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Category: Syntax

Approximate Count Distinct

Published 2021-03-09 by Kevin Feasel

Deepthi Goguri looks at the APPROX_COUNT_DISTINCT() function in SQL Server 2019:

In the previous post, we learned about Scalar UDF Inliningfeature. In this post, let’s focus on the Approximate QP with Approx_Count_Distinct feature introduced as a part of SQL Server 2019 Intelligent Query Processing features. This feature is useful to get the approximate count of distinct values just like the  Count distinct function to get the distinct number of records but this new feature will take less amount of CPU and memory to process the query.

Click through for more info. The algorithm itself is also pretty interesting.

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Deprecated Features to Ignore

Published 2021-02-23 by Kevin Feasel

Aaron Bertrand begins a series:

The issue in this specific case is that they spent that time contemplating a decision based on incomplete information. Are those I/Os reads or writes? If the user has an open transaction and has merely read a lot of data, there is far less impact in rolling that transaction back than if they have changed a lot of data. So, instead of sys.sysprocesses, let’s see what the more modern DMV, sys.dm_exec_sessions, can show us about this session:

On a slightly different topic, Mala Mahadevan looks at old but not-deprecated features, some of which you shouldn’t use:

I am part of a weekly talk show we run at the TriPASS user group, called ‘Shop Talk’. Shop Talk was the brainchild of Kevin Feasel, our key user group lead..we meet on a bi weekly basis and discuss random tech topics related to sql server. Some of these are questions from our audience, and some are just ideas for discussion that one of us come up with. I am constantly amazed and grateful for how much I learn by being part of this show – from my co hosts and from the very intelligent audience we are blessed with. Last week, we discussed Brent Ozar’s blog post on ‘What SQL Server Feature Do You Wish Would Go Away?’. The recording of our discussion (this topic starts around 26:00) is here.

And if you want a quick synopsis of the last link, I have the notes from each episode of Shop Talk, including the one Mala references.

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DEFINE TABLE in DAX Queries

Published 2021-02-03 by Kevin Feasel

Marco Russo and Alberto Ferrari takes us through the DEFINE TABLE statement in DAX:

Introduced in December 2020, the DEFINE TABLE statement lets you define a calculated table local to a query. The table is not persisted in the model, it exists only for the lifetime of the query. Apart from that, it is a calculated table in every sense of the term albeit with some limitations.

The extension of DAX with the capability to define calculated tables local to a query is needed in order to support composite models (DirectQuery for Power BI datasets and Azure Analysis Services). There are no limitations on the use of the feature, so you can take advantage of local tables in any DAX query. We refer to calculated tables defined in a query as query calculated tables, or query tables for short.

Click through for an example of how it works.

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The Pain of SELECT *

Published 2021-01-26 by Kevin Feasel

Grant Fritchey strongly recommends against SELECT *:

Quite a few years ago, I wrote a post about SELECT * and performance. That post had a bit of a click-bait title (freely admitted). I wrote the post because there was a really bad checklist of performance tips making the rounds (pretty sure it’s still making the rounds). The checklist recommended a whole bunch of silly stuff. One silly thing it recommended was to simply substitute ALL columns (let me emphasize that again, name each and every column) instead of SELECT * because “it was faster”.

My post, linked above, showed that this statement was nonsense. Let’s be clear, I’m not a fan of SELECT *. Yes, it has some legitimate functionality. However, by and large, using SELECT * causes performance problems.

I’ll use SELECT * for one-off queries (well, something like SELECT TOP(100) * but same difference), but it’s a really bad practice to include that in application code for the reasons Grant mentions.

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Using AT TIME ZONE

Published 2021-01-22 by Kevin Feasel

Chad Callihan walks us through using AT TIME ZONE in SQL Server:

Dealing with time zones in general can be a headache. Thankfully, SQL Server 2016 included a new clause to make working with time zones more manageable. Let’s look at a couple examples:

I’m in Eastern Standard Time so we’ll start here. Keep in mind that when no offset information is included, SQL Server is going to assume that the date value is in the target time zone.

This works best when your dates are stored in UTC, but Chad does show how to convert between two other time zones. This does not perform all that well when you need to convert a lot of rows, but if you’re doing one or two conversions, it’ll do just fine.

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The Concatenation Operator

Published 2021-01-19 by Kevin Feasel

Hugo Kornelis explains what the Concatenation operator does:

The Concatenation operator reads and returns all rows from all its inputs, in order, and without modification.

This operator is most commonly used to execute queries that use UNION or UNION ALL. In the former case, other operators are required to remove the duplicates, because Concatenation doesn’t provide that functionality. You may also find the Concatenation operator in queries on partitioned views.

Read on to see the algorithm and lots of details about the operator.

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Using sp_prepare with Plan Guides

Published 2021-01-13 by Kevin Feasel

Aaron Bertrand tries something different:

There are features many of us shy away from, like cursors, triggers, and dynamic SQL. There is no question they each have their use cases, but when we see a trigger with a cursor inside dynamic SQL, it can make us cringe (triple whammy).

Plan guides and sp_prepare are in a similar boat: if you saw me using one of them, you’d raise an eyebrow; if you saw me using them together, you’d probably check my temperature. But, as with cursors, triggers, and dynamic SQL, they have their use cases. And I recently came across a scenario where using them together was beneficial.

Read on to see the method to this madness.

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String Modification in T-SQL

Published 2021-01-08 by Kevin Feasel

Steve Jones answers a question:

Recently I ran across a question posted by a beginner on the Internet and thought this would be a good, basic topic to cover. The question was: how can I replace a value in a comma separated string in a table?

This post covers the basics of this task.

Incidentally, this is where I say hey, that sounds like a failure in normalization. If you need to care about individual values in a collection, your value is not atomic. But that’s a bit of a tangent.

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