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table named employee is given below:

id salary

10  100 
10  100
10  100

what should be the query in sql server 2012 to get following output

id salary 

10 300
10 300
10 300

that is sum of salary

You probably want:

select e.*, sum(e.sal) over (partition by as total_salary
from employee e;

That is, I'm guessing you want the sum per id.

GROUP BY does not remove duplicates, How do you combine duplicate rows and sum values in access? The OVER clause lets us execute the COUNT function without the need for a group by and in the above example it will return the count of all records returned in the query.

Based on sample data you can use window function :

select e.*, sum(sal) over ()
from emp e;

However, if you want the total salary for each Ids then include partition clause :

select e.*, sum(sal) over (partition by id) as tot_salary 
from emp e;

MySQL INSERT ON DUPLICATE KEY UPDATE, SELECT value, SUM(years) AS years, SUM(total) AS total FROM customers GROUP BY value;. You want the sum of the years and the sum of  SQL delete duplicate Rows using Group By and having clause In this method, we use the SQL GROUP BY clause to identify the duplicate rows. The Group By clause groups data as per the defined columns and we can use the COUNT function to check the occurrence of a row.

The right way is using SUM window function by ID

select, sum(salary) over (PARTITION BY ID) salary  
from T t

Another way you can use correlate select

SELECT,(SELECT SUM(salary) FROM T tt where = salary  

c# online

If you know the values to always be the same, then one simple (although not necessarily optimized) solution is to wrap your original GROUP BY query in another query (making the original a subquery) and then use the SUM function in the outer query, without a GROUP BY clause. SUM() function with group by. SUM is used with a GROUP BY clause. The aggregate functions summarize the table data. Once the rows are divided into groups, the aggregate functions are applied in order to return just one value per group. It is better to identify each summary row by including the GROUP BY clause in the query resulst.


SELECT, emp2.salary
     (SELECT id, SUM(salary) AS salary GROUP BY id) AS emp2
        ON =

The DISTINCT operand can be used to eliminate duplicate values within an A common function used to count the number of rows in the group if no Here is the same distinct value result without using SUM(Distinct());. 3. Remove Duplicates using group By The idea is to group according to all columns to be selected in output. For example, if we wish to print unique values of “FirstName, LastName and MobileNo”, we can simply group by all three of these. SELECT FirstName, LastName, MobileNo FROM CUSTOMER GROUP BY FirstName, LastName, MobileNo;

It seems like that should do the trick, since we only want to sum distinct shipping cost values, not all the duplicates. Let's give it a try: select o. You can set the groupby column to index then using sum with level df.set_index(['Fruit','Name']).sum(level=[0,1]) Out[175]: Number Fruit Name Apples Bob 16 Mike 9 Steve 10 Oranges Bob 67 Tom 15 Mike 57 Tony 1 Grapes Bob 35 Tom 87 Tony 15

How to use a TSQL windowing function with the COUNT function within a select statement so that we can use count in SQL without needing a group by clause. a row number returned after execution of a select statement by using a BY and then turn the select statement into an aggregate query which  In How to Use GROUP BY, we worked on a simple report request and covered the basics of GROUP BY and the issue of duplicate rows caused by JOINs. Today we'll finish up that report while examining SUM(Distinct), and see just how crucial derived tables are when summarizing data from multiple tables.

For this, use GROUP BY clause along with aggregate function SUM(). Let us first create a table −mysql> create table DemoTable( Name  To create a nested (or inner) group, select all detail rows above the related summary row, and click the Group button. For example, to create the Apples group within the East region, select rows 2 and 3, and hit Group. To make the Oranges group, select rows 5 through 7, and press the Group button again.