I was reading Dwain Camps’ article on Time Slots and thought it was a very interesting solution to a problem I’ve had a few times. Getting time slots inside of a period that I want to query. If you have a similar need, or want to learn more, I’d urge you to read the article.

It’s always easier to join to a set of data that matches what you need than to try and filter out other rows. SQL excels at joins, so whenever possible you want to join to data. As such, when I was looking at Dwain’s code, I thought the way he listed the tally table was very interesting. I’ve seen plenty of these generated, but I hadn’t run across someone spelling it out in comments. In case you are wondering, Dwain had code like this:

WITH Tally (n) AS
(
    SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) - 1                   -- zero-based
    -- Returns exactly 86400 rows (number of seconds in a day)
    FROM       (VALUES(0),(0),(0),(0),(0),(0))                         a(n) -- 6 rows 
    CROSS JOIN (VALUES(0),(0),(0),(0),(0),(0),(0),(0),(0),(0),(0),(0)) b(n) -- x12 rows
    CROSS JOIN (VALUES(0),(0),(0),(0),(0),(0),(0),(0),(0),(0),(0),(0)) c(n) -- x12 rows
    CROSS JOIN (VALUES(0),(0),(0),(0),(0),(0),(0),(0),(0),(0))         d(n) -- x10 rows
    CROSS JOIN (VALUES(0),(0),(0),(0),(0),(0),(0),(0),(0),(0))         e(n) -- x10 rows
),                                                                          -- = 86,400 rows

That’s a great visualization, and one I plan on using in the future. It makes it easy to see what’s being generated and at what scale.

For example, I can easily do this:

SELECT
        ROW_NUMBER() OVER ( ORDER BY ( SELECT
                                            NULL
                                     ) )
    FROM
        ( VALUES ( 0), ( 0) ) a ( n )                   -- 2 rows

which returns a single column table with the values 1 and 2 in it. Two rows.

Let’s say I want to now build a list of 12 rows. I could do this a few ways. One is to multiple 2 x 6 and get 12.

SELECT
   ROW_NUMBER() OVER (ORDER BY ( SELECT NULL))
 FROM
   ( VALUES (0), (0) ) a(n)         -- 2 rows
   CROSS JOIN 
   ( VALUES (0), (0), (0), (0), (0), (0) ) b(n);  -- x 6
;

Or I could give myself more flexibility to add and remove data with comments by doing factorials. How about 2 x 3 x 2 = 12?

SELECT
   ROW_NUMBER() OVER (ORDER BY ( SELECT NULL))
 FROM
   ( VALUES (0), (0) ) a(n)         -- 2 rows
   CROSS JOIN 
   ( VALUES (0), (0), (0) ) b(n)  -- x 3
   CROSS JOIN 
   ( VALUES (0), (0) ) c(n)  -- x 2
;

That gives me the same result: 12 rows. Of course, I can easily expand this quickly to thousands of rows.

The technique isn’t anything new, but the visualization is interesting, and to me, this is much easier technique to see and understand when you run into it in code. Right away I know I’m generating xx rows and I can easily see how to grow or shrink the number of I have the need.

Filed under: Blog Tagged: syndicated, T-SQL