Calculate a Running Total in SQL Server

While Sam Saffron did great work on it, he still didn't provide recursive common table expression code for this problem. And for us who working with SQL Server 2008 R2 and not Denali, it's still fastest way to get running total, it's about 10 times faster than cursor on my work computer for 100000 rows, and it's also inline query.
So, here it is (I'm supposing that there's an ord column in the table and it's sequential number without gaps, for fast processing there also should be unique constraint on this number):

;with 
CTE_RunningTotal
as
(
    select T.ord, T.total, T.total as running_total
    from #t as T
    where T.ord = 0
    union all
    select T.ord, T.total, T.total + C.running_total as running_total
    from CTE_RunningTotal as C
        inner join #t as T on T.ord = C.ord + 1
)
select C.ord, C.total, C.running_total
from CTE_RunningTotal as C
option (maxrecursion 0)

-- CPU 140, Reads 110014, Duration 132

sql fiddle demo

update I also was curious about this update with variable or quirky update. So usually it works ok, but how we can be sure that it works every time? well, here's a little trick (found it here - http://www.sqlservercentral.com/Forums/Topic802558-203-21.aspx#bm981258) - you just check current and previous ord and use 1/0 assignment in case they are different from what you expecting:

declare @total int, @ord int

select @total = 0, @ord = -1

update #t set
    @total = @total + total,
    @ord = case when ord <> @ord + 1 then 1/0 else ord end,
    ------------------------
    running_total = @total

select * from #t

-- CPU 0, Reads 58, Duration 139

From what I've seen if you have proper clustered index/primary key on your table (in our case it would be index by ord_id) update will proceed in a linear way all the time (never encountered divide by zero). That said, it's up to you to decide if you want to use it in production code :)

update 2 I'm linking this answer, cause it includes some useful info about unreliability of the quirky update - nvarchar concatenation / index / nvarchar(max) inexplicable behavior.

Update, if you are running SQL Server 2012 see: https://stackoverflow.com/a/10309947

The problem is that the SQL Server implementation of the Over clause is somewhat limited.

Oracle (and ANSI-SQL) allow you to do things like:

 SELECT somedate, somevalue,
  SUM(somevalue) OVER(ORDER BY somedate 
     ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) 
          AS RunningTotal
  FROM Table

SQL Server gives you no clean solution to this problem. My gut is telling me that this is one of those rare cases where a cursor is the fastest, though I will have to do some benchmarking on big results.

The update trick is handy but I feel its fairly fragile. It seems that if you are updating a full table then it will proceed in the order of the primary key. So if you set your date as a primary key ascending you will probably be safe. But you are relying on an undocumented SQL Server implementation detail (also if the query ends up being performed by two procs I wonder what will happen, see: MAXDOP):

Full working sample:

drop table #t 
create table #t ( ord int primary key, total int, running_total int)

insert #t(ord,total)  values (2,20)
-- notice the malicious re-ordering 
insert #t(ord,total) values (1,10)
insert #t(ord,total)  values (3,10)
insert #t(ord,total)  values (4,1)

declare @total int 
set @total = 0
update #t set running_total = @total, @total = @total + total 

select * from #t
order by ord 

ord         total       running_total
----------- ----------- -------------
1           10          10
2           20          30
3           10          40
4           1           41

You asked for a benchmark this is the lowdown.

The fastest SAFE way of doing this would be the Cursor, it is an order of magnitude faster than the correlated sub-query of cross-join.

The absolute fastest way is the UPDATE trick. My only concern with it is that I am not certain that under all circumstances the update will proceed in a linear way. There is nothing in the query that explicitly says so.

Bottom line, for production code I would go with the cursor.

Test data:

create table #t ( ord int primary key, total int, running_total int)

set nocount on 
declare @i int
set @i = 0 
begin tran
while @i < 10000
begin
   insert #t (ord, total) values (@i,  rand() * 100) 
    set @i = @i +1
end
commit

Test 1:

SELECT ord,total, 
    (SELECT SUM(total) 
        FROM #t b 
        WHERE b.ord <= a.ord) AS b 
FROM #t a

-- CPU 11731, Reads 154934, Duration 11135 

Test 2:

SELECT a.ord, a.total, SUM(b.total) AS RunningTotal 
FROM #t a CROSS JOIN #t b 
WHERE (b.ord <= a.ord) 
GROUP BY a.ord,a.total 
ORDER BY a.ord

-- CPU 16053, Reads 154935, Duration 4647

Test 3:

DECLARE @TotalTable table(ord int primary key, total int, running_total int)

DECLARE forward_cursor CURSOR FAST_FORWARD 
FOR 
SELECT ord, total
FROM #t 
ORDER BY ord


OPEN forward_cursor 

DECLARE @running_total int, 
    @ord int, 
    @total int
SET @running_total = 0

FETCH NEXT FROM forward_cursor INTO @ord, @total 
WHILE (@@FETCH_STATUS = 0)
BEGIN
     SET @running_total = @running_total + @total
     INSERT @TotalTable VALUES(@ord, @total, @running_total)
     FETCH NEXT FROM forward_cursor INTO @ord, @total 
END

CLOSE forward_cursor
DEALLOCATE forward_cursor

SELECT * FROM @TotalTable

-- CPU 359, Reads 30392, Duration 496

Test 4:

declare @total int 
set @total = 0
update #t set running_total = @total, @total = @total + total 

select * from #t

-- CPU 0, Reads 58, Duration 139

The APPLY operator in SQL 2005 and higher works for this:

select
    t.id ,
    t.somedate ,
    t.somevalue ,
    rt.runningTotal
from TestTable t
 cross apply (select sum(somevalue) as runningTotal
                from TestTable
                where somedate <= t.somedate
            ) as rt
order by t.somedate

In SQL Server 2012 you can use SUM() with the OVER() clause.

select id,
       somedate,
       somevalue,
       sum(somevalue) over(order by somedate rows unbounded preceding) as runningtotal
from TestTable

SQL Fiddle