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Day: October 22, 2020

More Fun with NULL

Chris Johnson troubleshoots an issue in code:

The poster had a CASE statement and was wondering why it didn’t work as expected. Essentially they were doing something like:


And they wanted to know why both were returning 0 when @a or @b were set to NULL. The issue here is that any normal predicate involving NULL returns an unknown. They had tried to compensate with the OR, which got them the result they wanted in the first statement, but didn’t understand why it did that.

Click through for the explanation.

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Azure Elastic Queries, Jobs, and Transactions

Steve Hughes walks us through three Elastic concepts in Azure:

Elastic queries allow developers to interact with data from multiple databases supported on the Azure SQL database platform including Synapse. Elastic queries are often referred to as Polybase which is currently implemented in SQL Server 2019 and Azure Synapse. The key difference is that elastic queries only allow you to interact with other Azure SQL Databases but not Hadoop or other database implementations (e.g. Teradata or Oracle). Part of the confusion comes from the fact that the implementation looks very similar. Both toolsets use external tables in SQL Server to interact with the connected data sources. However, Polybase requires additional components to run whereas elastic queries are ready to go without additional setup.

Read on for more information, including demos.

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Mapping New Column Names with Power Query

Soheil Bakhshi reminds me of DB/2:

So, here is my scenario. I received about 10 files, including 15 tables. Some tables are quite small, so I didn’t bother. But some of them are really wide like having between 150 to 208 columns. Nice!

Looking at the column names, they cannot be more difficult to read than they are, and I have multiple tables like that. So I have to rename those columns to something more readable, more on this side of the story later.

Fortunately, there’s a way to fix this; click through for that way.

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Tips for Using Azure Table Storage

Adrian Hills takes us through using Azure Table Storage:

Azure Table Storage is a NoSQL key-value PaaS data store that can be a great option for highly scalable, highly available systems. It supports storing petabytes of data and a flexible data schema, meaning different entities in the same table can have different schemas. References to NoSQL databases having “flexible schema” or being “schema-less” can give the impression that database schema design is a thing of the past and that you can bypass it and focus more on the application code. The reality is, even in this NoSQL world, schema design is very important and if you don’t give it due care and attention, then it can come back to bite you.

If you have a RDBMS background and are new to Azure Table Storage, it’s common to find yourself “thinking in SQL” and trying to solve database modeling requirements with a SQL approach before then trying to translate that to a key-value mindset. In this blog post, I’ll cover some of the fundamentals of Azure Table Storage and dive into some common questions you might find yourself asking about Azure Table Storage. Where code samples or references are applicable in this blog post, we’ll be focusing on .NET and using the Azure SDK (specifically relating to the Microsoft.Azure.Cosmos.Table nuget package).

Read on for the full story.

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Importing Perfmon Data Into SQL Server

David Klee continues a video series:

If you followed the last video, I showed you how to set up windows perfmon for ongoing performance metric collection on all of your critical SQL Server machines. However, having this raw data in a portable format doesn’t mean you have an easy means to access that data. In this training video, I show you a PowerShell script that we released that helps you export this data into a SQL Server database table so that you have access to the raw data to perform ongoing performance analysis with whatever favorite tool you prefer.

David walks through the process in a video, so check it out.

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