SQL Server and Ubuntu 18.04

Randolph West confirms that SQL Server on Linux will run on Ubuntu 18.04 even though it is not (yet) supported:

Although these screenshots show SQL Server 2019 preview CTP 2.3, this also applies to SQL Server 2017 on 18.04.2, because that’s what I had installed before upgrading the SQL Server version. However, as my friend Jay Falck pointed out on Twitter, Microsoft has stated publicly that it is not yet certified for production use:

Important, this does not change the support state of SQL Server 2017 on Ubuntu 18.04. Work to certify Ubuntu 18.04 with SQL Server 2017 is planned and we will announce when it will be supported for production use on this page. Until such as an announcement occurs, SQL Server 2017 on Ubuntu 18.04 should be considered experimental and for non-production use only.

Read on for Randolph’s thoughts on the issue.

R 3.5.3 Available

David Smith shares some info on R 3.5.3, released on Monday:

The R Core Team announced yesterday the release of R 3.5.3, and updated binaries for Windows and Linux are now available (with Mac sure to follow soon). This update fixes three minor bugs (to the functions writeLinessetClassUnion, and stopifnot), but you might want to upgrade just to avoid the “package built under R 3.5.4” warnings you might get for new CRAN packages in the future.

Click through for more info on this release, including where the name from each R release comes from.

Deploying SQL Server Versions with Kubernetes

Anthony Nocentino shows how we can upgrade or even downgrade our SQL Server containers using Kubernetes deployment scripts:

There’s a few things I want to point out in our YAML file. First, we’re using a Deployment Controller. This will implement a Replica Set of the desired number of replicas using the container imaged defined. In this case, we’ll have 1 replica using the SQL Server 2017 CU11 Image. A Replica Set will guarantee that a defined set of Pods are running at any given time, here we’ll have exactly one Pod. We’re using a Deployment Controller, which gives us move between versions of Replica Sets based off different container images in a controlled fashion…more on that in a second.

Read the whole thing.

Big SSAS News In SQL Server 2019 CTP 2.3

Chris Webb is excited about what’s in SQL Server 2019 CTP 2.3:

With the release of CTP 2.3 of SQL Server 2019 today there was big news for Analysis Services Tabular developers: Calculation Groups. You can read all about them in detail in this blog post:

https://blogs.msdn.microsoft.com/analysisservices/2019/03/01/whats-new-for-sql-server-2019-analysis-services-ctp-2-3/

In my opinion this is the most important new feature in DAX since… well, forever. It allows you to create a new type of calculation – which in most cases will be a time intelligence like a year-to-date or a previous period growth – that can be applied to multiple measures; basically the same thing that we have been doing in SSAS Multidimensional for years with the time utility/shell/date tool dimension technique. It’s certainly going to solve a lot of problems for a lot of SSAS Tabular implementations, many of which have hundreds or even thousands of measures for every combination of base measure and calculation type needed.

Click through for more of Chris’s thoughts and how calculation groups will make your life easier.

SQL Server 2019 CTP 2.3 Released

The SQL Server team announces SQL Server 2019 CTP 2.3:

At the SQL bits keynote today, we announced the release of SQL Server 2019 community technology preview 2.3, the fourth in a monthly cadency of preview releases. Previewed in September 2018, SQL Server 2019 is the first release of SQL Server to closely integrate Apache Spark and HDFS with SQL Server in a unified data platform.

There’s not a giant list but there are some interesting items on it. Click through for the full list.

Azure Data Lake Store Gen2

James Serra gives us the low-down on Azure Data Lake Store Gen2 now that it is generally available:

When to use Blob vs ADLS Gen2
New analytics projects should use ADLS Gen2, and current Blob storage should be converted to ADLS Gen2, unless these are non-analytical use cases that only need object storage rather than hierarchical storage (i.e. video, images, backup files), in which case you can use Blob Storage and save a bit of money on transaction costs (storage costs will be the same between Blob and ADLS Gen2 but transaction costs will be a bit higher for ADLS Gen2 due to the overhead of namespaces).

Looks like there are still some things missing from Gen2, so don’t automatically jump on an upgrade. Read the documentation first to make sure you aren’t relying on something which isn’t there yet.

Platform Compatibility and SSDT

Ed Elliott walks us through platform compatibility in SQL Server Data Tools:

Sometimes you don’t have the perfect development environment for SQL Server, sometimes you deploy to things like SQL Azure and want to test locally, for various reasons it is possible that you want to deploy to one version of SQL Server but set the project properties to a different version of SQL Server. If you find yourself in this situation you might need to use the parameter AllowIncompatiblePlatform
 which essentially says “I know I said the project is for SQL 2017 but I am deploying to SQL 2014”, anytime you say this you also sign the contract that says “If I am deploying to a lower version then I have made sure I haven’t used any keywords or object types that didn’t exist in that version and also if everything fails then so be it, I live with my choices every day”.

The story is a little complicated, but Ed straightens it out for us.

SQL Server Versions: Choose Your Own Adventure

Brent Ozar has a guide to help you choose which version of SQL Server to install:

Wait! Before you install that next SQL Server, hold up. Are you sure you’re using the right version?
I know, management wants you to stay on an older build, and the vendor says they’ll only support older versions, but now’s your chance to make your case for a newer version – and I’m gonna help you do it.
I’m going to go from the dark ages forward, making a sales pitch for each newer version.

My branch logic is easier: if you need the data today, SQL Server 2017. If you need the data later this year, SQL Server 2019. If you hate your company and yourself, SQL Server 6.5.

Migrating Lots Of Databases To SQL Server 2016

Andy Levy has a problem. Well, about 8000 of them. In part 1, he describes the plan:

How do you move eight thousand databases in a reasonable amount of time? I spent about an hour and a half one morning hashing ideas out w/ folks in the dbatools Slack channel, plus several conversations in the office and with our hosting provider.

Then, in part 2, he describes the execution:

We missed the estimated time for our go/no-go decision by five minutes. With the number of moving parts, databases in play, unexpected delays, and amount of testing we had to do, that’s pretty good! My colleague and I had some additional work we needed to take care of after the team declared the migration a success. Agent jobs needed to be enabled, overnight job startups monitored, things like that. We called it a day after about 14 hours in the office.

It was a nice success story, so check it out.

Query Store Changes

Milos Radivojevic shows us the Query Store default values and how they’ve changed between SQL Server 2017 and SQL Server 2019:

When you look at articles, posts and documents about new features and enhancements in SQL Server 2019 CTP2, you will find nothing about Query Store. However, there are some  graphical enhancements in SQL Server Management Studio in the version 18.0, also default configuration for Query Store attributes is changed too.
First SSMS 18.0. From this version, you can see another Query Store report – Query Wait Statistics. When you click on it, you can see aggregate waits per category in a given time interval (default is last hour). 

It looks like there have been some incremental improvements to Query Store. I think the defaults also make a bit more sense.

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