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Month: March 2022

Azure SQL News

Anna Hoffman brings us tidings:

Emily Lisa kicked it off by telling us about the latest Azure SQL Database product updates including Azure SQL maintenance windowszone redundancy for SQL Hyperscale, and configurable backup storage redundancy for SQL Hyperscale.

Dani Ljepava from the Azure SQL Managed Instance product team came on to share a range of new features announced at SQL Bits now available in public preview: Link feature for Managed Instancedata virtualization with ADLSAdvanced notifications for planned eventsHybrid Service BrokerWindows authentication for Azure AD Principals, and the general availability of Maintenance windows. Watch the episode to see a special look at Link feature for Managed Instance!

Pam Lahoud also came on to talk about about the latest improvements that help you manage your SQL Server in Azure Virtual Machines, including the newly released SQL best practices assessment, all available to you by installing the free SQL IaaS Agent extension!

Read on for plenty more links and updates.

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Azure Functions and Azure SQL Database

Rajendra Gupta builds a simple Azure Function:

As a Platform as a Service (PaaS) service, Azure SQL Database enables developers to deploy SQL Database in Azure Cloud without managing the infrastructure. We use SQL Server Agent to schedule jobs to run at a specific schedule in an on-prem SQL instance. However, Azure DB does not have agent functionality.

There are multiple ways to schedule job or batch processes in the Cloud. You can explore the Azure automation series for executing scripts using Azure Logic apps and automation runbooks.

This article focuses on the Azure functions for scheduling a job for Azure SQL Database.

Read on for the process.

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Finding Query Timeouts with Query Store

Kendra Little searches for timeouts:

Here are some basics regarding query timeouts for SQL Server, Azure SQL Database, and Azure SQL Managed Instance:

– Execution timeouts are NOT set or enforced by the database engine. It is happy to wait for your query to run or for your transaction to be open for hours, days, or years, until you commit, cancel, or get disconnected.

– Timeouts are set by the calling application. If you don’t explicitly set a timeout on your connection string, there is generally a default timeout that is used. Often, this is 30 seconds for query execution timeouts.

– Connection timeouts are different than execution timeouts. If you see a connection timeout, often this is a firewall or network issue preventing you from connecting to the database – or perhaps it’s even offline. Execution timeouts are when the calling application doesn’t want to wait any more for a query to complete.

Kendra shows how to generate an execution timeout and how you can use Query Store to find them. And Kendra’s post got Mark Freeman to write a blog post so that’s also worth something.

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When Compute Scalars Attack

Erik Darling goes scalar hunting:

This is awful. It really is. It’s so awful. These operators skated by undetected for years. Acting so innocent with their 0% cost.

Subprime operators, or something.

In this post, I’m going to show you how compute scalars hide work, and how interpreting them in actual execution plans can even be tricky.

I’m now imagining Erik as the Steve Irwin of the query tuning world. And it’s kind of working for me.

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Finding Zero-Record Tables Taking Space in SQL Server

Jeff Iannucci has a follow-up for us:

This is a follow up post to the previous one about tables with no records using data space, with the idea coming from twitter of all places. Sometimes on twitter the conversations kill, but after reading that post my friend Chris Wood suggested writing something to FIND those tables.

Which is a solid idea, so let’s get to it. No time to wait too long.

Click through for the process.

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YEARFRAC() in Power Query

Imke Feldmann translates an Excel function to Power Query:

While there is a native YEARFRAC-function in DAX that you can use to calculate year fractions, sometimes you might just need it in Power Query. The function I’m presenting here has the same function arguments than its Excel-equivalent. Its 5 different modes require some advanced calculations. Fortunately I found a great resource on how to calculate it here. So my version here is basically a direct translation into the M-language.

Click through for the code.

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The Right Amount of Detail on a Visual

Mike Cisneros answers a tricky question:

How much context, then, is necessary to include, so that we have an understandable (but un-cluttered) visual, presented with enough background information for the viewer to grasp its meaning, with the key insights and recommended actions emphasized?

When we’ve addressed this question in the past, we’ve relied on the always-true, if sometimes unsatisfying, response of, “It depends.” Every situation is unique, and there’s no checklist or scorecard you can use in every circumstance to ensure that you’ve hit the perfect amount of detail.

Read on for two factors upon which it depends.

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Making Kafka Clients Faster

Yeva Byzek has a few whitepaper recommendations:

Over the years, incredible technical content has been written about data plane performance, general principles and tradeoffs, cloud-native architectures, etc. These writings describe how you can get low latency and high throughput without compromising on a mature and reliable platform that provides persistence, no data loss, audit logs, processing logs, and more—all the things that enable you to go from proof of concept to production. This blog post highlights the top five reading recommendations to help you gain a deeper understanding of what makes applications that run on Confluent Cloud so fast. They cover the key concepts and provide concrete examples of how we do it, and how you can do it too, with specific benchmark testing and configuration guidelines.

Click through for links to those resources.

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Azure Purview Announcements

Wolfgang Strasser looks at some of the new Azure Purview announcements:

For me, Data lineage is one of those fascinating techniques to better understand your data estate and get a better knowledge how systems are connected and what data flows are there in your data landscape.

Lineage was there in Azure Purview since the beginning (Azure Data Factory, SSIS lineage, Power BI) but this week another very important part of data lineage was put into public preview: Dynamic Lineage Extraction from Azure SQL Databases.

Read on for more information.

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Database Code Reviews: a Process

Kenneth Fisher reviews some code:

I’ll be honest, ever since I did a SQL Homework about doing code reviews I’ve wanted to do a blog post about them. Recently Emily Krager (TikTok | Twitter) did a TikTok about code review suggestions which seemed like a good excuse for me to do this. If you don’t follow her I recommend it, she does a great job of combining humor and technology and is just a lot of fun to listen to. Here is her list as best I was able to transcribe it.

Click through for Kenneth’s thoughts on the topic.

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