Install SQL Server 2019 big data tools

THIS TOPIC APPLIES TO:yesSQL Server noAzure SQL DatabasenoAzure SQL Data Warehouse noParallel Data Warehouse

This article describes the client tools that should be installed for creating, managing, and using SQL Server 2019 Big Data Clusters (preview). The following section provides a list of tools and links to installation instructions. Before deploying a big data cluster, configure the tools marked required on Windows or Linux.

Note

SQL Server 2019 release candidate is available as public preview. Public preview releases of SQL Server 2019 include CTP 3.2 and this release candidate. Prior to SQL Server 2019 CTP 3.2, SQL Server big data clusters was available as a limited public preview through the SQL Server 2019 Early Adoption Program.

Big data cluster tools

The following table lists common big data cluster tools and how to install them:

Tool Required Description Installation
python Yes Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Many parts of big data clusters for SQL Server use python. Install python
azdata Yes Command-line tool for installing and managing a big data cluster. Install
kubectl1 Yes Command-line tool for monitoring the underlying Kuberentes cluster (More info). Windows | Linux
Azure Data Studio - SQL Server 2019 release candidate (RC) Yes Cross-platform graphical tool for querying SQL Server. Install
SQL Server 2019 extension Yes Extension for Azure Data Studio that supports connecting to the big data cluster. Also provides a Data Virtualization wizard. Install
Azure CLI2 For AKS Modern command-line interface for managing Azure services. Used with AKS big data cluster deployments (More info). Install
mssql-cli Optional Modern command-line interface for querying SQL Server (More info). Windows | Linux
sqlcmd For some scripts Legacy command-line tool for querying SQL Server (More info). Windows | Linux
curl 3 For some scripts Command-line tool for transferring data with URLs. Windows | Linux: install curl package

1 You must use kubectl version 1.13 or later. Also, the version of kubectl should be plus or minus one minor version of your Kubernetes cluster. If you want to install a specific version on kubectl client, see Install kubectl binary via curl (on Windows 10, use cmd.exe and not Windows PowerShell to run curl).

Tip

To use kubectl with a previously deployed cluster on Azure Kubernetes Service (AKS), you must set the cluster context with the following Azure CLI command:

az aks get-credentials --name <aks_cluster_name> --resource-group <azure_resource_group_name>

2 You must be using Azure CLI version 2.0.4 or later. Run az --version to find the version if needed.

3 If you are running on Windows 10, curl is already in your PATH when running from a cmd prompt. For other versions of Windows, download curl using the link and place it in your PATH.

Which tools are required?

The previous table provides all of the common tools that are used with big data clusters. Which tools are required depends on your scenario. But in general, the following tools are most important for managing, connecting to, and querying the cluster:

  • azdata
  • kubectl
  • Azure Data Studio
  • SQL Server 2019 extension

The remaining tools are only required in certain scenarios. Azure CLI can be used to manage Azure services associated with AKS deployments. mssql-cli is an optional but useful tool that allows you to connect to the SQL Server master instance in the cluster and run queries from the command line. And sqlcmd and curl are required if you plan to install sample data with the GitHub script.

Install python offline

  1. On a machine with internet access, download one of the following compressed files containing Python:

    Operating system Download
    Windows https://go.microsoft.com/fwlink/?linkid=2074021
    Linux https://go.microsoft.com/fwlink/?linkid=2065975
    OSX https://go.microsoft.com/fwlink/?linkid=2065976
  2. Copy the compressed file to the target machine and extract it to a folder of your choice.

  3. For Windows only, run installLocalPythonPackages.bat from that folder and pass the full path to the same folder as a parameter.

    installLocalPythonPackages.bat "C:\python-3.6.6-win-x64-0.0.1-offline\0.0.1"
    

Download and install Azure Data Studio SQL Server 2019 release candidate (RC)

Azure Data Studio SQL Server 2019 RC provides a capabilities and features specifically for SQL Server 2019 RC.

For normal, production releases of Azure Data Studio, follow the instructions at Download and install Azure Data Studio.

Platform Download Release date Version
Windows User Installer (recommended)
System Installer
.zip
August 27, 2019 RC 1.11.0-insiders
macOS .zip August 27, 2019 RC 1.11.0-insiders
Linux .deb
.rpm
.tar.gz
August 27, 2019 RC 1.11.0-insiders

For details about the latest release, see the release notes.

Get Azure Data Studio for Windows

This release of Azure Data Studio includes a standard Windows installer experience, and a .zip file.

The user installer is recommended because it does not require administrator privileges, which simplifies both installs and upgrades. The user installer does not require Administrator privileges as the location is under your user Local AppData (LOCALAPPDATA) folder. The user installer also provides a smoother background update experience. For more information, see User setup for Windows.

User Installer (recommended)

  1. Download and run the Azure Data Studio user installer for Windows.
  2. Start the Azure Data Studio app.

System Installer

  1. Download and run the Azure Data Studio system installer for Windows.
  2. Start the Azure Data Studio app.

.zip file

  1. Download Azure Data Studio .zip for Windows.
  2. Browse to the downloaded file and extract it.
  3. Run \azuredatastudio-windows\azuredatastudio.exe

Get Azure Data Studio for macOS

  1. Download Azure Data Studio for macOS.
  2. To expand the contents of the zip, double-click it.
  3. To make Azure Data Studio available in the Launchpad, drag Azure Data Studio.app to the Applications folder.

Get Azure Data Studio for Linux

  1. Download Azure Data Studio for Linux by using one of the installers or the tar.gz archive:

  2. To extract the file and launch Azure Data Studio, open a new Terminal window and type the following commands:

    Debian Installation:

    cd ~
    sudo dpkg -i ./Downloads/azuredatastudio-linux-<version string>.deb
    
    azuredatastudio
    

    rpm Installation:

    cd ~
    yum install ./Downloads/azuredatastudio-linux-<version string>.rpm
    
    azuredatastudio
    

    tar.gz Installation:

    cd ~ 
    cp ~/Downloads/azuredatastudio-linux-<version string>.tar.gz ~ 
    tar -xvf ~/azuredatastudio-linux-<version string>.tar.gz 
    echo 'export PATH="$PATH:~/azuredatastudio-linux-x64"' >> ~/.bashrc
    source ~/.bashrc 
    azuredatastudio 
    

    Note

    On Debian, Redhat, and Ubuntu, you may have missing dependencies. Use the following commands to install these dependencies depending on your version of Linux:

    Debian:

    sudo apt-get install libunwind8
    

    Redhat:

    yum install libXScrnSaver
    

    Ubuntu:

    sudo apt-get install libxss1
    
    sudo apt-get install libgconf-2-4
    
    sudo apt-get install libunwind8
    

Supported Operating Systems

Azure Data Studio runs on Windows, macOS, and Linux, and is supported on the following platforms:

Windows

  • Windows 10 (64-bit)
  • Windows 8.1 (64-bit)
  • Windows 8 (64-bit)
  • Windows 7 (SP1) (64-bit) - Requires KB2533623
  • Windows Server 2019
  • Windows Server 2016
  • Windows Server 2012 R2 (64-bit)
  • Windows Server 2012 (64-bit)
  • Windows Server 2008 R2 (64-bit)

macOS

  • macOS 10.13 High Sierra
  • macOS 10.12 Sierra

Linux

  • Red Hat Enterprise Linux 7.4
  • Red Hat Enterprise Linux 7.3
  • SUSE Linux Enterprise Server v12 SP2
  • Ubuntu 16.04

Next steps

After configuring the tools, deploy a SQL Server 2019 big data cluster to Kubernetes in the Cloud or on-premises. For more information, see the following deployment articles:

For More info about big data clusters, see What are SQL Server 2019 Big Data Clusters?.