Category: Syntax

Phil Factor dives into sys.dm_exec_describe_first_result_set_for_object():

I’ve been working on a project unkindly nicknamed ‘The Gloop’ because the code is a bit amorphous. Basically, it is an approach to documenting SQL Server databases, using the facilities provided such as the metadata views and DMFs. Although it is relatively simple to record the result returned by a table-valued function I’d rather neglected the stored procedures because there was no metadata that could produce the first result set produced by a procedure or trigger.

I’d been silly because there is, of course, an Execution system DMF that does it: sys.dm_exec_describe_first_result_set_for_object(). it takes as its parameter the object_id of a procedure or trigger and describes the first result metadata for the module with that ID. It has the same result set definition as sys.dm_exec_describe_first_result_set.

I’m going to have to try this out, but I have problems with sp_describe_first_result_set and how it blows up if you use a temp table in the stored procedure whose result set you’re grabbing.

Andy Levy talks about one of my favorite functions in SQL Server 2017:

This is another in a group of several posts on modernizing T-SQL code with new features and functionality available in SQL Server.

SQL Server 2016 gave us the STRING_SPLIT() function, but what about the reverse – compiling a set of values into one delimited string? We only had to wait 15 months for the release of SQL Server 2017, and the STRING_AGG() function.

I had the STUFF() / FOR XML PATH trick memorized for quite some time, but that was always a solution which felt like it worked on accident. Even if the new solution weren’t faster than the old, I’d still use it.

Itzik Ben-Gan continues a series complexity around NULL:

When using the offset window functions LAG, LEAD, FIRST_VALUE and LAST_VALUE, sometimes you need to control the NULL treatment behavior. By default, these functions return the result of the requested expression in the requested position, irrespective of whether the result of the expression is an actual value or a NULL. However, sometimes you want to continue moving in the relevant direction, (backward for LAG and LAST_VALUE, forward for LEAD and FIRST_VALUE), and return the first non-NULL value if present, and NULL otherwise. The standard gives you control over this behavior using a NULL treatment clause with the following syntax:

offset_function(<expression>) IGNORE_NULLS | RESPECT NULLS OVER(<window specification>)

There are three good examples of functionality around handling NULL which the current implementation of T-SQL is missing.

Andy Levy recommends using STRING_SPLIT():

Last year, you finally retired the last of your SQL Server 2008R2 instances. Congratulations! But are you taking advantage of everything that your new instances have to offer? Unless you did a review of all of the T-SQL in your applications, I’m guessing not.

At one time or another, we all find ourselves having to do some string parsing, especially splitting strings on a delimiter. Nearly all of us have one (or two or a dozen) functions for doing this somewhere on every instance of SQL Server. But since SQL Server 2016, we’ve had an official way to do it – the STRING_SPLIT() function.

Andy’s example involves splitting strings, but there are plenty of functions which come into the T-SQL lexicon. It might be worth doing a quick review of the available system functions just to see if there’s something useful which slipped with a newer version of SQL Server.

Ed Pollack continues a series on gap and island analysis:

Gaps and islands analysis supplies a mechanism to group data organically in ways that a standard GROUP BY cannot provide. Once we know how to perform an analysis and group data into islands, we can extend this into the realm of real data.

For all code examples in this article, we will use a set of baseball data that I’ve created and maintained over the years. This data is ideal for analytics as it is large and contains data quality that varies between very accurate and very sloppy. As a result, we are forced to consider data quality in our work, as well as scrutinize boundary conditions for correctness. This data will be used without much introduction as we will only reference two tables, and each is relatively straightforward.

The code in this article gets a bit complex, but Ed shows off some powerful techniques.

Dan Guzman takes us through different SET options in T-SQL and where you can go wrong:

ANSI_PADDING OFF has also been deprecated for quite some time and the SQL Server documentation specifically calls out “ANSI_PADDING should always be set to on.” In summary, a column-level ANSI_PADDING OFF setting causes nullable fixed-length char(n) and binary(n) columns to behave like variable-length varchar(n) and varbinary(n) columns. Furthermore, SQL Server automatically trims trailing blank characters from character data and leading binary zeros from binary data and stores the values as variable length instead of storing the provided value as-is during inserts and updates. Varchar(n)/varbinary(n) columns with ANSI_PADDING OFF are similarly trimmed. Note that it is the persisted ANSI_NULLS column meta-data setting that determines the storage and trimming behavior, not the current session ANSI_PADDING setting. The session ANSI_PADDING must still be ON when using features that require proper settings.

Some of these will pop up in occasional errors, like if you’re using filtered indexes or indexed views.