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Category: T-SQL

Not all Window Function Calls are Deterministic

Chen Hirsh reminds us of an important fact:

One of the scariest things that can happen when you develop SQL code is getting indeterminate results. When you run your query multiple times and each time gets a different value.

How can that happen?

SQL functions or queries can be categorized into two groups – deterministic vs. non-deterministic.

I even have a demo where I show off the non-deterministic nature of ROW_NUMBER() versus, say, RANK() or DENSE_RANK(). But there’s nothing too scary about it: just ensure that your PARTITION BY criteria are guaranteed to be unique and you’re good to go. H/T Madeira Data Solutions blog.

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Window Functions and Running Totals

Steve Jones makes a comparison:

Often I see running totals that are written in SQL using a variety of techniques. Many pieces of code were written in pre-2012 techniques, prior to window functions being introduced.

After SQL Server 2012, we had better ways to write a total. In this case, let’s see how much better. This is based on an article showing how you might convert code from the first query to the second. This is a performance analysis of the two techniques are different scales..

Steve shows a very fancy version of the self-join technique, which is actually even slower than using a cursor for this work. The fastest variant on the technique was something nicknamed the ‘quirky update’ technique, but it relied on an accidental property of how clustered indexes worked on temp tables in SQL Server and was not something Microsoft ever officially supported, meaning that any service pack, cumulative update, or hotfix might have broken your code and the best you’d get is an indifferent shrug.

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ISNULL vs COALESCE in SQL Server

Erik Darling has a video for us:

A Difference Between ISNULL And COALESCE You Might Care About In SQL Server

There’s nothing for me to snip as the graf. I don’t often link to videos without any sort of text accompaniment, but it’s been too long since I’ve linked to Erik and this was an interesting topic.

Bonus points for using “case expression” instead of the more common but technically incorrect “case statement.”

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Finding Basic Table Information via T-SQL

Andy Brownsword has a script for us:

In Management Studio we can view object details by hitting F7 in Object Explorer. It gives us basic metrics but I find it very slow to load for the details I typically need.

For that reason I though I’d share a script to turn to for metrics I commonly need. This query returns:

  • The table details (schema, name, created date)
  • The primary storage (Heap, Clustered, or Columnstore)
  • The numbmer of Nonclustered / Columnstore Indexes
  • The number of records and rough size for data / indexes

Click through for the script and an example of what it looks like.

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Thoughts on T-SQL Snapshot Backups

Anthony Nocentino has a two-parter for us. First is the idea of how T-SQL snapshot backups work:

Traditional SQL Server backups can struggle with large databases, resulting in longer backup times and resource contention. T-SQL Snapshot Backup, a new feature in SQL Server 2022, addresses these challenges by allowing storage-based snapshots to be coordinated through T-SQL. This feature delivers faster, more efficient backups, especially for large-scale environments with the most aggressive of recovery objectives.

The follow-up is for point-in-time recovery from a T-SQL snapshot backup:

In this post, the second in our series, I will guide you through using the new T-SQL Snapshot Backup feature in SQL Server 2022 to take a snapshot backup and perform point-in-time database restores using a snapshot backup as the base of the restore. We will explore how to manage storage-level operations, such as cloning snapshots and executing an instantaneous point-in-time restore of a database from the snapshot with minimal impact on your infrastructure. Additionally, I will demonstrate a PowerShell script that utilizes dbatools and the PureStoragePowerShellSDK2 modules to automate the process.

Check out both posts and be on the lookout for subsequent entries in the series.

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Understanding the EXISTS Keyword in SQL

Eric Blinn probably exists:

I’ve seen the EXISTS keyword in Microsoft SQL Server T-SQL code and don’t understand it well. What does it do? How do I use it? Are there best practices around SQL EXISTS?

This SQL tutorial will explain what the keyword EXISTS does and show several different use cases.

Read on to see how you can use EXISTS and its complement, NOT EXISTS, in a variety of use cases. One important part of why EXISTS can be useful compared to other ways of writing a particular query is that the performance profile of an EXISTS clause is a semi-join: we proceed until we find the first result matching our clause. If that happens to be in the first row, we can stop there as we’ve fulfilled the requirement. By contrast, an alternative using IN or something else like using SELECT COUNT(*) would likely need to read more pages of data than EXISTS.

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Eliminating Unexpected Whitespace or Null Characters in Columns

Kevin Wilkie has fun with an unexpected character:

The query ran just fine so I happily completed my work for the day. I sent it to my QA team and had them check it out before pushing it to Production. They sent it back with a note saying “We expect a lot more “Insert Garbage Data Here” to show.

Being a good data developer – or someone who just wants to show QA up (take your pick) – decided to dig deep into what FieldName really shows. I found a lot of the following:

In Kevin’s case, he tried to use TRIM() and it didn’t fix anything. That’s because TRIM(), by default, only removes the space character (up to the first non-space character), not all whitespace and not the null character CHAR(0) that Kevin found.

An alternative version of TRIM() that would have worked in this case, plus adding in tabstops as well, would be:

SELECT
    TRIM(' '+char(0)+char(9) FROM FieldName) AS TrimmedFieldName
FROM dbo.SomeTable;
GO

And you could also extend that to include newlines, line feeds, vertical tabs, the line separator character, and whatever else you need.

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Searching for Wildcard Characters in LIKE

Andy Brownsword is looking for a discount:

Performing a wildcard search by throwing a % into a LIKE expression is bread and butter. How do we handle this when we actually want to search for the wildcard though?

This was an issue I first saw early in my career before I was even building database solutions. The business had a back office solution where you could search through offers on the UI. Unfortunately it threw up some strange results.

Searching for ‘30%’ offers would return more than expected.

Read on for an example of the problem, as well as how you can resolve it.

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