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Curated SQL Posts

Antipattern: DAX Measures Never Returning Blank

Published 2024-07-08 by Kevin Feasel

Chris Webb explains the value of BLANK:

Following on from my earlier post on the Query Memory Limit in Power BI, and as companion to last week’s post on how a DAX antipattern using Calculate() and Filter() can lead to excessive memory consumption by queries (and therefore lead to you hitting the Query Memory Limit), in this post I want to look at the effects of another DAX antipattern on performance and memory usage: measures that can never return a blank value.

Read on to see how much of a difference using DAX to fill a grid with 0’s can make.

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Limiting Jobs to the Primary Replica of an AG

Published 2024-07-08 by Kevin Feasel

Chad Callihan doesn’t want jobs running willy-nilly:

Transitioning from a failover cluster configuration to an Availability Group configuration brings with it all kinds of “fun” challenges. One such challenge that you may not have considered is the handling of jobs on whatever server is Primary, along with secondary servers. Let’s briefly discuss a potential challenge and an option to address it.

Click through for the example and a solution. Eitan Blumin has another solution in the comments, so check that one as well.

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Modifying Column Return Order in sp_QuickieStore

Published 2024-07-05 by Kevin Feasel

Josephine Bush demands order:

I love QuickieStore, but I wanted some columns to be at the front end of the results returned. Namely, I wanted top_waits, query_sql_text, and query_plan right after database name. This way I don’t have to scroll over to see those values.

Unfortunately, it would appear that there’s no advanced functionality for column ordering like we have for sp_whoisactive. But that didn’t deter Josephine, and you can grab a copy of an updated script that includes columns in this different arrangement.

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Dealing with Query Store in Error State

Published 2024-07-05 by Kevin Feasel

David Fowler turns it off then back on again, like a true IT professional:

I recently received a complaint that Query Store for a particular database was turned off, which was strange as that particular database has seen quite a few performance issues and I know that I’d ensured Query Store was enabled in the past.

No problem, I flicked the switch and Query Store was enabled again.

Half an hour or so later and I’m being told that Query Store is again disabled. What’s going on?

Read on to learn what to do if you get stuck with this problem.

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Real-Time Intelligence in Microsoft Fabric

Published 2024-07-05 by Kevin Feasel

Dennes Torres takes a peek at a service with a new name:

When everyone starts to announce Real-Time Intelligence in Microsoft Fabric as something new, I need to double check what’s happening: Am I crazy or is everyone else? Wasn’t this already there?

Finally, I realize that Real-Time Intelligence is a new name for Real-Time Analytics, and they are doing this so fast we don’t even have time to notice the difference.

What’s Real-Time Intelligence and what’s the difference from Real-Time Analytics?

Read on for those answers.

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Performance Testing Microsoft Fabric Dataflow Gen2

Published 2024-07-05 by Kevin Feasel

Reitse Eskens hammers away:

In my previous blogs, I’ve been hammering Fabric with data from some different angles. Either with the Copy dataflows, notebooks, Pipelines, Data Warehouse SQL scripts or in PowerBI.
This time, I’m going to make the dataflow Gen2 work for it’s money.

Reitse tries the normal mechanism for Dataflows Gen2, but then also tries out a preview feature for fast copy and sees a marked difference.

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RIP Stretch DB

Published 2024-07-05 by Kevin Feasel

Debbi Lyons calls it:

Ever since Microsoft introduced SQL Server Stretch Database in 2016, our guiding principles for such hybrid data storage solutions have always been affordability, security, and native Azure integration. Customers have indicated that they want to reduce maintenance and storage costs for on-premises data, with options to scale up or down as needed, greater peace of mind from advanced security features such as Always Encrypted and row-level security, and they seek to unlock value from warm and cold data stretched to the cloud using Microsoft Azure analytics services.     

During recent years, Azure has undergone significant evolution, marked by groundbreaking innovations like Microsoft Fabric and Azure Data Lake Storage. As we continue this journey, it remains imperative to keep evolving our approach on hybrid data storage, ensuring optimal empowerment for our SQL Server customers in leveraging the best from Azure.

This is not surprising at all, considering that the premise of Stretch DB was that you could off-load old and less-important data from your local SQL Server instances and expensive local disk into Azure, querying it when you need that data. The problem was, you couldn’t use cheap storage and pay a few cents per gigabyte of data per month. Instead, you were effectively spinning up Azure Synapse Analytics and paying a marked premium for your least important data. The price alone made this an untenable idea, but there were other holes in the plan as well that doomed it as a product.

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DAX Variables and Iterators

Published 2024-07-05 by Kevin Feasel

Nikola Ilic takes us through two major concepts in DAX:

“DAX is simple, but not easy!” – famously said Alberto Ferrari, when asked which best describes Data Analysis Expression language. And, that’s probably the most precise definition of the DAX. It may look very easy at first glance, but understanding nuances and how DAX really works, requires a lot of time and “try and fail” cases.

Obviously, this article is not a deep-dive into DAX internals and will not go into these nuances, but it will (hopefully) help you to get a better understanding of the few very important concepts that will make your DAX journey more pleasant and assist you in preparing the DP-600 exam.

Click through for Nikola’s explanation of each.

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Tips for Choosing a Classifier

Published 2024-07-03 by Kevin Feasel

I’ve wrapped up yet another series:

In this video, I wrap up the series on classification and provide some quick-and-dirty tips on when to use each of the classification algorithms we have discussed.

This was a series I really enjoyed. I’ve had a talk on the topic for a few years, but getting the opportunity to dig in deeper and spend a few hours on the topic was nice. It also helped me fill in some gaps in my understanding and fix a few long-standing bugs in my demo code, so it’s got that going for it as well.

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Parallel Download in Oracle Object Storage

Published 2024-07-03 by Kevin Feasel

Brendan Tierney continues a series on Oracle Object Storage:

In previous posts, I’ve given example Python code (and functions) for processing files into and out of OCI Object and Bucket Storage. One of these previous posts includes code and a demonstration of uploading files to an OCI Bucket using the multiprocessing package in Python.

Building upon these previous examples, the code below will download a Bucket using parallel processing. Like my last example, this code is based on the example code I gave in an earlier post on functions within a Jupyter Notebook.

Click through for the code.

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