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Month: June 2022

Query Store in SQL Server 2022

Melody Zacharias gives us a heads up on what’s new with Query Store:

The SQL Server team has improved on Query Store for 2022 again and made some great improvements for SQL 2022. Query Performance was originally introduced as a flight recorder for your queries. It uses a system that gathers query performance data and gives you insights into your work loads over time. In 2022 it is being used to build and expand new capabilities in intelligent query processing.  To allow this to work well and be accurate, Query Store is now enabled by default for new databases. In addition to providing hinting support, it will facilitate the ability to build new intelligent query processing scenarios and improve performance.

Read on for a list of improvements you’ll see in the product.

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An Overview of Parameter-Sensitive Plan Optimization

Erik Darling is diving into what we currently know about Parameter-Sensitive Plan Optimization, starting with an overview:

The way this feature works is, rather than caching a single query plan for every other execution to use, it creates what’s called a Dispatcher plan (if your query qualifies).

You’ll see something like this in the properties of the root node of your query plan, and your query will have some additional funny business at the end of it.

Read on to see what information is available to us and current feature limitations.

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Resolving Implicit Conversion on a Join

Andrea Allred has a process:

As I was troubleshooting a performance issue, I noticed that there was an implicit conversion (SQL Server automatically converts the data from one data type to another) happening in my join. The join was on a column that was named the same in both tables, but one was datatype INT (integer) and the other was a datatype of VARCHAR(50) (variable character up to 50 places).

Read on for one way to resolve this issue…so long as no other calling code expects a string on a call.

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Triggering a Power BI Dataset Refresh from Synapse

Nick Edwards updates a dataset:

Login to and in the top right hand corner locate “Settings” and then “Admin portal”

Under “Tenant settings” locate “Developer Settings” and then “Allow service principles to user Power BI APIs”.

Set this service to “Enabled” using the toggle. Next under the heading “Apply to:” select “Specific security groups (Recommended)”. Next add the newly created security group “AzureSynapsePowerBIIntegration” and click apply.

Click through for the full process.

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Reading from and Writing to Excel with R

Benjamin Smith needs to modify an Excel file:

I was recently asked as part of a larger task to combine multiple sheets from an excel workbook into a into a single sheet. When approached about the problem I immediately was asked if I was going to use VBA to do it. While I know my way around VBA, since VBA does not have a native way to undo its operations I was uncomfortable with the potential hazard using VBA would yield if a mistake was made or something wrong happens.

In this blog I share how its possible to combine and format sheets using the openxlsx package and base R. Since I’m limiting myself to one library and base R, I will be employing base R’s pipe operator – |>, instead of the superior magrittr pipe – %>% (my opinion only, don’t take it too seriously).

Can confirm, the magrittr “default” pipe is better.

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SharePoint Lists Showing 100 Items in Logic Apps

Koen Verbeeck needs more than 100 results:

I was reading a SharePoint List using the “Get Items” activity in an Azure Logic App. I explain how you can create such a Logic App in the blog post Reading a SharePoint List with Azure Logic App.

It all worked fine for a while, but recently the list grew larger than 100 items. Suddenly, I started getting complaints that some items didn’t make it into the data warehouse. What’s going on? I ran the Logic App and I could see only 100 items were inserted into the SQL Server table:

Read on to see how you can bump that number past 100.

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Using a Tree Map as a Legend in Power BI

Prathy Kamasani makes clever use of a tree map:

I recently worked on two projects where the client wanted to show multiple metrics sliced by the same categorical data. For example, seeing how various metrics are performing over different regions or different product groups. A use case like this can be achieved in many ways; probably the best approach is to use small multiples functionality or to keep it simple, five same visuals with different metrics.

Let’s look into it with energy consumption data. Here, I want to show metrics 1 to 5 on different income levels over the years.

I like this solution when you have multiple graphs off of the same base data, like in the small multiples scenario Prathy shows us.

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Restoring SQL Managed Instance Backups to SQL Server 2022

Mladen Andzic has a preview around how we can take a Managed Instance backup and go on-premises:

Restoring a backup file is the easiest way to copy a SQL Server database to another instance. It allows you to create a copy of your production database for easier troubleshooting or debugging of an issue, to provide a copy of a database to your end users or eligible third parties, or as a light-weight business continuity/disaster recovery solution to restore functionality on another instance of SQL Server. These are just a few use cases, and the list is much longer and there are some very inventive ways of using backup-restore in the wild.

This article explains the challenges of cross-release restore to an older version of SQL engine and announces the private preview of a capability to restore a backup of a database taken from Azure SQL Managed Instance to instance of SQL Server 2022. 

So much SQL Server functionality has been built with the idea of getting you from on-premises into the cloud (specifically Azure) but it’s good to see them spend some development effort on the entirely reasonable and realistic scenario that Azure is not the best choice for a company and there are many such companies still willing to throw money at Microsoft for a good product.

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“Unsafe Repository” When using Git

Niels Berglund sees something odd:

Every 6 – 9 months (or so), I clean up my development PC just to keep it “lean and mean”. I do it by formatting the hard-drive partition the OS (in this case, Windows) is on, followed by a new install. Recently I had a four-day weekend here in SA. Four glorious days off, a perfect time to “nuke” my PC and re-install!

Off I go, everything goes to plan (Chocolatey is my friend), and after a while, I am done (or as done as one can be). At this stage, I needed to do my weekly roundup blog post for the week gone by, and as I had done some changes to the GitHub repo from my MacBook Pro, I wanted to do a git pull in the repo directory for my blog. Part of the story is that on my dev PC, I have all my repos on a separate partition from the system partition, so the non-system partition was un-affected by the reformat (or so I thought). Imagine my surprise when doing the git pull I got:

Click through to see the error and root cause.

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