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Month: January 2023

Backing up SQL Server with Multiple Solutions

Published 2023-01-12 by Kevin Feasel

Chad Callihan tells us a story:

Many years ago, a friend was using a backup/recovery tool for managing their backups. This particular tool on its own wasn’t necessarily bad. But in this case, it didn’t work well. In fact, it barely worked at all. Backups were slow to complete and restores were even slower. Attempting to restore even one database could take 10-15 minutes just to navigate a GUI and start the restore process.

It…was…very…slow…

Read on for the rest of the story. Most of the time, when I see two products used for backups, I typically see a bunch of redundant backups, with both products taking full backups.

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Start and Stop for Managed Instances

Published 2023-01-12 by Kevin Feasel

Arun Sirpal pushes the big red button:

We all would like to save money when operating in the cloud, Microsoft has released a stop / start concept for SQL Managed Instances – preview mode!

At the time of writing, the Managed Instance needs to be built from the November wave where you will see the functionality in the overview section and it has to be in the General purpose tier. If you have managed links or failover groups then you cant use this feature.

There is a kicker, however, which makes this a less-than-pleasant option. Arun has more detail.

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Moving Azure SQL MI between Subscriptions

Published 2023-01-12 by Kevin Feasel

Sabrin Alsahsah migrates a SQL managed instance:

We have recently received a few service requests from our customers to know how to move an Azure SQL-managed instance between subscriptions. In this blog article, we will be discussing supportability, methods, and solutions that can achieve this goal, and you can decide the best for you depending on your business requirements and environment setup.

Currently, at this time there is no direct way to move a managed instance itself, but we can have a workaround by moving the Azure SQL managed databases across Azure SQL managed instances that are hosted\located in different subscriptions.

Click through for three workaround options.

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Ways to Convert a List to DataFrame in R

Published 2023-01-11 by Kevin Feasel

Tomaz Kastrun starts the stopwatch:

When you are working with large datasets performance comes to everyone’s mind. Especially when converting datasets from one data type to another. And choosing the right method can make a huge difference.

So in this case, I will be creating a dummy list, and I will convert the values in the list into data.frame.

Click through for a variety of techniques and how well they performed. There are some good solutions in the comments as well.

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KQL Contains and In

Published 2023-01-11 by Kevin Feasel

Robert Cain continues a series on KQL:

There are versions of these which are case sensitive. We’ll see a few here, focusing on the contains keyword. In addition there are not versions, which will also be demonstrated.

There is another operator we’ll discuss here, in. It is a bit of an odd duck, in that it is case sensitive by default. We’ll see it and its variants later in this post.

Case sensitivity in search is a curse.

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Indexing in Postgres

Published 2023-01-11 by Kevin Feasel

Grant Fritchey provides an overview:

In this article I’m going to go over the different types of indexes and some index behaviors. We’ll get into what the indexes are, how they work, and how best you can apply them within your databases. I’m hoping you’ll develop an understanding of which indexes are likely to work better in each situation.

However, I won’t be covering the indexes in detail. Further, I won’t be going very far into how these indexes affects performance. I’m not yet up on performance tuning within PostgreSQL. That article is quite a way down the track from here. When you know which index to use where, you can then drill down to better understand that index, and how best to measure the performance impacts.

This set of indexes is quite different from what we’re used to in SQL Server and much closer to what you get in Oracle.

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A Report of 2022’s Best Power BI Features

Published 2023-01-11 by Kevin Feasel

Nicky van Vroenhoven goes the extra mile:

Last night we had a work meeting at Powerdobs, with a few presentations about business updates, new joiners in the coming months and Power BI projects. I had the pleasure of closing the evening with a presentation on Power BI.

So I decided to do a presentation on my favourite additions to Power BI over the past year. But instead of doing a regular PowerPoint presentation, I decided to do an all-Power-BI presentation. It was very well received and I was encouraged to share it here!

Click through for the embedded report. Great job by Nicky to put this together.

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DB Restoration and Upgrade Management for Arc-Enabled Data Services

Published 2023-01-11 by Kevin Feasel

Warwick Rudd continues a series on Azure Arc-Enabled Data Services. Part 9 covers database restoration:

Now that we have our Azure Arc-enabled SQL Managed Instance deployed, potentially one of the most common tasks you will need to undertake is being able to perform a database restore of an existing database to your newly provisioned Azure Arc-enabled SQL Managed Instance.

In our previous post, we deployed our Azure Arc-enabled SQL Managed Instance – “ae-sqlmi-demo” that we will continue to investigate and learn about how we can utilize in our data environments. In this post, we are having a look at restoring a database.

Part 10 looks at upgrade management:

Managing your Data Controller through Azure Data Studio provides an easy approach for controlling when you wish to apply upgrades supplied by Microsoft. This is something you need to stay on top of as the upgrade path is an incremental approach and only allows you to upgrade to the next version. If you leave it too long, you could be faced with multiple upgrades to be undertaken. This could lead to extended outages while you get up to date.

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Pull Requests and Database Projects

Published 2023-01-11 by Kevin Feasel

Olivier Van Steenlandt continues building out a database project:

A Pull Request is an alternative way of merging branches. Instead of executing the merge yourself, you will create a Pull Request for someone else to revise your development and approve and merge when ok. By doing this you are introducing peer reviewing into your development process. From my experience, using Pull Requests will improve your development quality since someone needs to validate your changes before they can be deployed to a certain environment.

I wouldn’t advise using Pull Requests to get changes in a development environment but I would advise using it to get changes to an Acceptance- or Production environment. By doing this, you can already find issues in an earlier stage than in production.

Read on to see how they work, using Azure DevOps as the example. GitHub pull requests are very similar in nature.

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Parallel Loading in Spark Notebooks

Published 2023-01-10 by Kevin Feasel

Dustin Vannoy answers some questions:

I received many questions on my tutorial Ingest tables in parallel with an Apache Spark notebook using multithreading. In this video and post I address some of the questions that I couldn’t just answer in the YouTube comments. Watch the video for more complete answers but here are quick responses with links to examples where appropriate.

Click through for the video and some text versions. Dustin includes examples for Synapse and Databricks.

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