


What's the Most Efficient Way to Calculate Running Totals in SQL Server?
Detailed explanation of SQL Server cumulative sum calculation method
Calculating cumulative sums in SQL queries is a common requirement. The OVER
clause provides a convenient way to perform such calculations in Oracle and ANSI-SQL. However, SQL Server's implementation of the OVER
clause lacks the flexibility to handle certain use cases.
Update Tips
Despite its disadvantages, an effective technique for calculating cumulative sums in SQL Server is to use an aggregate set statement. This method includes:
- Create a temporary table with the same columns as the original table.
- Insert the data from the original table into the temporary table while setting the cumulative sum column to NULL.
- Update temporary table to calculate cumulative sum based on previous values.
This technique is very efficient, but has potential problems:
-
The order in which the
-
UPDATE
statement processes rows may not always be the same as the date order. - The update trick relies on undocumented implementation details of SQL Server.
Benchmark comparison
Benchmark testing shows that, within the constraints of SQL Server, the cursor method is the fastest and safest way to calculate a cumulative sum. The update trick provides the highest performance, but has potential issues with processing order. Therefore, for production code, it is recommended to use a cursor-based approach.
Example code and benchmark data
The following code provides a working example along with test data for benchmarking:
Test data settings:
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 INTO #t (ord, total) VALUES (@i, ABS(CHECKSUM(NEWID()) % 1000)); SET @i = @i + 1; END; COMMIT TRAN;
Test method:
Test 1: Correlated subquery
SELECT ord, total, (SELECT SUM(total) FROM #t b WHERE b.ord <= a.ord) AS RunningTotal FROM #t a ORDER BY a.ord;
Test 2: Cross-connection
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;
Test 3: Cursor
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;
Test 4: Update Tips
DECLARE @total INT; SET @total = 0; UPDATE #t SET running_total = @total, @total = @total + total; SELECT * FROM #t;
By comparing the execution efficiency of the above four methods, the best practice for calculating cumulative sums in SQL Server can be derived. Note that actual performance may vary depending on data volume and server configuration.
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