SQLite GROUP BY子句

SQLite GROUP BY子句與SELECT語句一起使用，將相同的相同元素合并成一個組。

GROUP BY子句與SELECT語句中的WHERE子句一起使用，并且WHERE子句在ORDER BY子句之前。

語法：

SELECT column-list  
FROM table_name  
WHERE [ conditions ]  
GROUP BY column1, column2....columnN  
ORDER BY column1, column2....columnN

下面舉個例子來說明如何使用GROUP BY子句。 假設(shè)有一個名為student的表，具有以下數(shù)據(jù)：

sqlite> select * from student;
1|Maxsu|27|Shengzhen|20000.0
2|Minsu|25|Beijing|15000.0
3|Avgsu|23|Shanghai|2000.0
4|Linsu|25|Guangzhou|65000.0
5|Sqlsu|26|Haikou|25000.0
6|Javasu|21|Shengzhen|18000.0
sqlite>

使用GROUP BY查詢每位學(xué)生的費(fèi)用總額：

SELECT NAME, SUM(FEES) FROM STUDENT GROUP BY NAME;

執(zhí)行上面代碼，得到以下結(jié)果 -

現(xiàn)在，使用以下INSERT語句向student表中創(chuàng)建一些記錄，為了更好演示，插入的部分列的數(shù)據(jù)值是相同的：

INSERT INTO STUDENT VALUES (7, 'Linsu', 27, 'Haikou', 10000.00 );  
INSERT INTO STUDENT VALUES (8, 'Minsu', 23, 'Guangzhou', 5000.00 );  
INSERT INTO STUDENT VALUES (9, 'Maxsu', 23, 'Shenzhen', 9000.00 );

執(zhí)行上面語句插入數(shù)據(jù)后，現(xiàn)在表中存在的數(shù)據(jù)如下 -

sqlite> select * from student;
1|Maxsu|27|Shengzhen|20000.0
2|Minsu|25|Beijing|15000.0
3|Avgsu|23|Shanghai|2000.0
4|Linsu|25|Guangzhou|65000.0
5|Sqlsu|26|Haikou|25000.0
6|Javasu|21|Shengzhen|18000.0
7|Linsu|27|Haikou|10000.0
8|Minsu|23|Guangzhou|5000.0
9|Maxsu|23|Shenzhen|9000.0
sqlite>

如上所示，現(xiàn)在有幾個字段：name,age和city中的值是相同的。

現(xiàn)在，使用GROUP BY語句按NAME列來分組并對同分組內(nèi)的所有的記錄的fees列求和：

 select name, sum(fees) from student group by name;

執(zhí)行上面代碼，得到以下結(jié)果 -

可以使用ORDER BY子句和GROUP BY按升序或降序排列數(shù)據(jù)。

SELECT NAME, SUM(FEES) AS total_fees FROM STUDENT GROUP BY NAME ORDER BY NAME DESC;
-- 或者
SELECT NAME, SUM(FEES) AS total_fees FROM STUDENT GROUP BY NAME ORDER BY total_fees DESC;

執(zhí)行上面代碼，得到以下結(jié)果 -

sqlite> SELECT NAME, SUM(FEES) AS total_fees FROM STUDENT GROUP BY NAME ORDER BY NAME DESC;
Sqlsu|25000.0
Minsu|20000.0
Maxsu|29000.0
Linsu|75000.0
Javasu|18000.0
Avgsu|2000.0
sqlite>
sqlite> SELECT NAME, SUM(FEES) AS total_fees FROM STUDENT GROUP BY NAME ORDER BY total_fees DESC;
Linsu|75000.0
Maxsu|29000.0
Sqlsu|25000.0
Minsu|20000.0
Javasu|18000.0
Avgsu|2000.0
sqlite>