Category: Syntax

Daniel Hutmacher explains some of what you can do with the VALUES clause:

Note the commas at the end of each line, denoting that a new row begins here. Because this runs as a single statement, the INSERT runs as an atomic operation, meaning that all rows are inserted, or none at all (like if there’s a syntax issue or a constraint violation).

I use this construct all the time to generate scripts to import data from various external sources, like Excel, or even a result set in Management Studio or Azure Data Studio.

Daniel also has a new app for us to try out.

Jess Pomfret takes us through the STRING_AGG() function:

I’m a SQL Server Database Engineer by day, but I must say my blog has a lot more PowerShell and automation posts than T-SQL.  However, last week I found a really great T-SQL aggregate function that I had no idea existed, so I thought I’d share it with you.

It’s a good function.

Greg Dodd digs into the ROLLUP and CUBE operators in a two-parter. First, ROLLUP:

As you can see, we now have these null’s popping up, but with totals. Row 5 for example, tells us that in 2017 there were 1,427,461 people living in Hawaii. Row 11 tells us that there are 2,438,188 people living in Rhode Island and Hawaii in 2017. Row 22 tells us that there were 2,429,070 people living in Rhode Island and Hawaii in 2018, and finally row 23 tells us that in total there have been 4,867,268 people in 2017 and 2018. This last row is a bit useless for this data as the overlap of those people would be huge, but for something like sales data, this number could be useful.

Next, CUBE:

For those with a keen eye you’ll see that I’ve started at row 28 in that screenshot. When we run the GROUP BY without ROLLUP or CUBE we get just 16 rows. With ROLLUP that grows to 23, but with CUBE it explodes out to 57. Why?

I’ve used ROLLUP several times with proper hierarchical data (e.g., product category, product sub-category, product) and it does an excellent job of summarizing that sort of data. CUBE has always returned too many rows for my liking. But the operator I go to most frequently is GROUPING SETS, as then I get to control the levels.

Itzik Ben-Gan continues a series on table expressions:

The term derived table is used in SQL and T-SQL with more than one meaning. So first I want to make it clear which one I’m referring to in this article. I’m referring to a specific language construct that you define typically, but not only, in the FROM clause of an outer query. I’ll provide the syntax for this construct shortly.

The more general use of the term derived table in SQL is the counterpart to a derived relation from relational theory. A derived relation is a result relation that is derived from one or more input base relations, by applying relational operators from relational algebra like projection, intersection and others to those base relations. Similarly, in the general sense, a derived table in SQL is a result table that is derived from one or more base tables, by evaluating expressions against those input base tables.

There’s a lot to digest in this post, so check it out.

Denis Gobo points out that there is a second option when using WAITFOR:

I was looking at some code I wrote the other day and noticed the WAITFOR command.. This got me thinking. How many times have I used WAITFOR in code, probably as much as I have used NTILE  🙂

I looked at the documentation for WAITFOR and notice there is TIME in addition to DELAY.  Oh that is handy, I always rolled my own ghetto-style version by calculating how long it would be until a specific time and then I would use that in the WAITFOR DELAY command

Read on to see why you might use WAITFOR and how to use each option. I use it a bit more frequently than Denis, though I still need to run a test each time to get the syntax right…