next()) {
             int id = rs.getInt(1);
             String dateStr = rs.getString(2);
             Timestamp time = rs.getTimestamp(3);
   
             String defaultDate = SIMPLE_DATE_FORMAT.format(new Date(time.getTime()));
             System.out.println("id: " + id
                 + ", date_str:" + dateStr
                 + ", date_col:" + defaultDate);
           }
         }
       }
     }
   }