A Fine Slice Of SQL Server
Olivier Van Steenlandt troubleshoots an issue:
When setting up database mirroring from Azure SQL to Microsoft Fabric for one of my demo databases, I ran into an issue while trying to connect to my Azure SQL database.
As you can see in the screenshot above, it seems that a setting on my logical SQL Server in Azure is misconfigured. Let’s resolve that in a couple of steps.
Click through for the screenshot, the specific error, and how Olivier was able to get things working.
Leave a CommentJon Lunn digs into a somewhat-new feature:
So first off, what are they? They are basically a table object that is based on a query. (Yes I know they are called ‘Views’… more on that later) So like a view, it is defined by a SQL query, but it doesn’t just sit over tables and runs that SQL when you query that view. What it does do is take the ‘View’ SQL query that defines the Materialised Lake Views, runs it and stores the query result data into a delta table. So when you query that view, you get the data from that object, and not the underlying tables. Neat! Save a bit on computing query time!
Read on to learn more about what they are, how they work, and when they can be useful.
Leave a CommentLouis Davidson has made a big mistake:
As I sit here, preparing to write my roundup post, I have not read anyone else’s post yet. I thought it would be good to introduce the idea first, recap to the other posts, then mine. I won’t share any detail of the mistake I shared, but I do want to mention something I included in my post. Types of mistakes. Mistakes of choice, and mistakes of accidents.
Read on for a nice round-up of a popular topic.
Leave a CommentRebecca Lewis shares a tale of woe:
Cloud-based SQL Server security isn’t simpler. It’s different — and the learning curve is brutal if you grew up on-prem.
If you’ve spent years working Windows authentication, SQL logins, role memberships, and the occasional certificate, you may assume cloud security is more of that, just with a portal. Not. The SQL Server/Cloud permission models are layered differently, the terminology shifts depending on the platform, and the people who ‘own’ security are spread across teams that don’t always speak the same language.
Read on for an example of the kinds of challenges you can run into. Adding to that complexities around managed identities and authorization mechanisms and things can get very convoluted, even when the intent is to simplify matters.
Leave a CommentPankaj Arora announces a new preview feature:
Until now, surge protection applied only at the capacity level—meaning all workspaces shared the same rules.
What’s new: workspace-level surge protection
We’re taking surge protection to the next level with workspace-level controls. This update gives you more granular management of compute usage across your organization.
Read on to see what this means for organizations using Microsoft Fabric.
Leave a CommentChris Webb takes us through a performance issue:
Here’s a fun DAX performance tip that I found this week. Do you have measures that use Calculate() with a filter on a numeric column? Is one of the filters on the value 0? If so then this may affect you.
Read on for a demonstration.
Leave a CommentMarco Russo and Alberto Ferrari want more detail:
A common challenge in Power BI reporting is how to display several pieces of information about a single item (such as sales transactions, product details, or customer details) without dedicating a separate column to each attribute. Using individual columns for each detail can consume space, especially for fields that are often empty. This article explores techniques to consolidate multiple fields from a business entity or transaction into a single column in a matrix visual, thus presenting transaction details in a space-efficient way.
They walk through several iterations of the process. The real challenge with displaying those details is that your end users need to understand what’s in the details, as there’s no good way to describe what the information means. But when your users do understand what can be in there, I could see this being quite helpful.
Leave a CommentRadim Marek goes deep into buffers:
The work around RegreSQL led me to focus a lot on buffers. If you are a casual PostgreSQL user, you have probably heard about adjusting
shared_buffersand followed the good old advice to set it to 1/4 of available RAM. But after we went a little bit too enthusiastic about them on a recent Postgres FM episode I’ve been asked what that’s all about.Buffers are one of those topics that easily gets forgotten. And while they are a foundation block of PostgreSQL’s performance architecture, most of us treat them as a black box. This article is going to attempt to change that.
Read on to learn more about how PostgreSQL users buffers.
Leave a CommentBen Richardson looks at a pair of beta functions:
Microsoft just added some brand-new IMPORT functions, designed to make bringing external data into Excel easier!
Instead of digging through menus or writing your own queries, you can now just use these new formulas, IMPORTTEXT and IMPORTCSV.
Importing data is something we do all the time, downloading CSV files, opening data from text files, or pulling data from databases. Having some new functions to keep expanding that skill set is just going to save so much time!
For well-structured files, these functions look to be quite effective. I do wonder how they’d fare against some of the messier CSVs we often need to deal with in real life.
Leave a CommentSemab Tariq wants to see which indexes are in use:
Indexes exist to speed up data access. They allow PostgreSQL to avoid full table scans, significantly reducing query execution time for read-heavy workloads.
From real production experience, we have observed that well-designed, targeted indexes can improve query performance by 5× or more, especially on large transactional tables.
However, indexes are not free.
The reasons for why are very similar to what we have in SQL Server. The way to track utilization is a bit different, however.
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