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Category: Versions

Columnstore in Standard Edition

Erik Darling looks at how powerful (or not) columnstore indexes are in SQL Server Standard Edition:

The top plan is from Standard Edition, and runs for a minute in a full serial plan. There is a non-parallel plan reason in the operator properties: MaxDOPSetToOne.

I do not have DOP set to one anywhere, that’s just the restriction kicking in. You can try it out for yourself if you have Standard Edition sitting around somewhere. I’m doing all my testing on SQL Server 2019 CU9. This is not ancient technology at the time of writing.

The bottom plan is from Enterprise/Developer Edition, where the the plan is able to run partially in parallel, and takes 28 seconds (about half the time as the serial plan).

You get what you pay for in this case.

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Apache Spark 3.1 Released

Hyukjin Kwon, et al, announce Apache Spark 3.1:

Various new SQL features are added in this release. The widely used standard CHAR/VARCHAR data types are added as variants of the supported String types. More built-in functions (e.g., width_bucket (SPARK-21117) and regexp_extract_all (SPARK-24884) were added. The current number of built-in operators/functions has now reached 350. More DDL/DML/utility commands have been enhanced, including INSERT (SPARK-32976), MERGE (SPARK-32030) and EXPLAIN (SPARK-32337). Starting from this release, in Spark WebUI, the SQL plans are presented in a simpler and structured format (i.e. using EXPLAIN FORMATTED)

There have been quite a few advancements around the SQL side.

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The Editions of Powershell

Jeffrey Hicks gives us an update on the Powershell landscape:

The PowerShell community is beginning another year in the world of PowerShell 7. Most of you know what that means. However, there are newcomers to our community practically every day. Or I know there are occasional or reluctant users who might not pay enough attention to understand the world of PowerShell as it stands today. I wrote this post as a kind of virtual sticky note for the PowerShell community. Feel free to reference this post in your own work so that you don’t have to explain or define “Windows PowerShell” and “PowerShell”.

Click through to learn how to differentiate the two.

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Security Update for SQL Server

Randolph West takes a look at a patch:

Microsoft announced updates today for all supported versions of SQL Server, for a privilege escalation vulnerability that leverages Extended Events. For security reasons no further details have been provided, but you can expect more information in the near future, now that this update is public.

Be sure to grab the latest update for your version of SQL Server.

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December 2020 SQL Tools Releases

Drew Skwiers-Koballa gives us an update on where SQL Server tooling is at:

The December releases of Azure Data Studio 1.25 and SQL Server Management Studio (SSMS) 18.8 are now generally available.  Additionally, the mssql extension for Visual Studio Code has recently been updated to version 1.10.0. Read on to learn more about each of these updates and grab the latest versions of SSMS, Azure Data Studio, or the mssql extension for VS Code.

Read on to learn more.

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Apache Flink 1.12.0 Released

Marta Paes and Aljoscha Krettek announce a new release of Apache Flink:

– The community has added support for efficient batch execution in the DataStream API. This is the next major milestone towards achieving a truly unified runtime for both batch and stream processing.

Kubernetes-based High Availability (HA) was implemented as an alternative to ZooKeeper for highly available production setups.

– The Kafka SQL connector has been extended to work in upsert mode, supported by the ability to handle connector metadata in SQL DDL. Temporal table joins can now also be fully expressed in SQL, no longer depending on the Table API.

– Support for the DataStream API in PyFlink expands its usage to more complex scenarios that require fine-grained control over state and time, and it’s now possible to deploy PyFlink jobs natively on Kubernetes.

Read on for more details on these as well as other changes.

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Sampling the Population of SQL Server Instances

Brent Ozar has a breakdown of SQL Server adoption by version:

Ever wonder how fast people are adopting new versions of SQL Server, or what’s “normal” out there for SQL Server adoption rates, hardware sizes, or numbers of databases? Let’s find out in the summer 2020 version of our SQL ConstantCare® population report.

Out of the 3,650 servers sending in data recently, the most popular version of SQL Server is still 2016. 

It’s an interesting survey, but it’s important to remember with any survey what the biases are before drawing conclusions on the general population of all SQL Server instances. This is among ConstantCare users, so if I had a hunch about them, I’d say they’re going to blow out the middle versus gen pop—in other words, I’d expect 2019 and 2017 usage to be a bit higher across the world (and not just among ConstantCare users), but also 2005 (not pictured), 2008, and 2008 R2 to be higher. My hunch here is that the former are shops which have their act together and figure that they don’t need ConstantCare, and the latter are all of those “hidden” instances of SQL Server acting as the back end for small business websites and the like, where nobody even thinks about having a database administrator, much less paying for tooling. Nonetheless, these are interesting trends and even if I think the general population might look different, my data-less guess is that these numbers look reasonable.

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Azure Data Studio November 2020 Release

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

Another feature request was to provide support for parameters in a notebook. Parameterization is the ability to execute the same notebook with different parameters.

With this release of Azure Data Studio, users will now be able to utilize Papermill’s ability to parameterize, execute, and store notebooks. By stating the parameters cell as the first code cell in your notebook, it ensures that the injected parameters in the outputted parameterized notebook will be placed directly after the original parameters cell. That way the parameterized notebook will utilize the newly injected parameters instead of the original parameters cell.

Users can utilize Papermill CLI as well as the Python API  to pass in a new set of parameters quickly and efficiently as shown below.

That does look interesting.

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Keeping .NET Tools Up to Date

Max Trinidad has a public service announcement for us:

Have you installed any of the .NET Tools? Such as “.NET Interactive” and “PowerShell Global“, then you’ll need to remember, to update these tools manually.

These tools give you the ability to use create Jupyter Notebook using Python Kernel but also with C#, F#, and PowerShell 7 kernels.

Read on to see how to check if you need to update either of these.

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