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Month: July 2021

Finding the Culprit in a Database Timeout

David Fowler sets us straight on query timeouts:

Not very helpful, right? And unless you’ve got some sort of monitoring in place, for example you can find these in SQL Sentry by looking for aborted queries, or you’re picking these up in your applicaiton logging, you’re going to have a hard time tracking down what query actually tripped the timeout. As you’re reading this post, I’m going to assume that you haven’t got monitoring.

So how do we go about figuring this out?

Click through for the answer.

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Differences in Power BI PPU Models vs Azure Analysis Services

Gilbert Quevauvilliers continues a series on migrating from Azure Analysis Services to Power BI Premium Per User:

When creating a new dataset in AAS this is typically done with Visual Studio, there are a lot of similar items between Visual Studio and Power BI desktop, the biggest difference is how you access them are very different as well as their look and feel.

When starting with a new dataset the process is to create a new data source, import some data and then to create the tables.

Click through for the differences. This is one area where Power BI drags in comparison to Azure Analysis Services.

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Azure Test Plan Terminology

Kevin Chant is here with a language lesson:

In this post I want to cover some Azure Test Plans jargon for Data Platform professionals. Because I understand it can be confusing.

In addition, I did say I would explain some jargon in my last post about using Azure Test Plans for Data Platform deployments. Of course, these explanations will help with other kinds of deployments as well as Data Platform ones.

By the end of this post, you will have a better understanding of some of the jargon involved in Azure Test Plans. Plus, a good recommendation of a lab to use.

Click through for that depiction.

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Data Mesh and Ownership Strategies

James Serra aims to clear up some confusion:

I have done a ton of research lately on Data Mesh (see the excellent Building a successful Data Mesh – More than just a technology initiative for more details), and have some concerns about the paradigm shift it requires. My last blog tackled the one about Centralized vs decentralized data architecture. In this one I want to talk about centralized ownership vs decentralized ownership, along with another paradigm shift (or core principle) closely related to it, siloed data engineering teams vs cross-functional data domain teams.

First I wanted to mention there is a Data Mesh Learning slack channel that I have spent a lot of time reading and what is apparent is there is a lot of confusion on exactly what a data mesh is and how to build it. I see this as a major problem as the more difficult it is to explain a concept the more difficult it will be for companies to successfully build that concept, so the promise of a data mesh improving the failure rates for big data projects will be difficult to achieve if we can’t all agree exactly what a data mesh is. What’s more is the core principles of the data mesh sound great in theory but will have challenges in implementing them, hence my thoughts in this blog on centralized ownership vs decentralized ownership.

Read on for James’s take on the matter.

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Connecting to Azure Blob Storage from Power BI

Kristyna Hughes links Power BI to a data source:

The step-by-step process below walks through connecting to data housed in Azure Blob Storage from Power BI using a SAS token. There are many ways to grab your data from Blob Storage, but this is the most efficient, scalable, and secure way that I found (with some security restrictions from watchful DBAs).

Click through for the solution, which is based on using SAS tokens.

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Issue with SQL Server and High Availability in Kubernetes

Andrew Pruski has a problem:

I’ve been running a proof of concept for SQL Server on Kubernetes over the last year or so (ok, probably longer than that…hey, I’m a busy guy 🙂 ) and have come across an issue that has been sort of a show stopper.

There are currently no HA solutions for SQL Server running on plain K8s (not discussing Azure Arc here) so my tests have been relying on the in-built HA that Kubernetes provides but there’s a problem.

Be sure to check it out because it is a doozy.

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Deploying Azure Policies via Terraform

Jonathan D’Aloia shows how you can use Terraform to work with Azure Policies:

As you may all know Terraform serves a great purpose in deploying resources and infrastructure into your Azure environment, however, Terraform can also be used to automate and consistently deploy Azure Policies which can be defined prior to any resources being generated. In this blog, I will cover how you can import policies into your Terraform State to then deploy into an Azure Resource Group in order to secure your landing zone prior to deploying any resources.

Click through for an example.

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Minimizing PAGELATCH_EX Waits in SQL Server 2019

Aaron Bertrand has some advice for us:

There is a common problem in SQL Server where contention when writing to a single page can lead to excessive waiting. This waiting comes in the form of the wait type PAGELATCH_EX, and often happens when the clustering key is a monotonically increasing value – like an IDENTITY or date/time column. Pedro Lopes has highlighted some non-trivial workarounds in his post, “PAGELATCH_EX waits and heavy inserts,” and there is some official guidance in the Microsoft Docs article, “Resolve last-page insert PAGELATCH_EX contention in SQL Server.” But are there any ways to address this issue without intrusive changes?

Read on to see what Aaron has in mind.

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