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Category: Versions

Azure Data Studio March 2020 Release

Published 2020-03-24 by Kevin Feasel

Alan Yu announces the March 2020 release of Azure Data Studio:

Now you can add visualizations using a T-SQL query. In addition, as the gif illustrates, you can also customize your visualization whether it is a scatter or time series graph.

You can also copy your visualization or save the image so that you can quickly add this in an email or report to other team members.

We will continue to bring improvements to charting over the next few months.

They’ve put a lot of time and effort into notebooks. They’re still missing some of the quality of life improvements I want to see before moving to them full-time, but they’re consistently getting better.

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SQL Server 2019 Supports Ubuntu 18.04, SLES 12 SP5

Published 2020-03-17 by Kevin Feasel

Tejas Shah announces a couple new versions of Linux distributions SQL Server 2019 supports:

We are also glad to announce the availability of SQL Server 2019 CU3 container image build on Ubuntu 18.04. It is fully supported for production use. You can read about how to deploy the container at following page.

Running SQL Server 2019 CU3 container with Ubuntu 18.04 base: https://docs.microsoft.com/en-us/sql/linux/quickstart-install-connect-docker?view=sql-server-ver15&p…

You could run SQL Server on these versions of Ubuntu and SUSE, but now you get production support, making it prudent to run on these. Ubuntu 20.4 is coming out soon, so we’ll see when that gets supported.

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R 3.6.3 Now Available

Published 2020-03-11 by Kevin Feasel

David Smith takes a look at R 3.6.3:

On February 29, R 3.6.3 was released and is now available for Windows, Linux and Mac systems. This update, codenamed “Holding the Windsock“, fixes a few minor bugs, and as a minor update maintains compatibility with scripts and packages written for prior versions of R 3.6. 

February 29 is an auspicious date, because that was the day that R 1.0.0 was released to the world: February 29, 2000. In the video below from the CelebRation2020 conference marking the 20th anniversary of R, core member Peter Dalgaard reflects on the origins of R, and releases R 3.6.3 live on stage (at the 33-minute mark).

I’m holding out for R 4, though then I’ll have to wait to see when SQL Server will officially support it.

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Deprecated and Discontinued Features in SQL Server

Published 2020-03-05 by Kevin Feasel

Randolph West takes a look at my favorite activity: deleting code:

The following statements are true:

– SQL Server 2019 does not have any deprecated features, but does have discontinued features
– SQL Server 2017 does not have any discontinued features, but does have deprecated features
– SQL Server 2016 has both deprecated and discontinued features

Let’s discuss the difference between deprecated and discontinued features, and explain how this affects database administrators looking to move to SQL Server 2016 or newer. My current advice is to target SQL Server 2019 with at least Cumulative Update 2 (CU2).

Read on for more details.

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SQL Server 2019 and sys.syslogins Changes

Published 2020-02-24 by Kevin Feasel

Taryn Pratt goes into a change in the sys.syslogins system view in SQL Server 2019:

Sigh ok, something is really broken because this was working before we failed over.

The code for the login replication basically does the following via a cursor (yeah, I know, but it works…normally):

1. Select from the primary via OPENQUERY to query the logins and passwords
2. Using sp_hexadecimal convert the varbinary password to a string value
3. Create a string to be executed, i.e. dynamic SQL that runs a CREATE LOGIN

Read on for the whole story and how you can protect yourself as you upgrade to SQL Server 2019.

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Azure Data Studio February Release

Published 2020-02-14 by Kevin Feasel

Alan Yu announces the February 2020 release of Azure Data Studio:

Azure Data Studio is a multi-database, cross-platform desktop environment for data professionals using the family of on-premises and cloud data platforms on Windows, MacOS, and Linux. To learn more, visit our Github.

The key highlights to cover this month include:

– Improved Azure sign in support.
– Find in Notebook support.
– Visual Studio Code merge to 1.42.
– Bug fixes.

Read on for more details on each topic.

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Interleaved Execution with SQL Server

Published 2020-02-10 by Kevin Feasel

Milos Radivojevic takes us through improvements with interleaved execution in SQL Server:

As you might know, the Interleaved Execution is the member of the Intelligent Query Processing family of features. It has been introduced with SQL Server 2017 (as a part of the Adaptive Query Processing). It is designed to improve the performance of queries referencing multi-statement table-valued functions (MSTVF). Actually, it addresses currently only queries using MSTVF, but is hopefully designed for much more. The query optimizer usually has two issues with queries using MSTVF:

– MSTVF is a black-box for the optimizer; it does not know what’s inside, it cannot perform cross-statement optimization (as it is a case with inline TVFs) and it assumes it is a cheap and fast operation
– MSTVF has a fixed cardinality of 100 (prior to SQL Server 2014, it was 1)

Interleaved execution does not improve the first issue (MSTVF is still a black-box for the optimizer), but solves the cardinality issue.

Read on to understand how this second aspect has changed for the better.

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Check Those R Repos

Published 2020-02-06 by Kevin Feasel

John Mount has a public service announcement:

In a lot of our R writing we casually say “install from CRAN using install.packages('PKGNAME')” or “update your packages by using update.packages(ask = FALSE, checkBuilt = TRUE) (and answering ‘no’ to all questions about compiling).”

We recently became aware that for some users this isn’t complete advice.

The above depends on your R install pointing to a repository that is in fact up to date. To check what repositories you are using please use the command options('repos').

The specific example here is around the Microsoft R Archive Network (MRAN), which stays at fixed dates. This is for a good reason: because it helps companies standardize on a known set of versions of R packages by default. That way you don’t have version 1.8 of a package in dev and then get 1.9 in production and find out that something broke between the two versions.

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