发布于 2015-07-25 11:05:08 | 753 次阅读 | 评论: 0 | 来源: 网络整理
本章介绍了SELECT语句的GROUP BY子句。GROUP BY子句用于分类所有记录结果的特定集合列。它被用来查询一组记录。
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];
让我们以SELECT... GROUP BY子句为例。假设员工表有如下Id, Name, Salary, Designation, 和 Dept字段。产生一个查询以检索每个部门的员工数量。
+------+--------------+-------------+-------------------+--------+
| 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 |
+------+--------------+-------------+-------------------+--------+
下面使用上述业务情景查询检索员工的详细信息。
hive> SELECT Dept,count(*) FROM employee GROUP BY DEPT;
成功执行查询后,能看到以下回应:
+------+--------------+
| Dept | Count(*) |
+------+--------------+
|Admin | 1 |
|PR | 2 |
|TP | 3 |
+------+--------------+
下面给出的是JDBC程序应用对给定的GROUP BY子句例子。
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();
}
}
保存程序在一个名为HiveQLGroupBy.java文件。使用下面的命令来编译并执行这个程序。
$ javac HiveQLGroupBy.java
$ java HiveQLGroupBy
Dept Count(*)
Admin 1
PR 2
TP 3