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Category: Containers

Running SQL Server on a Windows Container

Jamie Wick takes us through the less-trodden path:

SQL Server containers are gaining popularity as a way of enhancing and standardizing development environments for Windows & Linux based SQL databases. SQL containers allow developers to have their ‘own’ dedicated copy of a database, usually without the need for extensive server infrastructures. Additionally, a single computer can host multiple containers, each with a different edition/version of SQL Server. This allows the user to quickly switch between environments, without the need to reinstall. Currently, a popular option for implementing containers on Windows-based computers uses Docker.

For those not familiar with containerization, here is a Microsoft article on Windows containers.

I’d definitely prefer to use Linux containers, even on Windows machines. But if Windows-based containers is your thing (or you need to use them for some reason), Jamie’s got you covered.

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Restoring Databases Inside a Container

Aaron Bertrand has a quick-and-easy method of restoring databases in a Docker container:

I have been using Docker containers for local development and testing for some time now; I first blogged about my steps into this brave new world back in late 2016. Most of the time, I just need to create some throwaway database, with a throwaway table, to prove a point or to validate an answer I’ve supplied.

Sometimes, though, I need to work with a real database. It’s a little trickier to do this in a container, because it’s isolated — I can’t just attach or restore from my Downloads folder. I could fire up a VM and attach there, but I actually don’t even use Parallels on my work laptop, and I find that using VMs leads to response times that are a lot more sluggish across the board.

It’s not too difficult to get files into your containers, provided your instance will have a total size less than the size of the container, and this quick tutorial proved to be very helpful.

Read on for the walkthrough. Aaron notes that this is a Mac-specific walkthrough, though the Windows and Linux versions are pretty similar as well, as we still create persistent volumes.

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MR3: Hive on Kubernetes

Alex Woodie reports on a DataMonad production:

MR3 is a software product developed by a team led by Sungwoo Park. The software, which is not open source, is sold by a Delaware-based software company called DataMonad. After prototyping a Java-based execution engine called MR2 in the 2013 timeframe, development of Scala-based MR3 began in 2015. The first release of MR3 was delivered in early 2018, and version 1.0 was released yesterday.

According to DataMonad, MR3 is an execution engine for big data processing, and Hive is the first and main application that’s been configured to run on it (Tez is also supported). The company says MR3 offers comparable performance to the latest release of Hive, dubbed LLAP, but without the technical complexity.

The closed-sourcedness is a bit of a downer, but I like having more competition in the space.

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Should DBAs Learn Kubernetes?

Randolph West makes me violate Betteridge’s Law of Headlines:

So this question, whether a SQL Server DBA really needs to know about Kubernetes, is really a question about whether DBAs need to know about the plumbing that runs the infrastructure upon which our databases reside.

In October 2018 I asked, “What is a DBA anyway?” It was a week after another post where I declared the DBA role “history.” My answer is:

Yes! You need to know Kubernetes if you’re a SQL Server DBA.

I agree with Randolph that it’s useful for a DBA to have at least some working understanding of Kubernetes, especially around being able to troubleshoot database issues on the platform. Read on for Randolph’s take on the matter.

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Using Windows Subsystem for Linux 2 in Windows 10

Max Trinidad is excited about Windows Subsystem for Linux 2:

First, I love WSL (Windows Subsystem for Linux)! It’s a great addition to Windows 10, and everyone should learn how to use it.

To get started, follow the instructions on how to get your WSL 1 Linux Distro installed. And, begin with installing Ubuntu 18.04.

Now, get Docker Desktop (), which can be installed in Windows 10 RTM Build 18363 with WSL 1.

One of the key benefits around WSL 2 is that your Docker containers will run natively rather than through a VM. That’s a pretty big deal in terms of performance and production-readiness. That Docker capability is currently in preview, but I’d expect it to make its way to production sooner than later.

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Deploying a Big Data Cluster to a Multi-Node kubeadm Cluster

Mohammad Darab shows how we can deploy a SQL Server Big Data Cluster on a multi-node kubeadm cluster:

There are a few assumptions before we get started:

1. You have at least 3 virtual machines running with the minimum hardware requirements
2. All your virtual machines are running Ubuntu Server 16.04 and have OpenSSH installed
3. All the virtual machines have static IPs and on the same subnet
4. All the virtual machines are updated and have been rebooted

Mohammad shows how to set up the cluster, configure Kubernetes, and then install Big Data Clusters. Definitely worth the read if you’re interested in building a Big Data Cluster on-premises.

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Spark on Docker on YARN on Cloud

Adam Antal has included all of the layers:

Bringing your own libraries to run a Spark job on a shared YARN cluster can be a huge pain. In the past, you had to install the dependencies independently on each host or use different Python package management softwares. Nowadays Docker provides a much simpler way of packaging and managing dependencies so users can easily share a cluster without running into each other, or waiting for central IT to install packages on every node. Today, we are excited to announce the preview of Spark on Docker on YARN available on CDP DataCenter 1.0 release.

Joking about stack length aside, this looks really useful.

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Upgrading SQL Server Windows Docker Containers

Emanuele Meazzo shows how you can upgrade SQL Server if you are using a Windows Docker container instead of Linux:

With the 1st CU for SQL 2019 released just yesterday, and Microsoft updating the docker image right away, the only natural response for me was to update the docker instance that I showed you how to deploy a few months back.

In theory, a docker container can’t be really “updated”, they’re meant to be stateless machines that you spin up and down responding to changes in demand; what we’re technically doing is creating a new container, based on a new image, that has the same configuration and uses the same persistent storage as the old one.

Read on to see how you can perform this upgrade without losing your data.

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