impala 入门教程 impala 限制条款

2024-02-26 开发教程 impala 入门教程 匿名 3

Impala中的limit子句用于将结果集的行数限制为所需的数,即查询的结果集不包含超过指定限制的记录。

语法

以下是Impala中Limit子句的语法。

select * from table_name order by id limit numerical_expression;

假设我们在数据库my_db中有一个名为customers的表,其内容如下 -

[quickstart.cloudera:21000] > select * from customers;
Query: select * from customers
+----+----------+-----+-----------+--------+
| id | name | age | address | salary |
+----+----------+-----+-----------+--------+
| 3 | kaushik | 23 | Kota | 30000 |
| 6 | Komal | 22 | MP | 32000 |
| 1 | Ramesh | 32 | Ahmedabad | 20000 |
| 5 | Hardik | 27 | Bhopal | 40000 |
| 2 | Khilan | 25 | Delhi | 15000 |
| 8 | ram | 22 | vizag | 31000 |
| 9 | robert | 23 | banglore | 28000 |
| 7 | ram | 25 | chennai | 23000 |
| 4 | Chaitali | 25 | Mumbai | 35000 |
+----+----------+-----+-----------+--------+
Fetched 9 row(s) in 0.51s

您可以使用order by子句按照id的升序排列表中的记录,如下所示。

[quickstart.cloudera:21000] > select * from customers order by id;
Query: select * from customers order by id
+----+----------+-----+-----------+--------+
| id | name | age | address | salary |
+----+----------+-----+-----------+--------+
| 1 | Ramesh | 32 | Ahmedabad | 20000 |
| 2 | Khilan | 25 | Delhi | 15000 |
| 3 | kaushik | 23 | Kota | 30000 |
| 4 | Chaitali | 25 | Mumbai | 35000 |
| 5 | Hardik | 27 | Bhopal | 40000 |
| 6 | Komal | 22 | MP | 32000 |
| 7 | ram | 25 | chennai | 23000 |
| 8 | ram | 22 | vizag | 31000 |
| 9 | robert | 23 | banglore | 28000 |
+----+----------+-----+-----------+--------+
Fetched 9 row(s) in 0.54s

现在,使用limit子句,您可以将输出的记录数限制为4,使用limit子句如下所示。

[quickstart.cloudera:21000] > select * from customers order by id limit 4;

执行时,上述查询给出以下输出。

Query: select * from customers order by id limit 4
+----+----------+-----+-----------+--------+
| id | name | age | address | salary |
+----+----------+-----+-----------+--------+
| 1 | Ramesh | 32 | Ahmedabad | 20000 |
| 2 | Khilan | 25 | Delhi | 15000 |
| 3 | kaushik | 23 | Kota | 30000 |
| 4 | Chaitali | 25 | Mumbai | 35000 |
+----+----------+-----+-----------+--------+
Fetched 4 row(s) in 0.64s