Aggregate functions often need an added GROUP BY statement.
The GROUP BY Statement
The GROUP BY statement is used in conjunction with the aggregate functions to group the result-set by one or more columns.SQL GROUP BY Syntax
SELECT column_name, aggregate_function(column_name)
FROM table_name
WHERE column_name operator value
GROUP BY column_name
FROM table_name
WHERE column_name operator value
GROUP BY column_name
SQL GROUP BY Example
We have the following "Orders" table:O_Id | OrderDate | OrderPrice | Customer |
---|---|---|---|
1 | 2008/11/12 | 1000 | Hansen |
2 | 2008/10/23 | 1600 | Nilsen |
3 | 2008/09/02 | 700 | Hansen |
4 | 2008/09/03 | 300 | Hansen |
5 | 2008/08/30 | 2000 | Jensen |
6 | 2008/10/04 | 100 | Nilsen |
We will have to use the GROUP BY statement to group the customers.
We use the following SQL statement:
SELECT Customer,SUM(OrderPrice) FROM Orders
GROUP BY Customer
GROUP BY Customer
Customer | SUM(OrderPrice) |
---|---|
Hansen | 2000 |
Nilsen | 1700 |
Jensen | 2000 |
Let's see what happens if we omit the GROUP BY statement:
SELECT Customer,SUM(OrderPrice) FROM Orders
Customer | SUM(OrderPrice) |
---|---|
Hansen | 5700 |
Nilsen | 5700 |
Hansen | 5700 |
Hansen | 5700 |
Jensen | 5700 |
Nilsen | 5700 |
Explanation of why the above SELECT statement cannot be used: The SELECT statement above has two columns specified (Customer and SUM(OrderPrice). The "SUM(OrderPrice)" returns a single value (that is the total sum of the "OrderPrice" column), while "Customer" returns 6 values (one value for each row in the "Orders" table). This will therefore not give us the correct result. However, you have seen that the GROUP BY statement solves this problem.
GROUP BY More Than One Column
We can also use the GROUP BY statement on more than one column, like this: SELECT Customer,OrderDate,SUM(OrderPrice) FROM Orders
GROUP BY Customer,OrderDate
GROUP BY Customer,OrderDate
No comments:
Post a Comment