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Category: Syntax

Trimming Strings with T-SQL

Andy Levy saves us all several characters at a time:

Every now and then, we encounter data that needs to be cleaned up because it’s got leading and/or trailing spaces. Or maybe you’re storing short data in a CHAR(N) field, so when you query it, you’re getting trailing spaces. For time immemorial, we’ve had to wrap these fields in rtrim(ltrim(fieldname)) to do the deed.

Effective with SQL Server 2017, that’s no longer the case. 

The eight keystrokes add up over time. In all seriousness, I am happy that TRIM() is a thing in SQL Server 2017. And Andy gives us a little bonus to make it worth your refactoring while.

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Supporting Multiple NULL Values with a Unique Constraint

Itzik Ben-Gan walks us through a workaround in T-SQL:

Suppose that you have a database in a platform that supports the standard unique constraint and you need to migrate that database to SQL Server. You may face issues with the enforcement of unique constraints in SQL Server if the unique columns support NULLs. Data that was considered valid in the source system may be considered invalid in SQL Server. In the following sections I’ll explore a number of possible workarounds in SQL Server.

I use a simplified version of this as an interview question, so it’s nice to see an entire article from Itzik on the topic, including a couple solutions way outside the box.

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From IDENTITY to Sequences

Andy Levy recommends checking out sequences:

The SEQUENCE object eliminates all of this. It gives you a simple way to just grab a new number and increment for the next caller. It’s very fast as there’s no visible table I/O, and it’s unaffected by rollbacks.

And it’s so much easier to use! You just ask for the next number in the sequence!

I like sequences, though the interesting thing is that 2020 me has created them a lot less frequently than 2012 me was sure I would. I’m glad they’re in the product, however.

One thing I should point out is that sequences are like identity columns in that you can have gaps due to user behavior, such as rolling back transactions. If you absolutely need gap-free sets of numbers, you’re back to Andy’s Method One, except everything has to be serializable and wrapped in explicit transactions.

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DISTINCT is not a Function

Lukas Eder corrects a misconception:

A very common misconception I often encounter with SQL users is the idea that DISTINCT is something like a function, and that it can take parenthesised arguments. Just recently, I’ve seen this Stack Overflow question where the OP was looking for a way to express this in jOOQ:

SELECT DISTINCT (, emp.fname, FROM employee emp;

Notice the parentheses around (, which look as though this is some special kind of DISTINCT usage, which is akin to a DISTINCT function. The idea is often that:

– The behaviour is somewhat different from omitting the parentheses
– The performance is faster, because only the ID needs to be considered for distinctness

Both of these ideas are (mostly) wrong, as Lukas shows.

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LAST_VALUE() and Windows

Jeet Kainth explains the importance of specifying your window when using LAST_VALUE():

To return the actual last value, add the additional clause ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING. This ensures that for each row the LAST_VALUE() function looks at all rows; from the very first row to the very last row.

Click through for the example. Remember that the default is going to the current row, not the entire data set.

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Describing the First Result Set

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.

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String Aggregation with T-SQL

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.

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NULL Handling Features not in T-SQL

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.

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T-SQL Checker ADS Extension

Daniel Janik has a new Azure Data Studio extension for us:

I’ve created a sample ads extension that checks TSQL syntax in real-time for potential bad practice.

Right now the extension is using regex, which isn’t the best for parsing SQL but it works for the few test cases I’ve added.

I’m hoping that the community can help evolve the project into something really cool; so, I’m asking for your help in making that happen.

Click through for a demo, and check out the GitHub repo.

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