Podman checkpoint / restore and SQL Server 2019

One of Podman’s features is to be able to checkpoint and restore running containers. This means that Podman can “pause” a running container indefinitely, and then restart the container from where it left off on the same or another system. In this post, we’ll look at how you can do this with a container running Microsoft’s SQL Server.

Podman uses CRIU (Checkpoint/Restore In Userspace) to do the actual checkpointing and restoring of the processes inside of the container. This time I am using Podman 1.64 on Red Hat Enterprise Linux 8.2 with Microsoft’s SQL Server 2019. The documentation about how to set up SQL Server 2019 using Podman is on Microsoft’s site.

To start a container with SQL Server 2019 I am using this command on my RHEL 8 system:

## podman run -e 'ACCEPT_EULA=Y' -e 'MSSQL_SA_PASSWORD=Pass0..0worD' --cap-add cap_net_bind_service -p 1433:1433 -d mcr.microsoft.com/mssql/rhel/server:2019-CU1-rhel-8

If you want to persist your data even after running podman rm it is necessary, as described in the documentation, to mount a host directory as a data volume into your container using:

-v <host directory>:/var/opt/mssql

To access the database running in the container I am installing the sqlcmd tool using the curl command and then yum.:

## curl https://packages.microsoft.com/config/rhel/7/prod.repo > /etc/yum.repos.d/msprod.repo
## yum -y install mssql-tools unixODBC-devel

Once the container is running I am able to connect to the server process using the just installed sqlcmd:

## /opt/mssql-tools/bin/sqlcmd -S 127.0.0.1 -U SA -P Pass0..0worD
1> SELECT Name from sys.Databases
2> go
Name                                                                                                                         
----------------------------------------------------------------
master 
tempdb
model 
msdb 

(4 rows affected)
1>

To add some data to the database I created a few small SQL scripts:

#️ cat create-table.sql
CREATE TABLE things (id INT, name NVARCHAR(50))
GO
#️ for i in `seq 1 10000`; do echo "insert into things values($i, 'thing $i')"; done > insert.sql ; echo go >> insert.sql

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Introduction to Structured Query Language SQL pdf

SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.

Models for SQL exist. In any case, the SQL that can be utilized on every last one of the major RDBMS today is in various flavors. This is because of two reasons:

1. The SQL order standard is genuinely intricate, and it isn’t handy to actualize the whole standard.

2. Every database seller needs an approach to separate its item from others.

Right now, contrasts are noted where fitting.

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Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

• revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
• microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
• Anaconda 4.2 – Anaconda is an opensource Python package

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SCHEMAS in SQL Server -MS SQL Server – Zero to Hero Query Master

Introduction

This is part 3 of “MS SQL Server- Zero to Hero” and in this article, we will be discussing about the SCHEMAS in SQL SERVER. Before getting into this article, please consider to visit previous articles in this series from below,

• MS SQL Server – Zero to Hero Query Master – Part 1
• MS SQL Server – Zero to Hero Query Master – Part 2

A glimpse of previous articles

Part 1

In part one, we learned the basics of data, database, database management system, and types of DBMS and SQL.

Part 2

• We learned to create a database and maintain it using SQL statements.
• Best practice methods were also mentioned.

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Key Differences between SQL Server 2019 for Windows and Linux

Since the release of SQL Server 2017 for Linux, Microsoft has pretty much changed the entire game. It enabled a whole new world of possibilities for their famous relational database, offering what was only available in the Windows space until then.

I know that a purist DBA would tell me right away that the out of the box SQL Server 2019 Linux version has several differences, in terms of features, in regards to its Windows counterpart, such as:

• No SQL Server Agent
• No FileStream
• No System Extended Stored Procedures (e.g. xp_cmdshell)

However, I got curious enough to think “what if they can be compared, at least to some extent, against things that both can do?” So, I pulled the trigger on a couple of VMs, prepared some simple tests, and collected data to present to you. Let’s see how things turn out!

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Move SQL database files in SQL Server 2019 on Linux

In this article, I am going to explain how we can move the SQL database files to another location in Ubuntu 18.04. For the demonstration, I have installed Ubuntu 18.04, SQL Server 2019 on Linux on my workstation. You can read SQL Server 2019 on Linux with Ubuntu to understand the step-by-step installation process of the SQL Server 2019 on Linux. We will move database files of AdventureWorks2019 and Wideworldimportors database. To move the databases, we can use any of the following methods:

1. Backup and restore the database: I am going to explain this method by restoring the backup of the AdventureWorks2019 database
2. Detach and Attach database method: I will explain this method using the wideworldimportors database

First, let us view the current location of the database files.

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