Category: Uncategorized

Mikey Bronowski walks through a slew of dbatools cmdlets which replicate behavior from SQL Server Management Studio:

The reasons to alter the database might be as many as different users. Some want to rename the old database, or maybe change the owner or recovery model after restoring the database. Enabling features like Query Store is also common. Most of this can be done from the Database Properties screen and as well with dbatools.

This is part of a whole series on dbatools which Mikey has been putting together, and to which you can find a link as you click through.

Ebru Ersan announces a new extension for Azure Data Studio:

SQL Server Assessment Extension for Azure Data Studio provides a user interface for evaluating your SQL Server instances and databases for best practices. It uses SQL Assessment API to achieve this. In this preview version, you can:

– Assess a SQL Server or Azure SQL Managed Instance and its databases with built-in rules (Invoke Assessment)

– Get a list of all built-in rules applicable to an instance and its databases (View applicable rules)

– Export assessment results and list of applicable rules as script to further store it in a SQL table

It’s in preview status and requires version 1.19.0 (this month’s version) of Azure Data Studio at a minimum.

Taiob Ali tries out a new feature in SQL Server Management Studio:

SQL Server Management Studio (SSMS) was released on April 7th, 2020. You can download this latest version from this link. 18.5 is an update to 18.4 with these new items and bug fixes.

One of the features added in this release is to select ‘Azure Data Studio‘ Notebook as a destination for Generate Scripts wizard.

Now you can send the objects definition of Table, View, Stored Procedure, Function along with sample call, sample data, and my comments all packaged in one Azure Data Studio Notebook. I can see scope for better communication between business partners, developers, and database engineers.

Click through for an example of the process.

Erik Darling thinks about what phase in a procedure one should index a temp table:

You already know that your temp table needs an index. Let’s say there’s some query plan ouchie from not adding one. You’ve already realized that you should probably use a clustered index rather than a nonclustered index. Adding a nonclustered index leaves you with a heap and an index, and there are a lot of times when nonclustered indexes won’t be used because they don’t cover the query columns enough.

Good. We’ve fixed you.

But, like, when should you create the index?

I try to do as many inline operations as I can with temp tables because doing so means you might be able to take advantage of temp table reuse, and on a frequently-running procedure, that can make a difference.

Tim Mitchell looks at regular expressions in SQL Server Management Studio:

Regular expressions (or simply regex for short) have long been used by system administrators and data professionals for searching and manipulating text. Regular expressions allow the user to find, replace, and manipulate text based on the pattern they define in the expression. While every text editor allows simple search-and-replace capabilities, regex allows for searching for partial matches, using wildcards, and even integrating special characters (such as newlines and tabs) into the search or replacement text.

Regular expressions have been a part of SSMS for as long as I can remember, and make the process of pattern-based SQL code search much easier. In this tip, I’ll show you a couple of brief examples of the use of regular expressions for working with SQL code in Management Studio.

Regular expressions have been in the product for a long time, but the set of available regular expressions changed when SSMS moved over to the Visual Studio shell. And in some ways (particularly around capture groups), that was a change for the worse.

James Serra gives us some insights on the future of Power BI and how it relates with Azure Synapse Analytics today:

As an example of the speed of each layer, during an Ignite session (view here), there was a Power BI query run against 26 billion rows that was returning a sum of store sales by year. The same query was run three times using a different layer:

1. Using a DirectQuery against tables in SQL DW took 8 seconds
2. Using a DirectQuery against a materialized view in SQL DW took 2.4 seconds.  Note you don’t have to specify that you are using a materialized view in the query, as the SQL DW optimizer will know if it can use it or not
3. Using a Aggregation table that is Imported into Power BI took 0 milliseconds

Keep in mind this is all hidden from user – they just create the report.  If they do a query against a table not in memory in Power BI, it will do a DirectQuery against the data source which could take a while.  However, due to SQL DW result-set caching, repeat DirectQuery’s can be very fast (in the Ignite session they demo’d a DirectQuery that took 42 seconds the first time the query was run, and just 154 milliseconds the second time the query was run that used result-set caching).

There’s some interesting information in here, especially around Power BI eventually taking over Azure Analysis Services’ space in the market.

Gilbert Quevauvilliers shows how you can use load balancing with Power BI gateways:

I always recommend for On-Premise Data Gateway installations that there be at least 2 Gateways installed.

The initial reason was to ensure that if one gateway went down the other one would be able to still refresh or connect to the DirectQuery or LiveConnection sources.

With the recent update where you can now control the CPU and Memory on each Gateway instance, this means that I am able to define a dedicated server to take more of the refreshing/DirectQuery/LiveConnection load. And I can offload secondary refreshing to the second server which might be installed on another server with multiple roles.

NOTE: In order this to work you must have the Oct 2019 version of the On-Premise Data Gateway installed.

There’s a lot of good information here, including one potential failure scenario.

Milos Radivojevic takes us through a quick demonstration of a change in SQL Server 2019:

By using the same formula, the estimated number of rows is:

SELECT 0.001992032*1000000
--1992.032000000

This is exactly what we see in the execution plan. OK, that was CL 140, let’s see how SQL Server 2019 handles this simple case.

When we switch to CL 150, the plan and estimations for the c1 column (non-nullable) are the same. However, the estimation for the nullable column is changed!

Read the whole thing.

Eric Cobb has an enhancement to the SQL Server Metrics Pack:

I recently had a case at work where a database was restored, and several important indexes were accidentally removed. But because we are using SQL Server Metrics Pack to track the indexes on that server, we were easily able to recover all of the deleted indexes.

In order to spotlight the feature a little, I wanted to answer a few questions and provide some queries to help explain how to use this new feature.

Read on to learn more, and check out the GitHub repo as well.