通常， select 查询的结果集中的行从0开始.使用 offset 子句，我们可以决定应该考虑输出的位置.例如，如果我们选择偏移量为0，则结果将如常，如果我们选择偏移量为5，则结果从第五行开始.
以下是偏移的语法Impala中的子句.
select data from table_name Group BY col_name;
假设我们在数据库中有一个名为 customers 的表 my_db 及其内容如下 :
[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
您可以按照其ID的升序排列表中的记录并限制记录数到4，使用 limit 和 order by 子句，如下所示.
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
以下是 offset 子句的示例.在这里，我们按照id的顺序获取 customers 表中的记录，并从0 th 行开始打印前四行.
[quickstart.cloudera:21000] > select * from customers order by id limit 4 offset 0;
执行时，上述查询给出以下结果.
Query: select * from customers order by id limit 4 offset 0 +----+----------+-----+-----------+--------+ | 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 0.62s
以同样的方式，您可以从 customers 表中获取四个记录从具有偏移量5的行开始，如下所示.
[quickstart.cloudera:21000] > select * from customers order by id limit 4 offset 5; Query: select * from customers order by id limit 4 offset 5 +----+--------+-----+----------+--------+ | id | name | age | address | salary | +----+--------+-----+----------+--------+ | 6 | Komal | 22 | MP | 32000 | | 7 | ram | 25 | chennai | 23000 | | 8 | ram | 22 | vizag | 31000 | | 9 | robert | 23 | banglore | 28000 | +----+--------+-----+----------+--------+ Fetched 4 row(s) in 0.52s
