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Curated SQL Posts

Capturing SQL Server Login Details with extended Events

Jack Vamvas shows how to track SQL Server logins:

I have to capture logon information details for a specific logon on a SQL Server.   Specifically – the client_hostname, nt_username & username. What i’m looking for is a log recording a successful connection made to the server.     The event should be triggered a) when a connection is made & b)   from a connection pool. 

Click through to see how.

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From Azure Data Factory to Synapse Pipelines

Kevin Chant copies and pastes:

In this post I want to share an alternative way to copy an Azure Data Factory pipeline to Synapse Studio. Because I think it can be useful.

For those who are not aware, Synapse Studio is the frontend that comes with Azure Synapse Analytics. You can find out more about it in another post I did, which was a five minute crash course about Synapse Studio.

By the end of this post, you will know one way to copy objects used for an Azure Data factory pipeline to Synapse Studio. Which works as long as both are configured to use Git.

Click through to see how.

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Choosing between Power BI Pro and Premium

Marc Lelijveld has an image for us:

Often I got the question from customers: “Can you assign my workspace to a premium capacity?” But frequently they actually do not really need Power BI Premium. It remains to be a difficult topic to decide whether someone needs Power BI Premium or not. Therefore, I decided to setup a decision tree that helps to decide if you need Power BI Premium or not.

This decision tree highlights a bunch of Premium specific requirements and features like breaking the data size limits, XMLA Endpoints, unlimited content sharing and much more!

Click through to see that decision tree, though note that it does not differentiate between Premium and Premium per User.

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Comparing CPU Activity and Diagnosing the Cause

Joe Obbish has a tutorial for us:

Sometimes I have a need to run a quick CPU comparison test between two different SQL Server instances. For example, I might be switching from old hardware to new hardware and I want to immediately see a faster query to know that I got my money’s worth. Sometimes I get a spider sense while working with virtualized SQL Server instances and want to check for problems. Yesterday, I was doing a sort of basic health check on a few servers that I hadn’t worked with much and I wanted to verify that they got the same performance for a very simple query.

Click through for an easy test script and a good amount of diagnosis to understand why there is a significant difference between two instances.

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De Moivre’s Equation and Sample Size-Based Variance

Holger von Jouanne-Diedrich demonstrates de Moivre’s equation:

Over one billion dollars have been spent in the US to split up big schools into smaller ones because small schools regularly show up in rankings as top performers.

In this post, I will show you why that money was wasted because of a widespread (but not so well known) statistical artifact, so read on!

Do read on to learn more about this paradox.

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Visualization in Spark with Drsti

Jean-Georges Perrin shows off a Spark library:

I was looking for an effortless data visualization that would interface easily with Apache Spark. I found a few interesting tools, but nothing that would not require some complex interfacing, setup, or infrastructure. In a good geek way, I then decided to write the tool. This lack of simple tools is how Drsti (pronounced drishti) was born.

Aren’t you tired of looking at dataframes that looked like they came straight from a 1980 VT100? Sure, if you use notebooks, either standalone or hosted (IBM Watson Studio, Databricks…), you are not (or less) confronted with the issue. However, if you are building pipelines outside of the Data Science toys, oops, tools, you may need to visualize data in a graph.

Read on to see how it works and some of what you can do with Drsti.

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An Intro to Dapr

Steve Jones tries out Dapr:

I’ve heard about Dapr a few times from developer friends, but hadn’t really understood it that well. I had a webinar coming up, so I decided to spend a bit of time working with it to understand how it might function with an application.

I went to https://dapr.io/, and saw the basic outline of Dapr is in this video from their site. I also found this getting started video from Donovan Brown.

Note that Dapr is totally different from Dapper.

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ETL via Powershell

Greg Moore builds a simple ETL process using Powershell:

Recently a customer asked me to work on a pretty typical project to build a process to import several CSV files into new tables in SQL Server. Setting up a PowerShell script to import the tables is a fairly simple process. However, it can be tedious, especially if the files have different formats. In this article, I will show you how building an ETL with PowerShell can save some time.

It’s a simple process, but that’s a good reminder that simple processes can be good processes.

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HADR_SYNC_COMMIT

Sean Gallardy lays out what HADR_SYNC_COMMIT really tells you:

Initially I thought to myself, “this is the most misunderstood wait type that exists in the HA space for SQL Server”, then I realized maybe this isn’t the case… So, I pondered over this question, “is it truly misunderstood?” and came to the (possibly incorrect) realization that it is quite accurate in the general SQL Server’s users’ space of understanding. I also concluded that, really, it’s the way the wait is used in SQL Server coupled with how waits work in SQL Server, which leads to how it is viewed. Let me explain….

You’ll definitely want to read Sean’s explanation.

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Automating Notebook Execution with Powershell

Julie Koesmarno shows off an automation process for notebooks:

When I first think about automation, I generally think in the following way: in order to automate a script, we want to ensure that the script itself can be run via a command line interface (CLI) and with almost no user interaction (except for input and output parameters). Now, how do we apply this to Jupyter Notebooks so that we can automate SQL notebooks or PowerShell Notebooks?

The good news is that these SQL notebooks and PowerShell notebooks that we’ve created using Azure Data Studio, can be run on PowerShell CLI. If these notebooks can be run on PowerShell CLI, that means any automation systems or serverless architecture (Azure Automation combined with Azure Logic Apps as an example) should be able to run these notebooks also.

In this blog post, I’ll cover examples on using Invoke-SqlNotebook, using Invoke-ExecuteNotebook and putting it together with Azure Automation.

Click through to see the whole thing.

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