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Category: T-SQL

Approximate Percentiles in Azure SQL DB and MI

Published 2023-03-02 by Kevin Feasel

Balmukund Lakhani announces a feature has gone generally available:

Today, we are announcing General Availability (GA) of native implementation of APPROX_PERCENTILE in Azure SQL Database and Azure SQL Managed Instance. We announced preview of these functions in October 2022. Since then, many customers have adopted these for the applications where response time of percentile calculation was more important than the accuracy of the result.

I have and will continue to extol the virtues of these two functions wherever I go. They’re considerably better than the originals once you start getting into the hundreds of thousands or millions of rows. They’re also available in SQL Server 2022.

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Fun with Implicit Conversions to DateTime

Published 2023-03-01 by Kevin Feasel

Andrea Allred gets tested:

I have been teaching a T-SQL 101 class and for the homework, we asked the students to get all the records where our heroes had a birthdate between 1995 through 1999. I expected something like this:

[…]

Imagine my surprise when one of the students turned in this:

SELECT FirstName, LastName, Birthdate
FROM Heroes
WHERE Birthdate BETWEEN '1995' AND '1999'

When I first saw the query I thought, “There is no way they ran that and it worked.” So I wrote it up and ran it on my data. Guess what? IT RUNS AND RETURNS DATA! I was shocked.

Click through to see what it returns and how that’s not quite right.

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Speeding Up Queries via IF EXISTS

Published 2023-03-01 by Kevin Feasel

Chad Callihan doesn’t need to wait for the query’s end credits sequence:

When checking for the existence of a value or values in a table, typically, the whole table does not need to be read. The goal is to obtain more of a true or false answer, whether a criteria is met or not. If the criteria is met with the first few records then there’s no need to read on. Nonetheless, you may come across scripts written to unnecessarily retrieve the complete count of a value in a table. Let’s compare the performance difference between using COUNT(*) and using “IF EXISTS” when checking a table for values.

One’s going to give you a full scan and the other will give you a semi-join. Read on to see what the practical effect of this is.

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Performing a Detailed Code Review of a Stored Procedure

Published 2023-02-27 by Kevin Feasel

Aaron Bertrand has 99 problems and this stored procedure is 40 of them:

I’ve been at this for a while now, and have a very particular set of rules and coding conventions that I follow when writing and, more importantly, reviewing T-SQL code. I often perform code reviews and thought it would be fun to frame this exercise: a completely fictitious stored procedure hits my desk, I’ll reject it of course, and enumerate the reasons why. The procedure might pass review in a lot of shops, but not in mine.

Click through and give it a try. Aaron has outdone himself with this and I got angry with him about 2/3 of the way through the procedure. That’s how you know it’s a good example.

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ORDER BY Clause in Subqueries and SSMS Warnings

Published 2023-02-20 by Kevin Feasel

Ronen Ariely explains a warning message:

Warning: The ORDER BY clause is used only to determine the rows that are returned by the TOP clause in the view definition. The ORDER BY clause does not guarantee ordered results when the view is queried, unless ORDER BY is also specified in the query itself. Click CANCEL to discard your modifications. Click OK to save the view.

Read on for the full context of when you might see this warning message in SQL Server Management Studio.

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The Power of Date Truncation

Published 2023-02-14 by Kevin Feasel

Magda Bronowska rounds to the nearest minute:

From MS Learn:

DATETRUNC() function returns an input date truncated to a specified datepart.

On the surface the work similarly to DATEPART(), however that function returns integer values, opposed to the dates returned by DATETRUNC() (we will see that better in the example below).

Read on for plenty of examples of this, as well as two more syntax updates in SQL Server 2022.

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The Benefit of IS DISTINCT FROM

Published 2023-02-14 by Kevin Feasel

Rob Farley enjoys the syntax:

This month, Deepthi Goguri (@dbanuggets) asks us about our favourite new feature in SQL Server 2022 or Azure. And while there are always a few, I’m going to write about why I have a particular fondness of “IS [NOT] DISTINCT FROM“, despite the fact that it’s overly wordy and the functionality isn’t actually new at all.

People understand my point that it’s a little wordy. Typing “IS NOT DISTINCT FROM” instead of “=” doesn’t sound fun to anyone, and I think “==” or “IS” ought to be fine. The fact that the functionality isn’t new… well that statement seems to raise a few eyebrows.

Read on for Rob’s take on what IS DISTINCT FROM (and its negative cousin) actually do and what performance-killing alternative people used prior to that.

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Error Handling with OPENROWSET

Published 2023-02-14 by Kevin Feasel

Deborah Melkin handles missing servers with aplomb:

OPENROWSET is a functionality that allows you to access data sources outside your current server. This could be reading from an Excel file or calling another SQL Server instance. You’re able to treat that other data source as record set, or derived table, and work with the rows returned as you would a local table. One reason you may want to do this is that you need to use a stored procedures to query data from other servers and bring the data together, effectively creating an ELT (Extract – Load – Transform) process without having to use SSIS or Azure Data Factory (ADF).

Read on to see how OPENROWSET() works, what happens if you try to access a remote server which doesn’t exist (or times out), and how you can capture that error message in a CATCH block—something that is not possible to do by default.

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Antipattern Queries Extended Event in SQL Server

Published 2023-02-06 by Kevin Feasel

Bob Ward enumerates some anti-patterns SQL Server can guilt you over:

If a query uses certain antipatterns, it will be detected during query optimization.  For both SQL Server and Azure SQL (internally on by default), if these antipatterns are detected when optimizing the query, and the query_antipattern event has been added as part of a running extended event session, the output will be captured.  The output will contain the relevant capture fields configured for the extended event session, allowing one to quickly identify which queries contain these antipatterns and are, therefore, prime candidates for tuning.

Read on for more information about this extended event, which is new to SQL Server 2022. I haven’t used this yet, so the two caveats I’m about to give are speculative in nature…though when has that ever stopped me? Caveat the first: just because something shows up as an anti-pattern doesn’t mean it needs to be fixed. There can be good reasons why you have chosen what is normally a less-efficient path. Caveat the second: just because something doesn’t show up as an anti-pattern doesn’t mean it’s fine. These are likely directional and my guess is that SQL Server will be fairly conservative in its estimation of what constitutes an anti-pattern so that you don’t get a lot of false positives.

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Sessions and Execution of Dynamic SQL

Published 2023-02-01 by Kevin Feasel

Deborah Melkin riddles us this on dynamic SQL:

I admit it – I do waaayyyy too much with dynamic SQL. But I just keep running into situations that require it. That being said, I ran into an interesting problem that had me puzzled. I found a bunch of different blog posts that pointed to me to the right direction but required a little extra work to find the solution.

There are several concepts that are at play here, so I’ll try to break this out so we can put the pieces together. The first once is centered around dynamic SQL. There are two parts of this I want to make sure we understand first – how it fits into sessions and how it gets executed.

Read the whole thing.

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