一般来说，select查询的resultset中的行从0开始。使用offset子句，我们可以决定从哪里考虑输出。 例如，如果我们选择偏移为0，结果将像往常一样，如果我们选择偏移为5，结果从第五行开始。
语法
以下是Impala中的biasclause的语法。
select data from table_name Group BY col_name;
例
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
您可以按其id的升序排列表中的记录，并使用limit和order by子句将记录数限制为4，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
以下是偏移子句的示例。 这里，我们按照id的顺序在customers表中获取记录，并从第0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
以相同的方式，您可以从具有偏移5的行开始从客户表获取四个记录，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