Posts Tagged ‘sql server’

How to Calculate Running Totals, Subtotals and Grand Total Without a Cursor

By Gregory A. Larsen

If you have ever had the need to show detailed data of individual transactions and also keep a running total, subtotals, and grand total columns at the same time, but were not exactly sure how to tackle the problem then this article might help. In this article I will show you a few different techniques for calculating and summing information on multiple rows without using a cursor. The techniques I will show you will just use a basic SELECT statement. Of course, the calculations of the running total, subtotals and grand total will be done using other SQL clauses and functions like SUM and CASE.

Sample Data Used by Examples

Prior to showing you my examples, I will first need to establish a set of test data, which all my examples will use. My test data will consist of an “Orders” table with the following format:

create table Orders
(OrderID int identity,
 OrderAmt Decimal(8,2),
 OrderDate SmallDatetime)

I’ve populated this test Orders table with the following set of records:

OrderID     OrderAmt   OrderDate
----------- ---------- --------------------
1           10.50      2003-10-11 08:00:00
2           11.50      2003-10-11 10:00:00
3           1.25       2003-10-11 12:00:00
4           100.57     2003-10-12 09:00:00
5           19.99      2003-10-12 11:00:00
6           47.14      2003-10-13 10:00:00
7           10.08      2003-10-13 12:00:00
8           7.50       2003-10-13 19:00:00
9           9.50       2003-10-13 21:00:00

All my examples will be using this table to produce the running totals, sub totals, and grand total reports shown below. Basically this table contains a number of different orders that where created over time. Each order has an ID (OrderID) which uniquely identifies each record, an order amount (OrderAmt) that holds a decimal amount for the order, and a timestamp (OrderDate) that identifies when the order was placed.

Running Total On Each Record

This first example will display a simple method of calculating the running total of the OrderAmt. The calculated running total will be displayed along with each record in the Orders table. The “Running Total” column will be created with a simple SELECT statement and a correlated sub query. The correlated sub query is the part of the statement that does the heavy lifting to produce the running total.

select OrderId, OrderDate, O.OrderAmt
	,(select sum(OrderAmt) from Orders
                          where OrderID <= O.OrderID)
	  'Running Total'
from Orders O

When I run this query against my Orders table I get the following results:

OrderId     OrderDate            OrderAmt   Running Total
----------- -------------------- ---------- -------------
1           2003-10-11 08:00:00  10.50      10.50
2           2003-10-11 10:00:00  11.50      22.00
3           2003-10-11 12:00:00  1.25       23.25
4           2003-10-12 09:00:00  100.57     123.82
5           2003-10-12 11:00:00  19.99      143.81
6           2003-10-13 10:00:00  47.14      190.95
7           2003-10-13 12:00:00  10.08      201.03
8           2003-10-13 19:00:00  7.50       208.53
9           2003-10-13 21:00:00  9.50       218.03

As you can see, there is a “Running Total” column that displays the running total along with the other column information associated with each Orders table record. This running total column is calculated, by summing up the OrderAmt for all Orders where the OrderID is less than or equal to the OrderID of the current ID being displayed.

Running Total for Each OrderDate

This example is similar to the one above, but I will calculate a running total for each record, but only if the OrderDate for the records are on the same date. Once the OrderDate is for a different day, then a new running total will be started and accumulated for the new day. Here is the code to accomplish this:

select O.OrderId,
    convert(char(10),O.OrderDate,101) as 'Order Date',
    O.OrderAmt,
    (select sum(OrderAmt) from Orders
                          where OrderID <= O.OrderID and
                               convert(char(10),OrderDate,101)
                             = convert(char(10),O.OrderDate,101))
	                               'Running Total'
from Orders O
  order by OrderID

Here are the results returned from the query using my sample Orders Table:

OrderId     Order Date OrderAmt   Running Total
----------- ---------- ---------- ---------------
1           10/11/2003 10.50      10.50
2           10/11/2003 11.50      22.00
3           10/11/2003 1.25       23.25
4           10/12/2003 100.57     100.57
5           10/12/2003 19.99      120.56
6           10/13/2003 47.14      47.14
7           10/13/2003 10.08      57.22
8           10/13/2003 7.50       64.72
9           10/13/2003 9.50       74.22

Note that the “Running Total” starts out with a value of 10.50, and then becomes 22.00, and finally becomes 23.25 for OrderID 3, since all these records have the same OrderDate (10/11/2003). But when OrderID 4 is displayed the running total is reset, and the running total starts over again. This is because OrderID 4 has a different date for its OrderDate, then OrderID 1, 2, and 3. Calculating this running total for each unique date is once again accomplished by using a correlated sub query, although an extra WHERE condition is required, which identified that the OrderDate’s on different records need to be the same day. This WHERE condition is accomplished by using the CONVERT function to truncate the OrderDate into a MM/DD/YYYY format.

Running Totals With Subtotals and Grand totals

In this example, I will calculate a single sub totals for all Orders that were created on the same day and a Grand Total for all Orders. This will be done using a CASE clause in the SELECT statement. Here is my example.

select O.OrderID,convert(char(10),O.OrderDate,101) 'Order Date',O.OrderAmt,
       case when OrderID = (select top 1 OrderId from Orders
                           where convert(char(10),OrderDate,101)
                              = convert(char(10),O.OrderDate,101)
                          order by OrderID desc)
            then (select cast(sum(OrderAmt) as char(10))
                     from Orders
                     where OrderID <= O.OrderID
                        and convert(char(10),OrderDate,101)
                           = convert(char(10),O.OrderDate,101))
            else ' ' end as 'Sub Total',
       case when OrderID = (select top 1 OrderId from Orders
                           order by OrderDate desc)
            then (select cast(sum(OrderAmt) as char(10))
                      from Orders)
             else ' ' end as 'Grand Total'
from Orders O
  order by OrderID

Output from the SELECT statement looks like this:

OrderID     Order Date OrderAmt   Sub Total  Grand Total
----------- ---------- ---------- ---------- -----------
1           10/11/2003 10.50
2           10/11/2003 11.50
3           10/11/2003 1.25       23.25
4           10/12/2003 100.57
5           10/12/2003 19.99      120.56
6           10/13/2003 47.14
7           10/13/2003 10.08
8           10/13/2003 7.50
9           10/13/2003 9.50       74.22      218.03

In this example the first CASE statement controls the printing of the “Sub Total’ column. As you can see, the sub total is printed only on the last order of the day, which is determined by using a correlated sub query. The second CASE statement prints the “Grand Total”, which is only printed along with the very last order. Each of these CASE statements uses the TOP clause to determine which OrderID is the correct order for which to print out the “Grand Total”.

Conclusion

Hopefully these examples will help you understand different methods that can be used to calculate running totals, sub totals, and a grand total. As you can see you don’t need to use a cursor to calculate these different totals. With the creative use of correlated sub queries and other SELECT clauses like CASE you can easily create all these different totals. Next time you need to calculate totals consider using one of these non-cursor based solutions.

 

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