Question

Imagine the following table (called TestTable):

id     somedate    somevalue
--     --------    ---------
45     01/Jan/09   3
23     08/Jan/09   5
12     02/Feb/09   0
77     14/Feb/09   7
39     20/Feb/09   34
33     02/Mar/09   6

I would like a query that returns a running total in date order, like:

id     somedate    somevalue  runningtotal
--     --------    ---------  ------------
45     01/Jan/09   3          3
23     08/Jan/09   5          8
12     02/Feb/09   0          8
77     14/Feb/09   7          15  
39     20/Feb/09   34         49
33     02/Mar/09   6          55

I know there are various ways of doing this in SQL Server 2000 / 2005 / 2008.

I am particularly interested in this sort of method that uses the aggregating-set-statement trick:

INSERT INTO @AnotherTbl(id, somedate, somevalue, runningtotal) 
   SELECT id, somedate, somevalue, null
   FROM TestTable
   ORDER BY somedate

DECLARE @RunningTotal int
SET @RunningTotal = 0

UPDATE @AnotherTbl
SET @RunningTotal = runningtotal = @RunningTotal + somevalue
FROM @AnotherTbl

… this is very efficient but I have heard there are issues around this because you can’t necessarily guarantee that the UPDATE statement will process the rows in the correct order. Maybe we can get some definitive answers about that issue.

But maybe there are other ways that people can suggest?

edit: Now with a SqlFiddle with the setup and the ‘update trick’ example above

Answer 1

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