HiveQL Select-Group By子句
本章将详细介绍SELECT语句中的GROUP BY子句。GROUP BY子句用于使用特定的集合列对结果集中的所有记录进行分组。它用于查询一组记录。
阅读更多:Hive 教程
语法
GROUP BY子句的语法如下:
SELECT [ALL|DISTINCT] select_expr,select_expr,...
FROM table_reference
[WHERE where_condition]
[GROUP BY col_list]
[HAVING having_condition]
[ORDER BY col_list]]
[LIMIT number];
样例
让我们以SELECT…GROUP BY子句为例。假设以下员工表,具有Id,Name,Salary,Designation和Dept字段。生成一个查询,以检索每个部门中的员工数量。
+------+--------------+-------------+-------------------+--------+
| ID | Name | Salary | Designation | Dept |
+------+--------------+-------------+-------------------+--------+
|1201 | Gopal | 45000 | Technical manager | TP |
|1202 | Manisha | 45000 | Proofreader | PR |
|1203 | Masthanvali | 40000 | Technical writer | TP |
|1204 | Krian | 45000 | Proofreader | PR |
|1205 | Kranthi | 30000 | Op Admin | Admin |
+------+--------------+-------------+-------------------+--------+
以下查询使用上述方案检索员工详细信息。
hive> SELECT Dept,count(*) FROM employee GROUP BY DEPT;
成功执行查询后,您会看到以下响应:
+------+--------------+
| Dept | Count(*) |
+------+--------------+
|Admin | 1 |
|PR | 2 |
|TP | 3 |
+------+--------------+
JDBC程序
以下是应用给定示例的Group By子句的JDBC程序。
import java.sql.SQLException;
import java.sql.Connection;
import java.sql.ResultSet;
import java.sql.Statement;
import java.sql.DriverManager;
public class HiveQLGroupBy {
private static String driverName = "org.apache.hadoop.hive.jdbc.HiveDriver";
public static void main(String[] args) throws SQLException {
// Register driver and create driver instance
Class.forName(driverName);
// get connection
Connection con = DriverManager.
getConnection("jdbc:hive://localhost:10000/userdb", "", "");
// create statement
Statement stmt = con.createStatement();
// execute statement
Resultset res = stmt.executeQuery(“SELECT Dept,count(*) ” + “FROM employee GROUP BY DEPT; ”);
System.out.println(" Dept \t count(*)");
while (res.next()) {
System.out.println(res.getString(1) + " " + res.getInt(2));
}
con.close();
}
}
将程序保存在名为HiveQLGroupBy.java的文件中。使用以下命令编译和执行此程序。
$ javac HiveQLGroupBy.java
$ java HiveQLGroupBy
输出:
部门 数量(*)
Admin 1
PR 2
TP 3