impala ORDER BY子句

Impala ORDER BY子句用于根據(jù)一個(gè)或多個(gè)列以升序或降序?qū)?shù)據(jù)進(jìn)行排序。 默認(rèn)情況下，一些數(shù)據(jù)庫(kù)按升序?qū)Σ樵兘Y(jié)果進(jìn)行排序。

語(yǔ)法

以下是ORDER BY子句的語(yǔ)法。

select * from table_name ORDER BY col_name [ASC|DESC] [NULLS FIRST|NULLS LAST]

可以使用關(guān)鍵字ASC或DESC分別按升序或降序排列表中的數(shù)據(jù)。

以同樣的方式，如果我們使用NULLS FIRST，表中的所有空值都排列在頂行; 如果我們使用NULLS LAST，包含空值的行將最后排列。

例

假設(shè)我們?cè)跀?shù)據(jù)庫(kù)my_db中有一個(gè)名為customers的表，其內(nèi)容如下 -

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

以下是使用order by子句按照其ID的升序排列customers表中的數(shù)據(jù)的示例。

[quickstart.cloudera:21000] > Select * from customers ORDER BY id asc;

在執(zhí)行時(shí)，上述查詢產(chǎn)生以下輸出。

Query: select * from customers ORDER BY id asc 
+----+----------+-----+-----------+--------+ 
| 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  | 
+----+----------+-----+-----------+--------+ 
Fetched 6 row(s) in 0.56s

同樣，您可以使用order by子句按降序排列customers表的數(shù)據(jù)，如下所示。

[quickstart.cloudera:21000] > Select * from customers ORDER BY id desc;

在執(zhí)行時(shí)，上述查詢產(chǎn)生以下輸出。

Query: select * from customers ORDER BY id desc 
+----+----------+-----+-----------+--------+ 
| id | name     | age | address   | salary | 
+----+----------+-----+-----------+--------+ 
| 6  | Komal    | 22  | MP        | 32000  | 
| 5  | Hardik   | 27  | Bhopal    | 40000  | 
| 4  | Chaitali | 25  | Mumbai    | 35000  | 
| 3  | kaushik  | 23  | Kota      | 30000  | 
| 2  | Khilan   | 25  | Delhi     | 15000  |
| 1  | Ramesh   | 32  | Ahmedabad | 20000  | 
+----+----------+-----+-----------+--------+ 
Fetched 6 row(s) in 0.54s